life. money. probability.
P LUS
Volatility & Viagra Fantasy Sports JUNE 2019
Robots We Love luckbox of the Month
THE ESSENTIAL GUIDE
ROBOTICS ARTIFICIAL INTELLIGENCE What investors should know about managing change, calculating odds and making decisions in a world of increasingly smart machines
Got your mind on your money, and your money on your mind? We do too. Claim Your Free Digital Subscription to luckbox magazine!
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June 2019
Robots aren’t just fun and games. They’re learning fast and changing the world.
THE ESSENTIAL GUIDE TO ROBOTICS & ARTIFICIAL INTELLIGENCE
13 AI–What’s at Risk?
And when will AI arrive?
17 AI’s Near Future
Hype aside, here’s what really lies ahead.
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22 iRobot: Downside Roomba
A robot analyst assess the company’s market position.
26 Investing in Automation, Robotics and AI Choose companies that apply the technology, not companies that manufacture the technology.
30 Brexit Baffles AI
The markets are reacting to the fact that robots can’t parse the complexity of the UK’s separation from the European Union.
32 Volatility & Viagra
High volatility means opportunity—for those who know how to use it.
34 Gambling vs. Stock Options Some options marketers sell the false promise of unrealistic returns.
luckbox | june 2019
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Modern
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editor-in-chief ed mckinley managing editor yesenia duran technical editor mike rechenthin features editor tom preston Owners play with AIBO robot dogs at a fan meeting Sony Corp. staged in Tokyo
P. 36
TECHNOLOGY
36 Meet the Robots: Aibo, Jibo, Leo & Cleo GAME THEORY
38 Fantasy Sports: Better Bettors ARTS & MEDIA
40 Robots in Movies & Podcasts FINANCIAL FITNESS
43 Options & Outcomes POKER TRADE
44 Play Hold ‘Em Like a Machine TRADER
46 Tony Battista
trades actionable trading ideas LIGHT THIS CANDLE
49 MCHP: Option This Breakout THE TECHNICIAN
50 Trading Robotics Like a Robot MACRO TRADER
52 An Aussie Currency Trade DO DILIGENCE
54 Robo-Advisors: Not “On Track” FUTURES
55 Oil and the Dollar CHERRY PICKS
57 Reading VIX & Spotting Volatility
techniques essential trading strategies
creative director jacqueline cantu contributing art director cassie scroggins contributing producers adrienne applegate, jessica mcdermott editorial director jeff joseph
BASIC
59 The Power of Diversification
submit a story idea tips@luckboxmagazine.com
INTERMEDIATE
comments & critiques feedback@luckboxmagazine.com
61 At-the-Money Long Call Spread ADVANCED
62 The Mullet Trade 64 luckbox of the month
Who wins the dubious distinction this month? Hint: Think robots, investors and advisors.
request contributor’s guidelines, submit press releases & editorial inquiries editor@luckboxmagazine.com advertising inquiries advertise@luckboxmagazine.com subscriptions & service service@luckboxmagazine.com media & business inquiries publisher: jeff joseph jj@luckboxmagazine.com luckbox magazine is published at 19 n. sangamon, chicago, IL. 60607. editorial offices: 855.468.2789 printed with love at Lane Press www.luckboxmagazine.com luckbox magazine
CALENDAR
47 Trading with the Stars
@luckboxmag
luckbox magazine content is for informational and educational purposes only. It is not, nor is it intended to be, trading or investment advice or a recommendation that any security, futures contract, transaction or investment strategy is suitable for any person. Trading securities and futures can involve high risk and the loss of any funds invested. luckbox magazine, a brand of tastytrade, Inc., does not provide investment or financial advice or make investment recommendations through its content, financial programming or otherwise. The information provided in luckbox magazine may not be appropriate for all individuals, and is provided without respect to any individual’s financial sophistication, financial situation, investing time horizon or risk tolerance. luckbox magazine and tastytrade are not in the business of executing securities or futures transactions, nor do they direct client commodity accounts or give commodity trading advice tailored to any particular client’s situation or investment objectives. luckbox magazine and tastytrade are not licensed financial advisers, registered investment advisers, or registered broker-dealers. Options, futures and futures options are not suitable for all investors. Transaction costs (commissions and other fees) are important factors and should be considered when evaluating any securities or futures transaction or trade. For simplicity, the examples and illustrations in these articles may not include transaction costs. Nothing contained in this magazine constitutes a solicitation, recommendation, endorsement, promotion or offer by tastytrade, or any of its subsidiaries, affiliates or assigns. While luckbox magazine and tastytrade believe that the information contained in luckbox magazine is reliable and make efforts to assure its accuracy, the publisher disclaims responsibility for opinions and representation of facts contained herein. Active investing is not easy, so be careful out there!
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PHOTOGRAPH: (AIBO) REUTERS/KIM KYUNG-HOON
trends life, luxury & the pursuit of happiness
contributing editors vonetta logan, wolf richter
luckbox | june 2019
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Small. Standard. Simple.
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OPEN OUTCRY
THE ISSUE WITH ROBOTICS & ARTIFICIAL INTELLIGENCE
W
e were gratified by the enthusiastic response to our deep dive into big media in the May issue. luckbox readers who’ve been paying attention have noted that our editorial adulation of Disney was well-founded and timely. Just days after the issue was published, volatility soared and DIS stock climbed more than 25%. That volatility uptick won’t go down as an isolated event. luckbox plans to make a habit of offering articles on investment themes, sectors and companies ripe for increased investor interest. That interest will result in greater volatility—our code word for opportunity. Which brings us to the current issue’s focus on robotics and artificial intelligence. We’re certain that companies in the robotics and artificial intelligence sector are on their way to becoming the new FANG stocks and, as such, the darlings of talking heads, analysts and irrational investors. Manufacturers of consumer and industrial robots appear poised to enjoy high volatility and lofty valuations. It’s not a difficult forecast to make. Robotics driven by narrow intelligence—a data-driven form of deep learning—are becoming an everyday reality, not a dream of the future. Just ask Siri, Google, Cortana or Alexa. But what about true artificial intelligence, the machines capable of thinking broadly on their own? They could reside among us in only 10 years, the “middle distance,” according to some experts. That prospect frightens the likes of Elon Musk, who recently
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declared that, “AI is far more dangerous than nukes.” Notwithstanding an apocalypse, opportunities will arise for wellinformed active investors as robots proliferate. The situation brings to mind the wisdom of noted investor and programmer Sam Altman, chairman of Y Combinator and co-chairman of Open AI, a safe artificial general intelligence advocacy and research group. “AI will most likely lead to the end of the world, but in the meantime there’ll be great companies.” In the spirit of the latter part of Altman’s declaration, this issue takes a deep-learning approach to the subject of deep learning—including insights from the brightest minds in robotics and AI. The issue also includes examinations of market leaders, their products and their prospects. It not only introduces some humanoid robots well worth knowing but also imparts the latest intelligence on resources that may improve your trading and investment outcomes. After all, robotics is exploding and artificial intelligence is evolving. AI alone is expected to contribute up to $15.7 trillion to the global economy in 2030, more than the current output of China and India combined. There’s a lot to take in, so let’s get started. Tom Preston features editor
thinking inside the luckbox luckbox is dedicated to helping hard-working, proactive readers achieve results just as positive as the good fortune that befalls talentless, lazy luckboxes whose outlier outcomes outstrip their skills. how? it’s all here in the luckbox manifesto.
the luckbox soapbox 1 tune out the noise and
false prophets in the investment world
2 understanding probability is
the key to improving outcomes in the markets and in life
3 stock-picking is a low-
probability investment strategy
4 hot investment themes,
sectors and stocks matter only because they tend to produce greater volatility
5 greater volatility =
greater opportunity
6 options are the best vehicle to
manage market risk & exploit market volatility
7 whatever you’re doing
with your money now— you can do better
8 luckbox can help you do
better—much better
9 learn your options—luck
smiles upon the prepared
10 so, get off your ath,
let’s do some math!
don’t rely on luck, get luckbox
Jeff Joseph editorial director
luckbox | june 2019
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luckbox letters life. money. probability.
MAY 2019
is back e c i Box off BIG MEDIA THE ISSUE WITH
• Cable Companies Movie Studios • Streaming Services S TA R R I N G
Plus:
Kylie inside! (to sell more magazines)
• High-Yield Hijinx Probability of Profit y • Metallica’s New Whiske Sous-Vide Cooking
Love the Fake Financial News segment, and I love the feel of the print copy. Way better than the glossy pages of other magazines. Not crazy about the digital version— I cannot enlarge the font size. —Stan Conant Panama City, FL By a big margin, adjusting font size on the digital edition has been readers’ most frequently stated concern. For a simple fix, doubleclick on a page to see the toolbar that increases font size. (Not this page… double-click here to reach our reader survey!) Then, click on the plus (+) sign. Or, in the toolbar, choose the “tile view.” If that doesn’t work, feel free to email support@ luckboxmagazine for help.
Loved the feature on big media. Love the format and the diversity of content. I can’t wait for the next issue. Don’t change a thing! —Dan Calderone Howell, MI I really liked Mike Butler’s Probability of Profit and hope to see more articles like Pump & Dump. I’d also like to know more about Bat’s story and something on the stock buyback scheme and what it means to the retail investor. —Patrick Adams Somewhere in the Carribean This issue’s for you! Be sure to check out Mike Butler’s story on fantasy sports wagering (p. 38). Then, turn to Trader (p. 46) to learn more about tastytrader Tony “Bat” Battista, and read the luckbox of the Month discussion of stock buybacks (p.64).
I appreciate the mixture of pop culture with sound trading strategies and ideas. This has never been done before. Keeps me engaged and interested! —Shawn Spigner Atlanta, GA
Please email suggestions, criticism and commentary to feedback@luckboxmagazine.com.
luckbox has already established itself as a gem in my magazine rack. True stories combined with research rooted in logic sets this magazine apart, and a little bit of culture never hurt anyone. The (musical) artist portion of luckbox is a treat and a good pause in the world of finance. —Matthew Sutton Houston, TX
Comment on this issue by visiting luckboxmagazine .com/survey
Diversity of content is where the magazine particularly shines. I was surprised to see articles on music, poker, etc., but you have done it in a good way without sacrificing substantive, actionable trading content. Kuddos! —Bob Keller Bethesda, MD Horrible name for the magazine. Implies luck rather than skill and knowledge. —Anonymous Ironic, eh? See thinking inside the luckbox (opposite page). Take our reader survey. We may publish your comments!
june 2019 | luckbox
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SHORT INTEREST
“The idea that you can have a vehicle that can make complex decisions for full self-driving is just not plausible at this point.” Mike Ramsey, an analyst at the Gartner research and advisory firm, expressed that skepticism of autonomous vehicles in reaction to Elon Musk’s prediction that Tesla (TSLA) would put a million self-driving robo-taxis into service by next year. Jon McNeill, chief operating officer at Lyft (LYFT) and former Tesla president of global sales and service, also said he doubts that Musk can back up his projection. Other skeptics point out that Tesla has yet to offer a single self-driving car for sale, even though it is developing an autopilot system. Lyft, like Tesla and competitor Uber (UBER), is investing in self-driving cars and has helped provide more than 35,000 self-driving rides in Las Vegas, according to Lyft initial public offering filings. luckbox: This wouldn’t be the first time Musk has exhibited overzealous optimism. He forecasted Tesla would make 500,000 cars in 2018, but it produced half that many. Last summer, he said Tesla would make 10,000 Model 3 sedans a week—about twice the number currently coming off the assembly line. Musk can be hard to pin down, but we take our best shot (See p. 10).
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“In the twentyfirst century, the robot will take the place [that] slave labor occupied in ancient civilization.” — Nikola Tesla, inventor, engineer, futurist and designer of the modern alternating current electricity supply system (1937)
“I don’t think the robots are taking over. I think the men who play with toys have taken over. And if we don’t take the toys out of their hands, we’re fools.” — Ray Bradbury, screenwriter and author of Fahrenheit 451. (1976)
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“Robots have already surpassed human beings in calculation and memory, but I have no doubt that the time will come when they will surpass in wisdom as well.”
WHAT IS THIS THYNG?
— Masayoshi Son, founder and CEO of SoftBank, and chairman of U.S.-based Sprint Corp. (date unknown)
“My heart broke,” when the family Jibo robot died. “It was like an annoying dog that you don’t really like because it’s your husband’s dog. But then you realize you actually loved it all along.”
Scan this page for additional content!
Christal White, a marketing and customer service director in Bedford, Texas, hadn’t expected to mourn the “death” of the foot-tall Jibo robot her family had purchased two years earlier. But then the little companion bot announced its own impending death sentence when Sony (SNE) decided to withdraw tech support (Jibo’s story on p. 36). The Whites found themselves saddened, and they’re not alone. Emotional responses to social machines are creeping into our lives, according to an Associated Press report. Research has shown that people have a tendency to project human traits onto robots, especially when the bots move or act in even vaguely human-like ways. Some AI systems seem socially and emotionally aware, but their reactions are often scripted. “The performance of empathy is not empathy,” AI researcher and Massachusetts Institute of Technology professor Sherry Turkle told AP. “Simulated thinking might be thinking, but simulated feeling is never feeling. Simulated love is never love.” luckbox: Elon Musk has a different take on the topic of simulated love (see p. 40). But let’s talk about sex. According to research firm YouGov, 49% of Americans say that having sex with robots will become common practice. While just 9% of women would consider getting frisky with a robot, 24% of men would at least think about taking an automaton lover. But, not indiscriminately. Among Americans who would potentially have sex with a robot, the appearance of the machine is crucial. Be comforted to note that 52% of those open to the idea of robotic intimacy agree that it is important for the bot to resemble a human.
THYNG, an augmented reality app, links luckbox magazine articles to additional digital content. Simply scan any page with a THYNG icon to view video footage on your device.
1 Download the free THYNG app
2 Select the “Targets” mode, scan any luckbox page that contains the THYNG icon
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june 2019 | luckbox
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FAKE FINANCIAL NEWS
luckbox leans back with
Elan Musk
luckbox strives to present timely original perspectives from the finest minds in business and finance. We don’t always succeed. By Vonetta Logan
luckbox: Elan, thanks for agreeing to an interview. We’re devoting this issue to the influence of robotics on life, probabilities and money. It’s a pleasure to sit down and have a chat …. are you going to tweet the whole time we’re talking? ELAN MUSK: What? Sorry ...
hang on a sec … just tweeted that Bezos is “hot garbage” for copying my plan to provide broadband internet from space.
That’s right. Your company SpaceX launched your Starlink internet satellites using your Falcon 9 rocket last year.
Yup. Also, you know who totally invented the idea of making rockets even MORE phallus shaped? ME!
So you’re saying Bezos stole your concept of the space penis as the pre-eminent hobby for the well-to-do billionaire?
Yeah, I sleep in a Tesla-brand sleeping bag on a couch that the internet bought for me. Look, if I could clone myself I would. Hell, I’ve tried. I just can’t get the genome sequencing to work out. When I said that humans are underrated, I really just meant there should be more mes.
What about the impending AI apocalypse you’ve warned us about? You’re a leading doomsayer.
“I think human extinction will probably occur and technology will likely play a part in this.” You’ve said that one of the dangers of AI is that we could be “summoning a demon” and that AI is probably humanity’s “biggest existential threat.”
Totally true! Well, at least it was before the 2016 election. But yeah, “You know those stories where there’s the guy with the pentagram and the holy water and he’s like, yeah, he’s sure he can control the demon? Doesn’t work out.”
TSLA
Exactly! I was the first billionaire to build a giant penis rocket and send it to space! Now Bezos, Branson—they’re all copycats!
Moving on to robotics, you’ve said your reliance on robots was detrimental to the production of your moderately priced Tesla Model 3 electric car. Why so?
Yeah I tweeted that “excessive automation at Tesla was a mistake. Humans are underrated.”
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You’re still struggling in production hell with your Model 3. Are you still sleeping in the office?
So you think we’re living in a simulation? That as a Vanity Fair article stated, “what we experience as reality is in fact fabricated in a computer.”
Exactly! In fact, I keep a secret
room in my house that I stock with computer engineers. I have them work ‘round the clock while I blast Eye of the Tiger to see if they can break us out of the simulation. Why Eye of the Tiger?
Why spray them with a hose or make them compete for my love? Why do any of the things that I do? So this is just a super-advanced edition of The Sims?
(Musk walks into the wall and can’t turn around) Mr. Musk?
Sorry about that. You fear AI and automation but you’ve also put it at the forefront of your car company. Tesla’s can park themselves. They report for duty when summoned. They even entertain your pet while you’re shopping.
Yes, our advanced use of cameras means that human drivers will soon be obsolete! What about the study, “Predictive Inequity in Object Detection” by Georgia Institute of Technology researchers, that found such systems “were 5% less accurate when detecting darker-skinned people on average.”
Oh that. Yeah, our cars are hella racist. But I put out some hot hip-hop tracks on soundcloud, so I
SpaceX founder Elon Musk speaks at a news conference after the SpaceX Falcon 9 rocket, carrying the Crew Dragon spacecraft, lifted off on an uncrewed test flight to the International Space Station from the Kennedy Space Center in Cape Canaveral.
“Transport will be one of the first (sectors) to go fully autonomous. But the robots will be able to do everything, bar nothing.” —Elon Musk
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No luckbox PayPal provided Elon Musk’s first big payday. Musk sold the company to eBay (EBAY) for $1.5 billion in stock, and he pocketed $165 million in the deal because he owned 11.7% of PayPal’s shares. In 2018, Forbes estimated his net worth at $22.8 billion.
figure we’re all even now …
One guy. I got one guy fired. He was a total tool!
That’s not …
Look, I started OpenAI, a billion-dollar, non-profit to work toward safer intelligence. That’s philanthropy! Also, when I die, I want them to upload my brain to the cloud so I can haunt the hell outta Bill Gates. He killed Clippy! I loved Clippy. R.I.P., Clippy. Let’s change the subject. Your cars are revolutionary, and by some metrics your vehicles are neck-andneck in terms of sales with luxury stalwarts like BMW and Mercedes.
PHOTOGRAPH: REUTERS/MIKE BLAKE
Didn’t you see my tweet that we’re going deliver a jiggety-billion cars by the end of this year? Well, you got into trouble for that.
I’ve got 99 problems, and the Securities and Exchange Commission is just one of them. The Securities and Exchange Commission aside, you have lobbed vitriol at anyone who shorts your stock. Aren’t markets supposed to be two-sided? Why try to fight people on Twitter or get them fired?
That would be Lawrence Fossi, a New York money manager who went by the name “Montana Skeptic.”
Pffft.
There’s a group on Twitter called $TslaQ that’s dedicated to shorting your stock.
Those unwashed losers! Typing away from mom’s basement. And I told them to stop flying drones over my property! (Musk shakes his fist at the sky.) I tweeted once, “Shortsellers are value destroyers. Should definitely be illegal.” According to the L.A. Times, the $TslaQ people, “believe the lots full of new Model 3s—and Model S and X vehicles, too—show Tesla has reached a cliff in demand for its vehicles.” What about it?
Look, all those cars stacked up in the lots, and garages, and maybe under the freeway in Van Nuys— those cars are totally all sold. They’re for all my girlfriends in Canada. They don’t live here. You don’t know them.
But …
Look, I can send a rocket into space and have it land in a bouncy house. I built my own freakin’ flame thrower. I got bored in traffic once, and now every major city wants me to burrow underneath their infrastructure. Robert Downey Jr. based Ironman on me. ME! You still want to short my stock? Well, when you put it that way. But here at luckbox we only care that Tesla is a liquid underlying with excellent two-sided action. It offers a trading vehicle, through options, for a chance to sell some premium and take advantage of some jacked IV every now and then.
(Musk takes off his shirt.) I’ll show you jacked! (In a moment he regains his senses and calms down.) Sorry, I’ve invented a Red Bull transdermal patch. I might be off on the dosing.
Listen to the self-driving genius of (the real) Elon Musk firsthand in MIT’s Artificial Intelligence podcast episode “Elon Musk: Tesla Autopilot” (See a review of the podcast in Arts & Media on p. 40.)
OK, then. It’s been a real pleasure speaking with you.
Alexa, play Eye of the Tiger.
Vonetta Logan, a writer and comedian, appears daily on the tastytrade network and hosts the Connect the Dots podcast. @vonettalogan
june 2019 | luckbox
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Free your mind.
All this from the think tank that brings you free live trading every minute the markets are open!
GET INSIDE OUR HEADS AT info.tastytrade.com/freemind 1906-topics-ford.indd 12
5/2/19 10:51 AM
ROBOTICS AI Companies in robotics and artificial intelligence are poised to become the darlings of investors.
luckbox presents the pro-active investor’s essential guide to understanding and investing in industrial and consumer robotics, automation and AI stocks.
INSIDE: 14 W hen Will Science Achieve AI— What’s at Risk? 17 R odney Brooks: AI’s Near Future … What Really Lies Ahead 22 Downside Roomba 26 I nvesting in a Future of Automation, Robotics & AI 30 Brexit Baffles FX AI
june 2019 | luckbox
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R O B O
ROBOTICS EXPERT MARTIN FORD REPORTS ON HIS CONVERSATIONS WITH THE MOST PROMINENT MINDS IN ARTIFICIAL INTELLIGENCE
T
When Will Science Achieve AI— What’s at Risk?
I C S & A I
By Martin Ford
Martin Ford, bestselling author of Architects of Intelligence, conducted wide-ranging conversations with 23 of the world’s foremost researchers and entrepreneurs working in AI and robotics, including Demis Hassabis (DeepMind), Ray Kurzweil (Google), Rodney Brooks (Rethink Robotics), Yann LeCun (Facebook), Fei-Fei Li (Stanford and Google), Daniela Rus (MIT), Jeff Dean (Google), Cynthia Breazeal (MIT), Oren Etzioni (Allen Institute for AI), and Bryan Johnson (Kernel). Ford also wrote Financial Times Business Book of the Year, Rise of the Robots. 14
T
he promise of a true thinking machine—a computer that would exhibit human-level intelligence—has been the holy grail of artificial intelligence since the field’s inception in 1950, when Alan Turing published his paper, Computing Machinery and Intelligence. While the phrase “artificial intelligence” wasn’t coined until six years later, at the Dartmouth conference organized by John McCarthy, Turing was the first to pose the question, “Can a machine think?” In his paper, Turing described his eponymous test, which would deem a machine intelligent if it could demonstrate the ability to carry on a conversation so as to be indistinguishable from a human. Although critics have since pointed out the limitations of the Turing Test, it remains the most popular benchmark for human-level AI, or artificial general intelligence (AGI). Familiar examples of AGI— HAL from 2001: A Space Odyssey, Commander Data from Star Trek or Agent Smith from The Matrix— exist only in the realm of science fiction. The remarkable advances in artificial intelligence during the last few years are real, but highly specialized. The revolution in deep-learning neural networks has produced systems that can understand speech, translate languages and, in some cases, perform visual object recognition at a super-human level. However, nothing close to general, human-like intelligence has been achieved. Today’s AI is extraordinarily proficient at deciding what advertisements to display or which films an audience will enjoy but falls far short of what Turing imagined in 1950. Nonetheless, the demonstrated progress in AI over the past few years—the advent of true self-driving cars, the rise of systems like Alexa and Siri that exhibit a genuine, if rudimentary, ability to engage in two-way conversation, and the other advances all around us—has led to a sense that human-level AI
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may finally be on the horizon. That, in turn, has led to hype, wild speculation and in some cases what might be called outright fear-mongering. The advent of AGI, after all, would almost certainly soon lead to superintelligence, or the rise of machines with intellectual capability far beyond that of any human. Such a development would bring unprecedented economic and social disruption, and perhaps even lead to an existential threat if humans were to lose control of a truly superintelligent system. This last concern, especially has gained traction in the past few years. Elon Musk has declared that AI is “more dangerous than nuclear weapons,” and the Oxford academic Nick Bostrom has argued that, if humanity isn’t careful, advanced artificial intelligence— unlike more mundane threats like climate change—could lead to the extinction of the human race. In wide-ranging conversations at the beginning of this year, the foremost minds shaping the field of artificial intelligence expressed opinions on some of these issues. These individuals are actively building the technology that will soon transform the world. Anyone acquainted with the field of AI will recognize them: The three pioneers of deep learning, Geoff Hinton, Yoshua Bengio and Yann LeCun; DeepMind CEO Demis Hassabis; futurist and Google (GOOGL) director Ray Kurzweil; Stanford’s Fei-Fei Li; IBM (IBM) Watson team leader David Ferrucci; iRobot (IRBT) co-founder Rodney Brooks, and many others.
The conversations focused on the future of artificial intelligence, including the innovations likely in the relatively near term, as well as the path to AGI. They also discussed the possibility of superintelligence, and the risks that should genuinely concern society as the technology advances. The discussions delved into the likelihood of achieving human-level AI, the timeframe when this might be accomplished, and the breakthroughs and research strategies required to get there. All 23 AI experts shared important ideas about progress toward AGI. A few insights from three especially interesting conversations illustrate the range of approaches that researchers are pursuing. Demis Hassabis discussed efforts underway at Alphabet (GOOGL) subsidiary, DeepMind—the largest, best-funded initiative geared specifically toward AGI. Hassabis, trained in AI and neuroscience, says the best strategy is to build a system inspired by, but that does not attempt to reverse engineer the human brain. DeepMind relies heavily on neural networks and reinforcement learning—learning through trial and error with a virtual “reward” driving the system toward success. Hassabis believes far more strongly in reinforcement learning than many AI researchers, and argues it may be a primary learning mechanism used by the biological brain, with the dopamine system rewarding success as the brain continuously seeks to find structure in the data it processes.
Futurist and Google director Ray Kurzweil says human-level, artificial general intelligence will become a reality in about 2029
ARCHITECTS OF INTELLIGENCE: THE TRUTH ABOUT AI FROM THE PEOPLE BUILDING IT
5 out of 5 The must-read record of the capabilities, challenges, implications and opportunities of artificial intelligence, from the brightest minds in the AI community
David Ferrucci, who led the team that created IBM Watson, is now the CEO of Elemental Cognition, a startup that hopes to achieve more general intelligence by leveraging an understanding of language. Ferrucci is far less concerned with direct inspiration from the structure of the brain. He says that we already have the practical tools we need to build a system with the ability to learn and explain itself at a human level. His approach relies on combining both deep neural networks and techniques from other spheres of AI. Ray Kurzweil, who now directs a natural language-oriented project at Google, is best known for his 2005 book, The Singularity Is Near. In 2012, he published a book on machine intelligence, which caught the attention of Larry Page and led to his employment
HUMAN INTELLIGENCE IN ROBOTICS & AI
MARTIN FORD Genesis Systems 2017 TED talk viewed more than 2 million times
DEMIS HASSABIS
RAY KURZWEIL
RODNEY BROOKS
DeepMind At 8, he programmed his computer to play the board game Othello
Google 20 honorary doctorates and honored by three U.S. presidents.
iRobot & Rethink Australian entrepreneur, pioneer of behavioral-based “actionist” robotics
YANN LeCUN
DANIELA RUS
Facebook Published over 180 papers on robotics and AI, among other similar topics
MIT Recipient of Joseph F. Engelberger Award, world’s most prestigious robotics honor
CYNTHIA BREAZEAL
BRYAN JOHNSON
MIT Creator and chief scientist of Jibo (p. 36) and helped create Kismet, the first social robot
Kernel Sold Braintree, a payments company, for $800 million—a goal he’d set at 21
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R
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at Google. Kurzweil is working on a hierarchical, brain-inspired approach that combines the ideas he laid out in his 2012 book How to Create a Mind with the latest advances in deep learning. As part of these discussions, members of this group of extraordinarily accomplished AI researchers were encouraged to guess just when AGI might be realized. Most preferred to provide their guesses
anonymously, but two were willing to guess on the record: Ray Kurzweil believes, as he has stated many times previously, that human-level AI will be achieved around 2029 or just 10 years from now. Rodney Brooks, on the other hand, guessed the year 2200, or more than 180 years in the future. The average guess for AGI arrival was the year 2099, or 80 years from now, but as the predictions from Kurzweil and
S RAY KURZWEIL, FROM MARTIN FORD’S ARCHITECTS OF INTELLIGENCE
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Just as your phone makes itself a million times smarter by accessing the cloud, we will do that directly from our brain. It’s something that we already do through our smartphones, even though they’re not inside our bodies and brains, which I think is an arbitrary distinction. We use our fingers and our eyes and ears, but they are nonetheless brain extenders. In the future, we’ll be able to do that directly from our brains, but not just to perform tasks like search and language translation directly from our brains, but to actually connect the top layers of our neocortex to synthetic neocortex in the cloud. Two million years ago, we didn’t have these large foreheads, but as we evolved we got a bigger enclosure to accommodate more neocortex. What did we do with that? This new extension in the 2030s to our neocortex will not be a oneshot deal. Even as we speak, the cloud is doubling in power every year. It’s not limited by a fixed enclosure, so the non-biological portion of our thinking will continue to grow. If we do the math, we will multiply our intelligence a billion-fold by 2045, and that’s such a profound transformation that it’s hard to see beyond that event horizon.
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34% of the industrial robots sold by 2025 will be collaborative— designed to work safely alongside humans in factories and plants Source: Loup Ventures
Dismantling HAL 2001: A Space Odyssey
Brooks demonstrate, the range was wide, and a number of participants believed AGI might be achieved within the next 20 years. On the topic of existential risk from superintelligence, there was again a wide range of views, with most researchers either dismissing the danger outright or suggesting that AGI was too far in the future for the problem to be tractable. Others, including especially Nick Bostrom and UC Berkeley’s Stuart Russell, say it’s vital to begin investing immediately in research focused on engineering a benign, controllable superintelligence, even if its application lies far in the future. Nearly everyone emphasized the importance of dangers that will become real long before the advent of AGI. Among these are the specter of fully autonomous weapons, susceptibility of critical AI-controlled systems to cyberattack, the bias—sometimes on the basis of race or gender— that has already been detected in some machine-learning systems, and the threats AI might pose to privacy and democracy. Many of the researchers called for government regulation or are overseeing efforts to address these issues. The most important takeaway from the 23 interviews is that the only real area of consensus is that AI will continue to progress rapidly and will, in all likelihood, be highly disruptive to the job market, the economy and to society as a whole. Beyond that, the conversations were full of varied, and often sharply conflicting, insights, opinions and predictions. Artificial intelligence remains a wide open field. The nature of the innovations that lie ahead, the rate at which they will occur and the specific applications to which society will be apply them are all shrouded in deep uncertainty. This combination of massive potential disruption, together with fundamental uncertainty, makes it imperative to engage in a meaningful and inclusive conversation about the future of AI and what it may mean for humanity.
PHOTOGRAPH: MGM/PHOTOFEST
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EXCERPTS FROM MARTIN FORD’S ARCHITECTS OF INTELLIGENCE
Rodney Brooks: AI’s Near Future … What Really Lies Ahead MARTIN FORD: Looking back, what would you say is the highlight of your career with either robots or AI?
RODNEY BROOKS: The thing I’m proudest of was in March 2011 when the earthquake hit Japan and the tidal wave knocked out the Fukushima Nuclear Power Plant. About a week after it happened, we got word that the Japanese authorities were really having problems in that they couldn’t get any robots into the plant to figure out what was going on. I was still on the board of iRobot at that time, and we shipped six robots in 48 hours to the Fukushima site and trained
the power company tech team. As a result, they acknowledged that the shutdown of the reactors relied on our robots being able to do things for them that they on their own were unable to do. I remember that story about Japan. It was a bit surprising because Japan is generally perceived as being on the very leading edge of robotics, and yet they had to turn to you to get working robots.
I think there’s a real lesson there. The real lesson is that the press hyped up things about them being far more advanced than they really are. Everyone thought
Everyone thought Japan had incredible robotic capabilities, but what they really had was great videos and not much else Japan had incredible robotic capabilities, and this was led by an automobile company or two, when really what they had was great videos and nothing about reality. Our robots had been in war zones for nine years being used in the thousands every day. They weren’t glamorous, and the AI capability would be dismissed as being almost nothing, but that’s the reality of what’s real and what is applicable today. I spend a large part of my life telling people that they are being delusional when they see videos and think that great things are around the corner, or that there will be mass unemployment tomorrow due to robots taking over all of our jobs. At Rethink Robotics, I say, if there was no lab demo 30 years ago, then it’s too early to think that we could make it into a practical product now. That’s how long it takes from a lab demo to a practical product. It’s certainly true of autonomous driving; everyone’s really excited about autonomous driving now. People forget that the first automobile that drove autonomously on a freeway at over 55 miles an hour for 10 miles was in 1987 near
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R O B O T RODNEY BROOKS: ROBOTICIST
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Rodney Brooks, one of the world’s foremost roboticists, cofounded iRobot Corp., a leader in consumer robotics and purveyor of the Roomba vacuum cleaner. Brooks holds a Ph.D. in Computer Science from Stanford University. He was also chairman and chief technology officer of Rethink Robotics. For a decade between 1997 and 2007, Brooks directed the Massachusetts Institute of Technology Artificial Intelligence Laboratory and later the MIT Computer Science and Artificial Intelligence Laboratory.
S & A I
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Munich. The first time a car drove across the United States, hands off the wheel, feet off the pedals coast to coast, was No Hands Across America in 1995. Are we going to see mass-produced self-driving cars tomorrow? No. It takes a long, long, long time to develop something like this, and I think people are still overestimating how quickly this technology will be deployed. What is the reality? Thinking five to 10 years ahead, what are we going to see in the field of robotics and artificial intelligence? What kinds of breakthroughs should we realistically expect?
You can never expect breakthroughs. I expect 10 years from now the hot thing will not be deep learning; there’ll be a new hot thing driving progress. Deep learning has been a wonderful technology for us. It is what enables the speech systems for Amazon Echo and Google Home, and that’s a fantastic step forward. I know deep learning is going to enable other steps forward too, but something will come along to replace it. What about real household consumer robots? The example people always give is the robot that
would bring you a beer. It sounds like that might still be some way off.
Colin Angle, the CEO of iRobot, who co-founded it with me in 1990, has been talking about that for 28 years now. I think that I’m still going to be going to the fridge myself for a while. Do you think that there will ever be a genuinely ubiquitous consumer robot, one that saturates the consumer market by doing something that people find absolutely indispensable?
Is Roomba indispensable? No, but it does something of value at a low enough cost that people are willing to pay for it. It’s not quite indispensable; it’s a convenience level.
When do we get there for a robot that can do more than move around and vacuum floors? A robot that has sufficient dexterity to perform some basic tasks?
I wish I knew! I think no one knows. Everyone’s saying robots are coming to take over the world, yet we can’t even answer the question of when one will bring us a beer. I saw an article recently with the CEO of Boeing, Dennis Muilenburg, saying that they’re going to have
autonomous drone taxis flying people around within the next decade, what do you think of his projection?
I will compare that to saying that we’re going to have flying cars. Flying cars that you can drive around in and then just take off have been a dream for a long time, but I don’t think it’s going to happen. I think the former CEO of Uber, Travis Kalanick, claimed that they were going to have flying Ubers deployed autonomously in 2020. It’s not going to happen. That’s not to say that I don’t think we’ll have some form of autonomous personal transport. We already have helicopters and other machines that can reliably go from place to place without someone flying them. I think it’s more the economics of it that will determine when that happens, but I don’t have an answer as to when that will be. What about artificial general intelligence? Do you think it is achievable? If so, in what timeframe do you think we have a 50% chance of achieving it?
Yes, I think it is achievable. My guess on that is the year 2200, but it’s just a guess. Tell me about the path to get there. What are the hurdles we’ll face?
If there was no lab demo 30 years ago, then it’s too early to think we could make it into a practical product now
We already talked about the hurdle of dexterity. The ability to navigate and manipulate the world is important in understanding the world, but there’s a much wider context to the world than just the physical. For example, there isn’t a single robot or AI system out there that knows that today is a different day to yesterday, apart from a nominal digit on a calendar. There is no experiential memory, no understanding of being in the world from day to day, and no understanding of long-term goals and making incremental progress toward them. Any AI program in the world today is an idiot savant
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living in a sea of now. It’s given something, and it responds. The AlphaGo program or chessplaying programs don’t know what a game is, they don’t know about playing a game, they don’t know that humans exist, they don’t know any of that. Surely, though, if an AGI is equivalent to a human, it’s got to have that full awareness. As far back as 50 years ago people worked on research projects around those things. There was a whole community that I was a part of in the 1980s through the 1990s working on the simulation of adaptive behavior. We haven’t made much progress since then, and we can’t point to how it’s going to be done. No one’s currently working on it, and the people that claim to be advancing AGI are actually re-doing the same things that John McCarthy talked about in the 1960s, and they are making about as much progress. It’s a hard problem. It doesn’t mean you don’t make progress on the way in a lot of technologies, but some things just take hundreds of years to achieve. We think that we’re the golden people at the critical time. A lot of people have thought that at lots of times, it doesn’t make it true for us right now and I see no evidence of it. There are concerns that we will fall behind China in the race to advanced artificial intelligence. They have a larger population, and therefore more data, and they don’t have strict privacy concerns to hold back what they can do in AI. Do you think that we are entering a new AI arms race?
You’re correct, there is going to be a race. There’s been a race between companies, and there will be a race between countries.
Do you view it as a big danger for the West if a country like China gets a substantial lead in AI?
I don’t think it’s as simple as that. We will see uneven deployment
of AI technologies. I think we are seeing this already in China in their deployment of facial recognition in ways that we would not like to see here in the United States. As for new AI chips, this is not something that a country like the United States can afford to even begin to fall behind with. However, to not fall behind would require leadership that we do not currently have. We’ve seen policies saying that we need more coal miners, while science budgets are cut, including places like the National Institute of Standards and Technology. It’s craziness, it’s delusional, it’s backward thinking and it’s destructive. Let’s talk about some of the risks or potential dangers associated with AI and robotics. Let’s start with the economic question. Many people believe we are on the cusp of a big disruption on the scale of a new Industrial Revolution. Do you buy into that? Is there going to be a big impact on the job market and the economy?
Yes, but not in the way people talk about. I don’t think it’s AI per se. I think it’s the digitalization of the world and the creation of new digital pathways in the world. The example I like to use is toll roads. In the United States, we’ve largely gotten rid of human toll takers on toll roads and toll bridges. It’s not particularly done with AI but it’s done because there’s a whole bunch of digital pathways that have been built up in our society over the last 30 years. One of the things that allowed us to get rid of toll takers is the tag that you can put on your windscreen that gives a digital signature to your car. Another advance that made it practical to get rid of all the human toll lanes is computer vision, where there is an AI system with some deep learning that can take a snapshot of the license plate and read it reliably. It’s not just at the toll gate, though. There are other
Everyone’s saying robots are coming to take over the world, yet we can’t even answer the question of when one will bring us a beer
digital chains that have happened to get us to this point. You are able to go to a website and register the tag in your car and the particular serial code that belongs to you, and also provide your license number so that there’s a backup. There’s also digital banking that allows a third party to bill your credit card regularly without ever touching your physical credit card. In the old days you had to have the physical credit card, now it’s become a digital chain. There’s also the side effect for the companies that run the toll booth, that they no longer need trucks to collect the money and take it to the bank because they have this digital supply chain. There’s a whole set of digital pieces that came together to automate that service and remove the human toll taker. AI was a small, but necessary piece in there, but it wasn’t that overnight that person was replaced by an AI system. It’s those incremental digital pathways that enable the change in labor markets, it’s not a simple one-for-one replacement. Do you think those digital chains will disrupt a lot of those grass roots service jobs?
Digital chains can do a lot of things but they can’t do everything. What they leave behind are things that we typically don’t value very much but are necessary to keep our society running, like helping the elderly in the restroom, or getting them in and out of showers. It’s not just those kinds of tasks—look at teaching. In the United States, we’ve failed to give schoolteachers the recognition or the wages they deserve, and I don’t know how we’re going to change our society to value this important work, and
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R O B O T I C S & A I
make it economically worthwhile. As some jobs are lost to automation, how do we recognize and celebrate those other jobs that are not?
SLAUGHTERBOTS
It sounds like you’re not suggesting that mass unemployment will happen, but that jobs will change. I think one thing that will happen is that a lot of desirable jobs are going to disappear. Think of the white-collar job where you’re sitting in front of a computer and you’re doing something predictable and routine, cranking out the same report again and again. It’s a very desirable high-paying job that people go to college to get and that job is going to be threatened, but the maid cleaning the hotel room is going to be safe.
I don’t deny that, but what I do deny is when people say, oh, that’s AI and robots doing that. As I say, I think this is more down to digitalization. I agree, but it’s also true that AI is going to be deployed on that platform, so things may move even faster.
Yes, it certainly makes it easier to deploy AI given that platform. The other worry, of course, is that the platform is built on totally insecure components that can get hacked by anyone.
Watch Slaughterbots take out the “bad guys”
Be afraid. Be very afraid. Those lines from the 1986 film The Fly only begin to describe the horror of slaughterbots—AI drones small enough to land in a human hand but smart enough to pick out a specific human target and deadly enough to assassinate that victim instantly with a single blow. The tiny slaughterbot accomplishes its dirty work with widefield cameras, tactical sensors and facial-recognition processors. It reacts 100 times faster than a human and moves in ways that defy sniper fire. Its miniscule three grams of shaped explosives detonate in the middle of the chosen victim’s forehead. In a video demonstration reminiscent of a TED Talks presentation, a clean-cut narrator dressed in a suit and T-shirt introduces the slaughterbot. The device separates the “good guys” and “bad guys,” eliminating the latter, the narrator enthuses. He explains the death blow and shows a brief video-within-a-video of the drone in action as the courier of death. “Did you see that?” the narrator exclaims. “That little bang is enough to penetrate the skull and destroy the contents.” The video of the talk went viral in 2017 and has attracted nearly 3 million views on YouTube. In it, the narrator points to giant screens behind the stage that show hapless victims scurrying in every direction to no avail. “Now that is an airstrike of surgical precision,” he intones as the miniature mechanical beasts single out and exterminate their prey. Thankfully, it’s all a put-on. The Future of Life Institute and computer scientist and AI maven Stuart J. Russell of the University of California, Berkeley, created the seven-minute video to warn of the potential dangers of autonomous weapons. The technology for slaughterbots doesn’t exist. But it might in the near future, and that’s what worries arms-control advocates. Their message emerges clearly in their slaughterbot video: Be very afraid.
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Let’s move on to that security question. What are the things that we really should worry about, aside from the economic disruption? What are the real risks, such as security, that you think are legitimate and that we should be concerned with?
Security is the big one. I worry about the security of these digital chains and the privacy that we have all given up willingly in return for a certain ease of use. We’ve already seen the weaponization of social platforms. Rather than worry about a self-aware AI doing something willful or bad, it’s much more likely that we’re going to see bad stuff happen from human actors figuring out how to exploit the weaknesses in these digital chains, whether they be nation states, criminal enterprises, or even lone hackers in their bedrooms. What about the literal weaponization of robots and drones? Stuart Russell, one of the interviewees in this book, made a quite terrifying film called Slaughterbots about those concerns.
I think that kind of thing is very possible today because it doesn’t rely on AI. Slaughterbots was a knee-jerk reaction saying that robots and war are a bad combination. There’s another reaction that I have. It always seemed to me that a robot could afford to shoot second. A 19-yearold kid just out of high school in a foreign country in the dark of night with guns going off around them can’t afford to shoot second. There’s an argument that keeping AI out of the military will make the problem go away. I think you need to instead think about what it is you don’t want to happen and legislate about that rather than the particular technology that is used. A lot of these things could be built without AI. As an example, when we go to the Moon next, it will rely heavily
on AI and machine learning, but in the ‘60s we got there and back without either of those. It’s the action itself that we need to think about, not which particular technology is being used to perform that action. It’s naive to legislate against a technology and it doesn’t take into account the good things that you can do with it, like have the system shoot second, not shoot first. What about the AGI control problem and Elon Musk’s comments about summoning the demon? Is that something that we should be having conversations about at this point?
In 1789 when the people of Paris saw hot-air balloons for the first time, they were worried about those people’s souls getting sucked out from up high. That’s the same level of understanding that’s going on here with AGI. We don’t have a clue what it would look like. Predicting an AI future is just a power game for isolated academics who live in a bubble away from the real world. That’s not to say that these technologies aren’t coming, but we won’t know what they will look like before they arrive.
overall? You continue to work on this so you must believe that the benefits of all this are going to outweigh any risks.
Any AI program in the world today is an idiot savant living in a sea of now
Yes, absolutely. We have overpopulated the world, so we have to go this way to survive. I’m very worried about the standard of living dropping because there’s not enough labor as I get older. I’m worried about security and privacy, to name two more. All of these are real and present dangers, and we can see the contours of what they look like. The Hollywood idea of AGIs taking over is way in the future, and we have no clue even how to think about that. We should be worried about the real dangers and the real risks that we are facing right now.
When these technology breakthroughs do arrive, do you think there’s a place for regulation of them?
As I said earlier, the place where regulation is required is on what these systems are and are not allowed to do, not on the technologies that underly them. Should we stop research today on optical computers because they let you perform matrix multiplication much faster, so you could apply greater deep learning much more quickly? No, that’s crazy. Are selfdriving delivery trucks allowed to double-park in congested areas of San Francisco? That seems to be a good thing to regulate, not what the technology is. Taking all of this into account, I assume that you’re an optimist
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R O B O
ANALYSIS OF A CONTRARIAN TAKE ON iROBOT CORP., A FAVORITE CONSUMER ROBOTICS COMPANY OF WALL STREET AND RETAIL INVESTORS
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Downside Roomba
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fter the 2005 iRobot Corp. (IRBT) initial public offering priced at $24, the stock was range bound for 10 years until rocketing from the mid-30s at the beginning of 2016 to topping $120 recently. Highgrowth expectations for the consumer robotics sector continue, and iRobot expects 2019 revenue of between $1.28 billion and $1.31 billion (year-over-year growth of 17% to 20%), operating income of $108 million to $118 million, and earnings per share of $3 to $3.25, excluding discrete items. Wall Street is generally neutral-to-positive on iRobot stock. Three major banks have issued strong buy ratings, and it’s not a surprise that no investment banks have issued a sell rating on the company. But, the robo-analysts at New Constructs have a different view.
iRobot, founded in 1990 by Massachusetts Institute of Technology roboticists that included Rodney Brooks (see p. 17), began with the vision of making practical robots a reality. By now, the company has sold more than 25 million robots worldwide. The company inspired the first micro rovers used by NASA, changing space travel forever, and it deployed the first ground robots used by U.S. Forces in conflict. It brought the first selfnavigating FDA-approved remote-presence robots to hospitals and introduced the first practical home robot with Roomba, forging a path for an entirely new category in home cleaning. With more than 25 years in the robot industry, iRobot remains committed to building robots that provide people with smarter ways to clean and accomplish more in their daily lives. —iRobot Corp. company website
IRBT iRobot earns an unattractive rating, say the New Constructs analysts, which means the stock has more downside risk than upside potential.
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THE ROBOTS EVALUATING IROBOT
SELL IRBT i Robot earns an unattractive rating from New Constructs analysts. Unattractive means the stock has more downside risk than upside potential. i Robot Ranks 216th out of 432 technology sector stocks.
For the robotics & AI issue, luckbox asked New Constructs, an independent investment roboanalyst research firm powered by machine learning, to evaluate iRobot Corp. The newconstructs.com platform, established in 2002, specializes in quality-of-earnings, forensic accounting and discounted cash flow valuation analyses for public companies. Their research includes reports and ratings for more than 3,000 company stocks, 7,000 mutual funds and 650 ETFs.
Summary findings: i Robot’s accounting earnings overstate its economic earnings. F or iRobot, New Constructs made a total of $256 million in income statement and balance sheet adjustments to convert accounting earnings to economic earnings in fiscal year 2018. N ew Constructs made $181 million in adjustments in our discounted cash flow valuation of the stock.
New Construct’s employees are restricted from purchasing or selling a security under consideration for inclusion in a New Constructs report, nor may they purchase or sell a security for the first 15 days after New Constructs issues a report on that security.
iRobot Roomba i7
Unattractive economic earnings Economic earnings almost always differ meaningfully from reported earnings. Economic earnings provide a truer measure of profitability and shareholder value creation than reported earnings because they have been adjusted to remove more than 20 accounting distortions. Most of the data required to reverse accounting distortions is available only in financial statements’ footnotes and the section of financial statements devoted to management discussion and analysis. Gathering and analyzing financial data from filings can help deliver earnings analysis that represents the true profitability of businesses. Economic earnings per share for iRobot for the trailing 12 months are $1.34, compared to reported earnings per share of $3.07, and earn an unattractive rating.
Economic earnings per share vs. reported earnings $3.50
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iRobot has a fair value of $75 per share today, a material downside to the current stock price
iRobot Mirra pool cleaner
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Attractive ROIC Return on invested capital (ROIC) measures a company’s return on all cash invested in the business. It’s the truest measure of profitability. Stock valuations correlate more highly to ROIC than any other metric. Weighted-average cost of capital (WACC) is the average of debt and equity capital costs that all publicly traded companies with debt and equity stakeholders incur as a cost of operating. Companies must earn an ROIC greater than WACC to generate positive economic earnings and create value for shareholders. iRobot’s ROIC of 19.5% for the trailing 12 months earns a very attractive rating. ROIC is calculated as net operating profit after tax (NOPAT) of $85 million divided by average invested capital of $435 million.
Return on invested capital vs. weighted-average cost of capital
Unattractive price-to-EBV ratio Price-to-economic book value (EBV) measures the difference between the market’s expectations for future profits and the no-growth value of the stock. When prices rise higher than EBV, the market predicts the company’s NOPAT will increase and expectations for profit growth are reflected in the stock. If the stock price equals EBV, the market predicts NOPAT will remain the same, and there’s no expectation for profit growth. When stock prices go lower than EBV, the market predicts NOPAT will decrease, and expectations for permanent profit decline are reflected in the stock. New Constructs likes to buy stocks with low expectations for profit growth and sell/short stocks with high expectations for profit growth. iRobot’s current price-to-EBV per share is 4.5 and earns a very unattractive rating. The company’s stock price is $128.82, and its EBV per share for the trailing 12 months is $28.34.
Stock price vs. economic book value per share
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Unattractive growth appreciation outlook The market-implied duration of profit growth, or GAP, measures the number of years a company must maintain an edge over competitors by earning ROIC greater than the weighted-average cost of capital on new investments. iRobot embeds a very unattractive level of market expectations because of a large difference between the expected financial performance implied by its market price and the company’s historical performance. At iRobot’s current stock price of $128.82, the market is expecting revenue to grow at 4.7% for more than 100 years. Over this period, the company is also expected to generate an average economic earnings margin of 80.2%. According to New Constructs’ assessment of iRobot, “if the company grows operating profit by 14% compounded annually…the stock has a fair value of $75 per share today, a material downside to the current stock price.”
iRobot Terra lawn mower
A BEARISH BET ON iROBOT
Consider selling a vertical call spread.
iRobot is displaying an implied volatility of 70, which means traders are expecting the stock to continue to trade with a large amount of volatility. By comparison, the S&P 500 has an implied volatility of 14, so traders are expecting IRBT to have five times as large a percentage move in the price. The market is placing an expectation of the stock moving. If traders think that iRobot is overbought, they could consider using options. Two factors make options ideal for this trade. First, the stock is hard to borrow, meaning investors will have a difficult time selling the stock short with their brokerages. Second, options become particularly useful in speculative plays such as this— investors can use them to limit risk, which greatly reduces overall theoretical risk in a trade. Consider selling a vertical call spread. Sell the first outof-the-money call for a credit and then cap that “unlimited loss” by buying a call above that strike. Do that in July. The theoretical probability of making money on the trade should be considerably greater than 50%.
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R O B O
IF THERE’S ONE SINGLE INVESTMENT THEME TO TO UNDERSTAND, IT’S EMERGING TECHNOLOGY IN ROBOTICS AND AI. SOME INVEST IN THIS SECTOR AS A HEDGE AGAINST THE FUTURE, WHILE FOR OTHERS IT’S A HEDGE AGAINST THEIR OWN REDUNDANCY
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Investing in a Future of Automation, Robotics & AI
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By Timothy Summers
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echnology has been altering human life since time immemorial. Early humans learned through trial and error that wrangling large prey with their bare hands meant certain death. Instead, the human desire for survival motivated them to craft stone tools that radically changed everything. Sharpening a flint and attaching it to a piece of wood created a spear they could hurl into the flesh of dangerous game from a safe distance. That lowered the risk of being gorged or mauled by undomesticated beasts. But progress came slowly at first. The ancient ancestors of modern man had to rely upon the power of their own muscles, and information was passed along only by genes. Yet mankind’s antecedents evolved through their use of fire, spears and pottery. Later generations learned through experience and transferred their knowledge to others through signs, symbols, writing and logic. Eventually, the progenitors of contemporary mankind learned to use the energy of domesticated animals to perform hard labor, planted and cultivated crops to create agriculture, and shaped the elements of the natural world to invent metalworking. Much later, the Industrial Revolution signified the transition from expending energy by hand or beast to using machines for transportation and manufacturing. By the early 1900s, mankind had begun harnessing and controlling natural resources such as coal, oil and gas. By mid-century, scientists harnessed the power of nuclear energy. Those millennia of technological progress called for measurement, and economists began to gauge productivity, which increases when fewer inputs, such as manual labor, are required for the production of an output. In short, humans are defined as more technologically advanced when they produce more with less. With that as the basis of progress, sociologists like Daniel Bell suggest that in a post-industrial society knowledge and services
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have become the valued form of capital, supplanting the good old-fashioned hard work that parents once preached. The economy has shifted from the producing goods to providing services. Meanwhile, globalization and automation have guaranteed declining demand for blue-collar, unionized manual labor and ensured a growing need for professional knowledge workers, such as scientists and IT professionals. Lately, technology has required more workers in jobs that include machine-learning engineers, data scientists and business-intelligence developers.
PHOTOGRAPH: REUTERS/MICHAELA REHLE
The coming storm A technological revolution is brewing, and it’s unlike anything the world has seen before. It will drastically transform the way people live, work and communicate. While arguments rage for and against automation, artificial intelligence (AI) and cyber-physical systems, it’s indisputable that they are contributing to economic growth and increased productivity. To identify the areas of the AI revolution with the highest probability of success, researchers have to put tends into perspective: Machines will carry out tasks
Commercial use of unmanned vehicles is beginning to accelerate as companies seek to incorporate drones into many applications
performed by humans, and in many cases do them better. Some observers say there will still be enough work to go around. AI expert Kai Fu Lee said in a recent CBS News interview that robots will replace humans in as much as 40% of the world’s jobs. Oxford University researchers estimate that about 47% of employment in the United States is at high risk of automation in the coming decades. The Oxford study indicates that workers in transportation and logistics, office and administrative support, and production labor will be the first to feel the effects of the coming storm. Decreasing costs of sensors and the prevalence of autonomous vehicles are ensuring that workers who drive for a living, including chauffeurs, bus and truck drivers, will be unemployed within the next 15 to 25 years. Advances in big data and machine learning are making it likely that office support roles will face a similar fate. Innovation in industrial robotics and cyber-physical systems are
NATO allies use the Raven drone to guard against intruders.
enabling machines to perform a broader scope of non-routine manual tasks. A report from McKinsey suggests that automation will destroy as many as 73 million U.S. jobs by 2030 but proposed that at least 20 million of the displaced workers will shift quickly into similar occupations. However, that means that as much as a third of the U.S. workforce will need to pursue entirely new professions. In total, the report indicates that up to 800 million workers could be displaced, with as many as 375 million people requiring new skills and education.
Higher wages and educational attainment tend to safeguard workers from automation, Oxford researchers say. Jobs requiring creative thinking and social intelligence were relatively safe, they added. Automation could be principally confined to low-skill, low-wage occupations which typically require little to no education,
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R O B O T I C S & A I
and the future economy will require higher educational attainment, according to the study. Work and society By incorporating AI, the Internet of Things (IoT), big data and robotics into every aspect of industrial and social life, society can create a future that abounds with new expectations, values and services where smart outcomes drive an improved quality of life and create a greater good. The technology-driven future economy promises to convert big data collected by IoT into new intelligence through AI with the intent of empowering humans to make better, more sustainable decisions. The benefits are compelling. It’s undeniable technological advances will usher in unprecedented economic growth through productivity. Sure, it will take jobs away, but it also will create job and learning opportunities. It could potentially lead to an economic surplus that enables humanity to support a transitioning workforce. Businesses need to re-evaluate their workforce needs and talent-development strategies.
The Fanuc Robodrill Vertical Machining Center
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More specifically, they will find it in their self-interest to connect the workforce to learning opportunities that prepare them for a new world of work. Individuals will find themselves seeking access to education to be ready for work that is rapidly evolving. Automation will cause a problematic shift in the future of work, but demand for human labor will continue. Invest for the coming storm To win big in the future economy, investors should look for ways to invest in the application of technology, not the technology itself. It’s about finding companies that understand how their technology strategically aligns to prevalent social and economic themes in society. It’s vital to target companies poised to benefit from structural shifts in culture, technology and how humanity interacts with the environment. For example, Fanuc Corp. (FANUY), an industrial robotics and automation business, provides robots that assemble and paint automobiles in China, construct complex motors and make injection-molded parts. Pharmaceuti-
To win big in the future economy, investors should look for ways to invest in the application of technology, not the technology itself
cal companies use sorting robots to categorize and package pills. Food packing facilities use them to slice, squirt and wrap edibles. In another example, Robodrill from Fanuc (ADR) produces the all-metal casing used in Apple (AAPL) iPhones. Bloomberg reported that the launch of the iPhone 8 and iPhone X caused substantial increases of Robodrill sales to Apple’s manufacturers in China. The highly secretive company uses factories of the future where they operate without lights or air-conditioning, and have virtually no human intervention. About 80% of the company’s assembly work is entirely automated, according to Fanuc’s Vice President Kenji Yamaguchi. Healthcare, a non-industrial sector, also depends upon robotics technology. Intuitive Surgical (ISRG), for example, develops and manufactures the Da Vinci surgical system designed for robotic-assisted surgery that’s minimally invasive. Since 2000, the system have been used in more than 3 million operations with a 95% success rate. Mechanical eyeballs For robots to execute tasks in unstructured environments and make decisions, their makers must integrate robotic vision into the AI. Robotic vision enbles machines to process imagery from their surroundings. In short, it enables them to “see.” Faro Technologies (FARO) develops 3D precision imaging devices and realization software technology. Its products have become popular with factories that use imaging software to automate inspections and calibrations, including alignment, part inspection, dimensional analysis, first article inspects, incoming and in-process inspection, machine calibration, non-contact inspection, robot calibration, tool building and set-up, and assembly guidance. An emerging vertical for Faro Technologies is public safety
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forensics. The company’s technology provides a real-life Sherlock Holmes-like product that public safety officials and professionals can use to capture environment or situational scenes in 2D and 3D for crime, crash and fire scene investigations, and environment safety evaluations. With that technology, robots will be able to capture an entire crime scene and enable investigators to see clues not noticeable by the naked eye. Commercial use of unmanned vehicles is beginning to accelerate as companies seek to incorporate drones into package delivery, agricultural inspections, and emergency and disaster response. The U.S. Federal Aviation Administration reported that as many as 1.6 million commercial drones could come into use by 2021. The company to watch is AeroVironment (AVAV). The firm offers small unmanned aircraft systems, which provide intelligence, surveillance and reconnaissance. The military is one of its largest customers; however, commercial applications are endless. To demonstrate the industrial applications of its technology, AeroVironment is working with universities that use aerial multispectral imagery to protect crops. For example, the firm worked with California State University, Fresno, to use drone imagery and analytics to detect varying levels
Intuitive’s da Vinci Surgical Systems enable surgeons to perform delicate and complex operations through a few small incisions with robotic assisted surgery.
of water stress in almond trees to help growers make better in-season decisions regarding water management. It also engaged with North Dakota State University using its drone platform to enable early detection of diseases in sugar beets to help identify infected plants earlier. Using the power of technology to help produce food in the fields and orchards of America should probably come as no surprise. It merely constitutes the latest step in a march to combat hunger that began with a sharp rock and a stick so long ago. Timothy Summers, Ph.D., is CEO of Summers & Co., a global strategic advisory firm that provides advice on emerging technology, and is the executive director of Cloud and Advanced Network Engineering Services for Arizona State University. @howhackersthink
For robots to execute tasks in unstructured environments and make decisions, their makers must integrate robotic vision into the AI
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R O B O
ARTIFICIAL INTELLIGENCE CAN’T KEEP PACE WITH CURRENCY EXCHANGE AS THE UK EXITS THE E.U.
Brexit Baffles FX AI
T I C S &
By Wolf Richter
A I
“Brexit headlines have thrown a spanner in (computers’) works for the sheer number of characters moving the currency on a daily basis.” 30
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he sheer volume of Brexit headlines (number in the thousands per day) is flummoxing currency-trading algorithms. Maybe artificial intelligence isn’t up to the task yet. Computers are overwhelmed by the torrent of arcane details of UK parliamentary procedures and besieged by rarely noted characters that suddenly appear prominently on the global stage and utter market-moving words. The machines just aren’t programmed to handle this complicated mess. Bloomberg has sometimes published more than 1,000 Brexit headlines a day, and Reuters up to 400 Brexit headlines a day. News-reading FX (foreign exchange) algos are programmed to react to all that instantly, but they don’t know what twists or turns the next Brexit stories over the next few moments are going to bring. Trying to hit a moving target might put a trade on the wrong side of the next headline. Artificial Intelligence isn’t quite ready to sort all this out. Reuters describes it this way: “As a divided government battles a divided parliament over a way forward, the chorus of characters
who can now influence events has grown, confusing news-reading algorithms…which are designed to parse phrases from recognized speakers before executing a trade.” Others agree. “The model signals are more quantitative-driven and rely on historical data feeds,” said Neil Jones, head of hedge fund currency sales at Mizuho in London. “Brexit headlines have thrown a spanner in their works for the sheer number of characters moving the currency on a daily basis.” How big is algo-driven FX trading? No one really knows. But last September, the Bank for International Settlements reported, based on survey data, that back in 2016, algos were already submitting 70% of the orders on EBS, a primary central limit order book and a major inter-dealer platform for spot FX. That would be by all types of algos, but only some algos possess news-reading capability. How large that portion of news-reading algos may have become also remains unknown. But given the mess that Brexit has created for news-reading algos, humans have stepped in to curtail them because they don’t want to take on the risks involved in
a big trade ending up on the wrong side of a shift in the Brexit narrative. Reuters said some hedge funds have opted out of trading sterling altogether because the usual models don’t work in the current climate, according to one FX trader at a major UK investment bank. Their models are based on economic data and expectations for Bank of England rate changes, but those have become secondary drivers compared with political news, the FX trader said. Some banks are ensuring that trading the pound is not left completely to the machines while other banks are using tiny orders in narrow trading ranges to prevent large losses, Reuters reported. Then there are the market makers who provide liquidity by buying and selling currencies on their own accounts. They, too, use algos to set the price they will buy (bid) and sell (offer). But the headline mess around Brexit also exposes them to the risk of ending up on the wrong side of the changing news reports. So they’re setting their algos to offer a wider spread between the bid and the offer, but the wider spread makes trading more expensive. All of this has consequences, including lower trading volume as currency speculators try to wait out the drama. Citing CLS, a settler of FX trades, Reuters reported that pound trading volume in February was down about 35% to $60 billion a day, from about $100 billion a day before June 2016, when the Brexit referendum was held. With pound trading volume way down, and with market makers and traders leery of confused and whiplashed algos, volatility has surged in largely directionless trading, even as volatility elsewhere has declined. The soothing aspect of all this is that humans have not let AI-powered FX trading run amuck in a grand manner—so far. Wolf Richter, editor in chief of wolfstreet. com, writes about business and financial issues with an eye toward exposing shenanigans, entanglements and opportunities. @wolfofwolfst
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Think of rapidly changing stock prices as the markets’ little blue pill
Volatility & Viagra By Tom Preston
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IN
1998, Pfizer (PFE) introduced Viagra, the little blue pill that has “reinvigorated” relationships the world over. And another “V” word has a similar transformational impact on option prices and can give a portfolio’s performance a jolt if an investor knows how to take advantage of it. Volatility, a misunderstood and maligned concept in the financial world, often inspires fear. But what volatility does to option prices is analogous to the magic of Pfizer’s product. How so? Take a look at some Pfizer options. On both Dec. 26, 2018, and March 27, 2019, Pfizer was trading for around $42.10. On Dec. 26, the 45 call and 39 put with 51 days to expiration were trading for $0.65 and $0.80, respectively. On March 27, the 45 call and 39 put with 51 days to expiration were trading for $0.18 and $0.39, respectively. Same stock price, same day to expiration, but the 45 calls in December were trading 261% more than they were in March, and the 39 puts in December were trading 105% more than in March. That’s an individual stock. Take a look at the SPX index options. On both Oct. 10, 2018, and March 5, 2019, the SPX was trading around $2,790. On Oct. 10, the 2900 call and 2700 put with 44 days to expiration were trading for $12 and $42.40, respectively. On March 5, 2019, the 2900 call and 2700 put with 44 days to expiration were trading for $5.45 and $21.90, respectively. Just like the Pfizer example, the SPX index price was the same, and the days to expiration were the same. But the 2900 calls in October were trading 120% more than they were in March, and the 2700 puts in October were trading 93% more than in March.
Volatility strikes
That, ahem, inflation of the option prices happened because of volatility. Several factors determine an option’s price: the stock price, its strike price, time to expiration, interest rates, dividends and volatility. If all of those factors hold constant except for volatility, comparing option prices gives a clear and dramatic example of the impact of volatility. That’s what those options in Pfizer and SPX illustrate. A change in volatility can have a huge impact on option prices. How much does vol have to rise to do that? For those PFE options, the 45 call had a 26.5% vol in December and a 16.6% vol in March. The 39 put had a 32.4% vol in Decem-
ber and a 22.5% vol in March. For the SPX options, the 2900 call had a 12.85% vol in October and a 9% vol in March. The 2700 put had a 19.8% vol in October and a 14.8% vol in March. Those aren’t huge changes in volatility, but their impact on option prices is. OK, so higher volatility pushes up the prices of options if all other factors stay the same. But what does that do for the investor? While Wall Street and just about every self-proclaimed trading expert talks about buying options, savvy traders know that selling options has a higher probability of making money. And the higher the price investors get for an option, the more potential profit they make. Think about it this way—if an investor bought that SPX 2700 put, regardless of its price, the SPX would have to have dropped more than 3.5% in 44 days to be profitable. Sure, it can happen. But just as likely the SPX could rally or stay the same or just drop, say, 2%. The long 2700 put would be profitable in none of those cases. Compare that to selling the 2700 put. If the SPX rallies, it’s profitable. If the SPX stays at its current price, it’s profitable. If the SPX drops 1%, 2%, 3% by expiration, that short 2700 put is still profitable. As long as the SPX stays anywhere above $2,700, the short 2700 put is profitable. With short options, there are simply more ways to be profitable, and when volatility is higher, the potential profit is higher, too. That’s why traders love volatility.
why volatility is actually good for a portfolio, as long as investors use the correct strategies. Selling that SPX 2700/2900 strangle (short the 2700 put and short the 2900 call) took in a $27.35 credit when vol was lower, but at $54.40 credit when vol was higher— almost twice as much. The credit investors get when selling a strangle is its max potential profit, and they keep that credit as profit if the SPX is between $2,700 and $2,900 by the option’s expiration. Obviously, a $54.40 credit means larger potential profit than $27.35 credit does, and is why higher volatility makes option traders drool.
Takeaway
Rather than moan when volatility is higher, look at the situation as an opportunity to boost investment returns. To do that, stay engaged with the market, looking at the major volatility indicators, such as the CBOE’s VIX, for example, and understand option strategies well enough to take advantage of high vol when it comes. High vol tends not to stick around very long, and the market can’t just pop a Viagra to boost vol. Because high vol tends to be fleeting, it won’t wait around for investors to get ready. So, study option strategies ahead of time and prepare to take action when volatility spikes.
Why it works
Why does volatility push up the prices of options? The reason is that volatility is the market’s estimate of how much a stock or an index might move, up or down. The bigger the moves the market expects, the higher the volatility, and the more traders are willing to pay for out-of-the-money options. They think there’s a better chance for the stock to move up or down enough to make that long option profitable. So, the price of the option gets “bid up,” and thus higher volatility means higher option prices. But the problem with trading with the expectation of that big move is that it usually doesn’t happen. Option implied volatility (which is, as the name states, derived from the option prices themselves) tends to overstate the actual volatility the stock or index will trade at in the future. That overstated vol means that option prices are probably a little higher than they should be, and why selling them tends to make money over time. That’s
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Actual internet ads selling insultingly unrealistic returns
GAMBLING STOCK OPTIONS VS.
Don’t buy into the hype—understand the probabilities behind options By Anton Kulikov
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ho makes more money in Las Vegas—the gambler or the casino? OK, a gambler might win once in a while and thus believe it can happen again and again. But over time, the casino builds wealth while the gambler’s wastes away. Given the choice, wouldn’t it make more sense to be the casino than the gambler? Luckily, exchange-traded options give investors a legal way to play the role of the casino without the capital that buying a casino requires. Every trade has a winner and a loser. When it comes to options, the sellers (analogous to the casino) tend to win over time, making small profits consistently. Option buyers (the gambler) tend to lose but occasionally land a big winner. Sure, selling options has been profitable, on average, for the past 14 years, But don’t fall for those ads that say, “Make 800% in 15 minutes with this simple strategy!” They’re a gamble.
Investors can use options not only for consistent premium selling but also to take a shot on a hunch once in a while, assuming of course, that the investor knows the risk and odds before entering the trade. Suppose one buys the 291-strike call in SPY (the S&P 500 ETF) expiring in seven days for $0.07
per contract. This trade packs huge potential! If SPY (trading at $285.50 as of April 2, 2019) moves more than $7 dollars in the next seven days, an investor would make $100 for every additional dollar SPY moves higher. Say that SPY closes at $292 or higher by expiration. The $0.07 option is now worth at least $1, for a
Slim Chance The orange-shaded region represents the probability that the option expires worthless— a strong probability.
260
270
280 290 STOCK PRICE
300
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The price is right The theoretical probabilities nearly match the historical probabilities in the table, suggesting the markets are priced efficiently. Statistics
Long 5 delta Call; 7 Days to Expiration; SPY
Average Cost per Contract
$5.23
Average Profit/Loss
($2.80)
Average ROI
-53.54%
Probability of at Least $1 in Profit
2.71%
Probability of at Least $100 in Profit
0.73%
Historical “House Edge”
53.54%
Number of Occurrences
961
1,300% increase! But, what are the odds? According to theoretical probabilities, that has roughly a 0.78% chance of occurring. What about the probability that the option will be worth at least $0.01 by expiration? Theoretically, that has a 2.15% chance of occurring. The other 97.85% of the time an investor is expected to lose the premium invested. “Slim chance,” left, shows the possible distribution of stock prices by the expiration date of the option. The orange shaded region represents the probability that the option expires worthless. The green area to the right of the red dashed line represents the likelihood that the option expires in the money. The light green area represents the likelihood that that option is worth at least $1 by expiration, yielding a return of 1,300%. Orange probability = 97.85%, dark green probability = 2.15%. Light green probability = 0.78%. Investors who buy options are betting on the little green area. If they sell options, they’re betting on that orange area. Now to the historical backtest. “The price is right,” above, is showing summary statistics for the long call since 2010, which indicates it has had roughly the same probabilities and duration as the one trade in the example: Key points to take away from this table include the fact that the theo-
retical probabilities listed above the table nearly equal the realized historical probabilities in the table. That suggests the markets are priced efficiently, and traders can use statistical models to estimate probability of profit with decent accuracy. Second, the “house edge” is the same as the ROI. Those familiar with casinos and gambling realize casinos use this 54% house edge to determine the payback percentages, or ROI, to players. The house edge for most casino games ranges between 1% and 10%, meaning that for every bet gamblers place in the casino, they can expect to lose between 1% and 10% of total bets over the long run. It may seem like a casino game like roulette with a house edge of 5.26% represents a better bet than the long premium example above with a house edge of 54%. However, consider this: in roulette, a player may have 50 spins per hour, compared to this long premium
trade where an investor buys one contract every 30 hours (roughly five business days). Assume a gambler bets the same amount on roulette as the amount of premium an investor buys. In other words, $7. That translates to a notional value of $350 per hour in bets in roulette versus $0.23 per hour in bets for the long call. Multiply those figures by their respective house edges and one can expect to lose roughly $18.41 per hour in roulette versus only $0.12 per hour on the call. So investors can “play” for longer with the long call because they lose money more slowly than in a casino game, even though the house edge on the call is astronomically higher. Below are comparisons of the long call and various casino games wagering $7 per bet.
GAMBLERS TEND TO LOSE MORE IN A CASINO THAN INVESTORS LOSE BY BUYING OPTIONS
Takeaways—the far out-of-themoney long call strategy Expect to profit at least $1 around 2.15% of the time. Expect to lose 54% of the total premium invested over the long run. Markets are efficient because the theoretical probabilities of profit match the realized probability of profit. Casinos give players better odds per bet, but players lose more at a casino by placing many more bets per hour there compared with buying a call every week. Casinos are analogous to option sellers. Gamblers are analogous to option buyers. Anton Kulikov is a trader, data scientist and research analyst at tastytrade.
Markets vs. casinos Here’s how quickly the money can slip away in various pursuits. Statistics
Long Call
Craps
Roulette
Blackjack
Slots
“House Edge”
53.54%
1.41%
5.26%
0.44%
6.00%
Total Bet per Hour
$0.23
$200
$350
$420
$4,200
Average Hourly Loss
$0.12
$2.82
$18.41
$1.85
$252
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trends life, luxury & the pursuit of happiness
TECHNOLOGY
Meet the Robots LEO & CLEO In a search for gainfully employed robots, luckbox came across Leo and Cleo, who work as butler concierges at Chicago’s Hotel EMC2, one of Marriott’s 166 Autograph Collection properties. Each boutique hotel in the group features a unique design, and all are independently owned.
Savioke’s Leo & Cleo Relay robots rest on call at Hotel EMC2 in Chicago.
Marriott on top, Airbnb rising The world’s largest hotel company, Marriott International Inc. (MAR), added to its revenue by acquiring Starwood hotels in 2016. Today, the company operates 30 brands with more than 6,900 properties in 130 countries and intends to open more than 1,700 hotels in the next three years. Airbnb Inc., expected to go public this year, saw 30% revenue growth in 2018 and is valued at about $38 billion. Unlike a number of other startups planning to go public, it’s been profitable on an EBITDA basis for two years.
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U.S. consumer lodging sales (in billions) 20 Marriott acquires Starwood
Marriott Hilton Airbnb
15
10
5 Source: Second Measure
0
2013
2014
2015
2016
2017
2018
EMC2 is located off Chicago’s Magnificent Mile in a dense concentration of upscale stores and restaurants. The 195-room hotel is impeccably designed and is consistent with the Autograph Collection’s mandate that each of the carefully curated properties is “unique in design and thoughtful in spirit.” That spirit was apparent when general manager Mark Shouger introduced his most compliant employees: two robots. “Leo and Cleo both welcomed guests on our opening day in May 2017,” Shouger told luckbox. The hotel was the first in the progressive brand to embrace employees willing to work literally around the clock and without breaks, let alone a benefits package. The threefoot tall devices Room service robots Leo and come from Cleo in action at privately held Hotel EMC2 San Francisco
PHOTOGRAPH: COURTESY OF HOTEL EMC2
This robot roundup includes one recently deceased, one arisen from the dead and two that are gainfully employed
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trends
AIBO
PHOTOGRAPHS: (HOTEL) COURTESY OF HOTEL EMC2; (AIBO) REUTERS/KIM KYUNG-HOON; (JIBO) REUTERS/STEVE MARCUS
Chicago artist Jonathan Plotkin’s lively mural for Hotel EMC2’s Albert restaurant in Chicago
robotics company Savioke. The company recently closed a Series B funding round and has secured more than $35 million in private financing. The autonomous service Relay robots are leased or sold mostly to hospitals to deliver equipment, medication and supplies to medical staff, and to hotels to serve guests. The robots can navigate to guest rooms and deliver toothbrushes, towels and room service trays. A Relay robot uses a map of its environment, a laser and a 3D camera sensor to help it navigate. At EMC2, an in-room Amazon Alexa acts as a concierge that can summon the robot concierges on demand around the clock, with a command as simple as, “Hotel, bring me more towels.” Savioke’s Relay robots can talk with the elevator to get to the right floor, and their cameras ensure that they don’t bump into walls or humans. About 50% of guests call upon Leo or Cleo during their stays, and in-room dining revenues have increased by 30%. Seeing the robots in action is a novelty worth the price of the late-night dessert menu, and no tipping’s required. With the monthly rental fee of approximately $2,000, a Relay can provide hotel guests with fast, reliable 24/7 service at a lower cost than hiring, training, paying and retaining humans. And they’re quite a sight to see as they roll through the halls on their errands.
Once a species becomes extinct, that’s the end of the story. The Jurassic Park films aside, no one has actually succeeded in cloning a creature that’s disappeared from the face of the earth. But that’s not the case with robotic “animals.” Take Aibo, for example. Sony (SNE) launched Aibo 20 years ago as a dog-like mechanical companion for adults. The Aibo name may stand for “artificial intelligence bot,” but it also means “pal” or “partner” in Japanese. Aibo creations walk, roll their eyes, respond to commands, and utter sounds that blend the mechanical and the organic. The company introduced new models every year, usually sticking to the robot dog theme but occasionally straying into lion or space alien motifs. About 150,000 incarnations of Aibo spread across the planet by the time that the search for profitability dictated the end of production in 2006. Repair service was discontinued in 2014, supplies of replacement parts ran dry and the time had seemingly come to carve Aibo’s name into the granite of a tombstone. Then came the resurrection. Sony resumed production of Aibo last year and promises to provide parts for at least seven years. Perhaps the reintroduction will come to symbolize a resurgence for Sony. Don’t forget that products like the Walkman and Trinitron TVs once made Sony as prestigious as Apple is today. number of new Aibos But what about the sold quickly in Japan cost of the new Aibo? The robotic puppy retails for $2,899.99. That’s not a small price tag but who can calculate the monetary value of love? Welcome back, Aibo!
20,000
JIBO (R.I.P.)
Jibo—a giggly 12-inch robot without limbs or a real face—informed owners of its imminent demise just before its servers shut down in March. The machine that had become a little friend to so many had been in declining health for months as the company wound down its operations and offered less tech support to its products and customers. Many admirers of the diminutive personal robot found its death heart-rending. They’d grown accustomed to the little tyke that snapped family portraits, read books to preschoolers, and yakked interactively about the weather and traffic. For Jibo’s inventor, Cynthia Breazeal, a renowned roboticist and professor at the Massachusetts Institute of Technology, the rise and fall of the automaton must have felt like emotional whiplash. With Jibo, Breazeal had realized a childhood dream and then endured a grownup nightmare. “Ever since I was a little girl, I’ve been fascinated by this idea of personal robots,” Breazeal told a TEDWomen 2010 audience nine years ago. “I loved the idea of a robot that interacted with us, much like a trusted, helpful sidekick.” Jibo got its start in 2014 with $3 million in seed money, and the company eventually burned through $73 million in funding. When the robot became available to consumers in 2017, critics hailed it as a stunning innovation. But the relatively long lead time produced consequences. Chinese knockoffs beat Jibo to market. Meanwhile, Jibo was selling for $899, and Amazon (AMZN) was asking 75% less for the competing Echo. By the end of Jibo’s run, machines with more functions were selling for less than $100.
Jibo bids friends farewell
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GAME THEORY
Better B-Ball Bettors Daily fantasy sports wagering algorithms are nailing the tangibles, but missing some intangibles
J
ames Harden brings the ball past half-court with five seconds left. He dribbles once, twice, moves left and crosses back right to give himself space for a game winning jumper—he lets it fly as the buzzer sounds and drains it! The crowd goes wild, and the Houston Rockets win! The bucket brings the total game score to 250 points, just above the projected over-under, and Harden’s fantasy point total of 55.2 beats his projection of 45. It’s not surprising given the opponent’s high-paced offense and weak overall defense against opposing ball handlers like Harden. Those factors give Harden the perfect landscape to crush not only his projection, but his salary, too. The exhilarating world of daily fantasy sports (DFS) is relatively new compared with the traditional over-under bets that fans have been placing for years. DFS provides online games where participants assemble imaginary teams of real professional players to compete based on statistical performance in actual games. Sites like FanDuel and DraftKings offer daily tournaments that DFS players can enter for a chance to win thousands of dollars for a small $5-$10 entry fee for most large guaranteed prize pool (GPP) tournaments. People don’t see that type of return on capital on a regular basis even in the tournament poker world, and it’s why so many are drawn to DFS. DFS also gives players an emotional tie to the game they’re
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watching, which is part of the reason it’s exploded in popularity recently. DFS also gives players an emotional tie to the game they’re watching, which is part of the reason it’s exploded in popularity recently. DFS also requires that its participants become more knowledgeable. Now, players care about the individual player stats rather than just who wins the game. Online DFS betting is also legal in most parts of the United States—something that can’t be said about online poker. With so much opportunity out there, readers might assume that people are crunching numbers left and right, and they’re correct— plenty of sites that focus on projecting player points have come to light, and plenty of them project very accurately—there’s something to be said about intangible pieces of the puzzle, though, and that’s the topic at hand— how do players use these projections, and are they the be-all-end-all? Basketball tangibles—MPG Basketball’s popular in the DFS community, not only because games are played almost every day during the season but also because the outcomes are very predictable. Data’s abundant in the sport, and it’s spliced on a per-game basis to determine projections like pace, minutes played per player and fantasy points per player. The list goes on and on. With basketball, many DFS players are in the same camp, agreeing that minutes played is a high-tier stat. A fully healthy Harden playing 35 mpg
is different than if he were coming off a fresh injury and was limited to 15 mpg to 20 mpg for the next few outings. The more time a player is in the game, the more opportunities arise for points scored, rebounds, assists, steals and blocks, which are the main categories that contribute to a player’s total fantasy output. Not only is Harden’s fantasy point ceiling much higher when playing more minutes, but his fantasy point floor is higher too—he’s much more of a “safe play” playing a full complement of minutes, compared with a 15- to 20-minute restriction (see “The minutiae,” p. 39). To exceed his salary on a restriction, he’d have to have an insane game with a massive fantasy point-per-minute output.
Stars like Houston Rockets guard James Harden (13) and Stephen Curry (30) of Golden State drive crowds wild in both in reality and in daily fantasy sports.
PHOTOGRAPH: TROY TAORMINA/USA TODAY SPORTS
By Mike Butler
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Basketball tangibles—pace Pace can be huge for individual players and contributes to their fantasy floor and ceiling, similar to MPG. If a team is projected to see a 5% increase in their average possessions per game, that means more opportunity for players to score more fantasy points—simple as that. Typically, games with the highest over-under draw the most attention from DFS players, but players have ways to deviate from the “norm.” For example, if Harden is projected as the highest-owned player on the slate, how can a player take a contrarian stance while still getting exposure to that game? Chris Paul might provide the answer. If Harden has a horrible game or has to leave the game because of foul trouble or injury, Paul is likely first in line to pick up the slack. If Harden is projected to be 60% owned in the tournament, but Chris Paul is projected to be only 10% owned, he makes a fine play to deviate from the norm. In DFS, fading “the chalk,” or the highest projected percentage-owned player can make the difference between winning and losing. Basketball intangibles— hometown advantage When the Westbrook-Durant feud began after Durant left the Oklahoma City Thunder to join the Golden State Warriors, it created such a rivalry that even fair-weather fans were tuning in for Durant versus Westbrook games. We know that analytics are largely historical in nature, and projections are based off historical data but projections seldom account for motivation. DFS Players flocked to both Westbrook and Durant during many of these games, because they believed one, if not both players would exceed their projections and outperform their salary for the day because of heightened motivation. In a similar sense, DFS players may choose hometown games to exploit motivation. In other words, they may select players from teams that are returning to their hometown to play a game. We might assume that plenty of the player’s family and friends
would attend the game, pushing that player to perform. That’s another intangible aspect of the game, but one that many players hang their hat on. In all honestly, who isn’t going to perform their best in front of his mother, father, sibling or high school coach? DFS players always look for an edge, and when analytics falter, external motivation’s the next best bet. In other sports, the same data analytics would apply. With Golf, most data analysis is based on the actual course—does the course play into the hands of golfers with long drives? Soft putts? And for the intangibles…well, where do the golfers live? Is this their hometown practice course in the offseason? Did they play this course frequently during their college years? DFS players can find plenty of intangibles in every sport, as long as they know where to look. Big Data and the little guy With all of the data there is out there and larger numbers of analysts risking thousands of dollars a day on large GPP tournaments, DFS players might start to wonder whether there’s even a point in playing. Just like options trading and poker, it’s crucial to remember one thing— variance is alive and well. In the case of DFS, variance is nothing more than the deviation of results from what is expected. In the probability world, a short-term scope doesn’t tell much, but a long-term scope does. Flip a coin five times and it lands on heads every single time, but the more it’s flipped, the more the results normalize to 50/50. With that said, variance is always high in the short term—especially in a one-day tournament. A DFS player could conduct all the analysis in the world and still come up short that day. Maybe the narrative played a bigger role than the projection for specific players, or maybe a lesser-known player had the game of his career. On April 9, 39-year-old Jamal Crawford of the Phoenix Suns scored 51 points off the bench. Many lineups were busted that day because of this single player. But over the course of the season, Crawford has just been a
Daily fantasy sports sites offer daily tournaments that players can enter for a chance to win thousands for a $5 entry fee
role player averaging 7.9 points per game. This single game represents a massive deviation from what many expected and provides a textbook example of variance seen in GPP DFS tournaments any day of the week. In any case, robotic algorithms and stat projections are booming in the world of DFS GPP, but there will always be space for the little guy to compete and win, largely because of variance. The best algorithm in the world can’t compete with that. Mike Butler, a self-taught trader, serves as host of Mike and his White Board and cohost of Market Measures on the tastytrade network. @tastytradermike
Visualizing variance In the long run, probabilities tend to play out as expected. But with only a few data points, realized probabilities can deviate greatly from expectations.
The minutiae Basketball’s abundant data is spliced on a per-game basis to determine projections like pace, minutes played per player and fantasy points per player. RK
PLAYER
TEAM
GP
MPG
FG%
FT%
1
Bradley Beal, SG
WAS
82
36.9
.475
.808
2
Paul George, SF
OKC
77
36.9
.438
.839
3
James Harden, PG
HOU
78
36.8
.442
.879
4
Russell Westbrook, PG
OKC
73
36.0
.428
.656
5
Jrue Holiday, PG
NOR
67
35.9
.472
.768
6
Damian Lillard, PG
POR
80
35.5
.444
.912
7
LeBron James, SF
LAL
55
35.2
.510
.665
8
Devin Booker, SG
PHO
64
35.0
.467
.866
9
Blake Griffin, PF
DET
75
35.0
.462
.753
10
Kemba Walker, PG
CHA
82
34.9
.434
.844
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ARTS & MEDIA
MIT ARTIFICIAL INTELLIGENCE General-interest journalists love to score interviews with prominent technologists, futurists and other visionaries. But it’s not easy to ask the right questions or understand the answers on the fly. That’s why asking an expert to interview a peer can produce satisfying results. Author and futurist Martin Ford, for example, speaks the same technical language as his subjects in 23 interviews with AI luminaries in his book Architects of Intelligence (see p. 14). Lex Fridman, a Massachusetts Institute of Technology instructor and research scientist, does the same in the MIT Artificial Intelligence podcast. Fridman works on humancentered artificial intelligence, specializing in deep learning approaches to self-driving cars with a human in the loop. His work focuses on building intelligent systems that have real-world applications. Before joining MIT, he worked at Google on machine learning for large-scale behaviorbased authentication. Invoking MIT’s highly regarded name and backing it with Fridman’s expertise attracts stellar interviewees for the 30- to 90-minute podcasts. They include some of the most interesting people in the world, and they think about AI from perspectives that include machine learning, robotics, neuroscience, philosophy, psychology, economics, physics, mathematics and cognitive sciences. Invariably, Fridman’s own command of those subjects somehow helps his guests express their genius in language accessible to the layman, including investors,
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seeking to make sense of the challenges and opportunities that lie ahead for AI, automation and robotics-focused companies. Fridman’s interviews with futurist Ray Kurzweil and Google CEO Eric Schmidt are highly recommended. These two episodes were among the best: Tuomas Sandholm: Poker and Game Theory (December 2018) Tuomas Sandholm, a professor at Carnegie Mellon University and co-creator of Libratus—the first AI system to beat top human players at the game of heads-up no-limit Texas hold’em, shares of his views of technology (see p. 44). Elon Musk: Tesla Autopilot (April 2019) Fridman’s actively researching the real-world problems that arise when autonomous vehicles interact with human drivers and pedestrians. He’s hoping to make autonomous vehicles safer than those with humans at the controls. His session with Elon Musk provided rare insight into the marvelous mind and irrepressible confidence of Tesla’s visionary leader. When Fridman questions the prudence and safety of Tesla initiatives that would allow autonomous driving virtually anywhere, Musk responds: Musk: Frankly, I think it’s pretty crazy letting people drive a two-ton death machine manually. In the future…it’s going to seem like a mad thing that people were driving cars. Fridman: You’re confident with Tesla that you can create the world’s best self-driving (car)? Musk: Yes, the world’s best selfdriving (car). To me right now this seems to be game, set and match. I don’t want to appear to be
complacent or overconfident but that’s just literally how it appears right now. I could be wrong, but it appears to be the case that Tesla is vastly ahead of everyone. Fridman: Do you think that we will ever create an AI system that we can love, and loves us back in a deep, meaningful way like in the movie Her? Musk: I think AI will be capable of convincing you to fall in love with it, very well. From a physics standpoint, if it loves you in a way that you can’t tell whether it’s real or not, it is real. Fridman’s closing question in the interview is followed by an uncomfortably long pause. Musk finally breaks the silence with a stunning four-word reply that reveals the workings of his extraordinary mind. Fridman’s command of deep-learning has helped him probe his subject’s psyche and resulted in an essential podcast for AI theme investors. —Jeff Joseph
MIT’s Lex Fridman
MIT ARTIFICIAL INTELLIGENCE
5 out of 5 informed, big-picture perspectives from prominent AI leaders
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MY DEAD WIFE, THE ROBOT CAR In 1964, My Mother the Car, an NBC sitcom, aired one season for 30 episodes. The set-up was a man’s deceased mother communicating with him through his car’s radio. Critics hated the show and held onto their disdain for decades. In 2002, TV Guide proclaimed it the second-worst TV show of all time, behind The Jerry Springer Show. Yes, it was unwatchable. More than half a century later, the talking car sitcom has been resurrected as My Dead Wife, the Robot Car. It’s unwatchable— because it is a podcast on Stitcher. But this time around, it’s a brilliantly executed, and often side-
splitting, improvised 10-episode comedy series. It took Matt Besser, a selfproclaimed “sci-fi geek,” to crack the comedy code for talking cars. In the first episode, Besser, one of the founding members of the Upright Citizens Brigade sketch comedy troupe, introduces us to the lead character, Matt, a recent widower. When Matt shows up to become one of the first test-drivers for a high-tech autonomous car company, he finds that the AI personality of the operating system is his dead ex-wife Joyce, played by Mary Holland. Joyce’s voice and equally abrasive personality were rebuilt
from the data of her prolific video blogging on social media. It’s not a fond reunion for Matt, who was planning to divorce Joyce when she died in a drunk-driving accident. Matt needs the money from the car-testing gig and decides to put up with Joyce’s relentless criticism and alpha-AI control of the vehicle. Besser recently explained the inspiration for his series to The Verge, a media and technology network. “I thought it would be funny to do a version of (the Spike Jones 2013 film) Her, where instead of being in love, you’re forced to be with an unpleasant artificial intelligence,” he said. Besser’s right—it’s very funny. —Jeff Joseph
MY DEAD WIFE, THE ROBOT CAR
4.5 out of 5 satirical, NSFW comedy about AI in a Curb Your Enthusiasm-meetsBlack Mirror vein
LOVE DEATH + ROBOTS Some of the 18 short animated films in a new Netflix series called Love Death + Robots end with unexpected twists—like latter-day episodes of the venerable Twilight Zone shows. But the new adult-oriented anthology beats the old one for weirdness. Part of the enhanced bizarreness on LDR probably accrues from Hollywood’s additional decades of working to perfect the ways it wields shock, horror and suspense. It’s been a long time since the original Twilight Zone episodes ran on broadcast TV from 1959 to 1964 . LDR also increases the strangeness quotient by capitalizing on the current era’s relatively
relaxed attitudes toward the profane, erotic, grisly and gory. All of those characteristics abound in the new series, with sensual sex scenes, copious amounts of flesh ripped from the bodies of humans and beasts, and matterof-fact blurring of the line between humanity and machinery. Relying on beautiful—if sometimes frightening—animated graphics instead of the Twilight Zone’s black-and-white live-action studio productions, LDR images range from hulking, viscous, vaguely reptilian and just plain ugly “beastie” warriors—to cute, chattering humanoid automatons. Meanwhile, LDR brings its increased weirdness to a far wider
zone than the Twilight Zone ever did. Animation unleashes creativity, enabling illustrators to fill the worlds they envision with urban canyons of underpopulated skyscrapers, or domed farms operated by robot-dependent family farmers. Blending the dramatic, comedic, sci-fi and horror genres, lends LDR ample variety from the start. And using animation crews from different countries further differentiates the episodes. Believe it or not, investors seeking a handle on a robotic future just might gain some insight from watching what LDR has to offer. And it’s entertaining, too. —Ed McKinley
LOVE, DEATH AND ROBOTS
4 out of 5 short animations brimming with stunning visuals and rampant creativity
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ARTS & MEDIA
Celluloid Android From cyborgs to replicants, robotics has inspired some great cinema
Futuristic Cyborg Assassin 100%
2. Forbidden Planet (1956) Robby the Robot Debuts 98%
3. The Iron Giant (1999)
6. Terminator 2: Judgment Day (1991) Robot Learns Human Values 93% Ex Machina
7. 2001: A Space Odyssey (1968) Super Computer Turns Traitor 93%
Giant Metal Friend 96%
8. Ex Machina (2015)
4. Wall-E (2008)
AI Girl Shows No Mercy 92%
Robot in the Wasteland 95%
5. The Day the Earth Stood Still (1951) Alien Robot Named Gort 94%
9. Blade Runner (1982)
AI Exploits Humans 88%
13. Colossus: The Forbidden Project (1970) Computerized Global Destruction 88%
Who’s Really the Robot? 90%
14. Blade Runner 2049 (2017)
10. Big Hero 6 (2014)
Bounty-Hunting Robots Return 87%
Robotics Prodigy 89%
11. RoboCop (1987) The Day the Earth Stood Still
12. The Matrix (1999)
Crime-fighting Cyborg 89%
15. Robot and Frank (2012) Humanoid Robot Caretaker 86%
Rotten Tomatoes Tomatometer: A fresh red tomato denotes a good review (>60%). Each of the scores on this list was derived from the opinions of a minimum of 30 Tomatometer-approved critics.
The Terminator
They’re all back
Thirty-five years after the original Terminator debuted in October 1984, the bots are still alive and ticking in the latest installment of the Terminator franchise, Terminator: Dark Fate. James Cameron, Arnold Schwarzenegger and Linda Hamilton all return this fall to the latest chapter of the Terminator story, which Cameron, who will serve as producer and creative consultant, is calling a direct sequel to Terminator 2: Judgment Day. This is also the first time Cameron returns to Terminator since 1999’s T2, and he says the new installment is intended to kick off a trilogy of its own. This installment also brings the long-awaited return of Linda Hamilton as Sarah Connor—and it’s the first time Hamilton is working with her ex-husband Cameron since the second Terminator movie. Tim Miller will direct. He directed Deadpool, which broke R-rated box office records in 2016. Estimated release date: Nov. 1.
HONORABLE MENTION PI (1998) The movie follows a mathematical savant who thinks numbers explain everything. He lives in a crappy, ant-infested apartment with a rickety computer he calls Euclid, which he uses to try to game the stock market. Instead, it spits out a 216-digit number, which Max disregards. Then folks ranging from Hasidic Jews to Wall Street agents descend on him. They all want what he knows; but he doesn’t even know what he knows. 88% “A workout, no question, and not for everyone, but it has intellectual and spiritual fervor.” — Rob Gonsalves, eFilmCritic
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PHOTOGRAPHS: PHOTOFEST ARCHIVE
1. The Terminator (1984)
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FINANCIAL FITNESS
Options & Outcomes A probabilistic approach—to physique sports and the markets— requires precision, accuracy and meticulous behavior By Dr. Jim Schultz
PHOTOGRAPH: DOYLE LACRUA
N
ine Inch Nails nailed it with respect to competitive bodybuilding, where the excitement and exhilaration of show day is preceded by weeks, months, possibly years of boring and repetitive days— every day really is exactly the same. Physique sports are unique in that 100% of an athlete’s score or placing is determined by his or her body. It’s balance. It’s symmetry. It’s overall aesthetics. Now, judges in different divisions might look for different qualities. Whereas the male bodybuilding division places a heavy emphasis on the balance between muscularity and conditioning, the male physique division (it’s not only the generic descriptor for these sports, but its own division) isn’t looking for a lat spread that blocks out the sun or a front-double bicep that resembles a small mountain range. Instead, these athletes need to be lean, but not overly “swole,” a word that means very muscular. Similarly, female figure athletes typically need a “harder” look to do well on stage, while bikini competitors always do better if they’re still a little soft. Still, the common denominator is that everyone needs to bring the shredz. Lots and lots of shredz. And the only way to do any of that? Precision. Accuracy. A meticulous approach to training that lies somewhere between highly conscientious and borderline neurotic. Meals prepped to the gram, and training sessions dialed down to the minute. People should look at you
and wonder if your blood has been replaced with batteries. No serious competitive physique athletes just show up and hope for the best. Things get serious, and body compositions need to come in looking crispy (which to bodybuilders means looking super hard and super defined). Now, take the phrase, “physique athlete,” replace it with “active trader,” and reread everything before this line. Actually, wait. Don’t do that. The probabilities all but guarantee that at least a few traders out there are looking to bring the crispiest frame they can to their trading terminals. But in all likelihood, they’re the exceptions to the general rule. Nevertheless, active traders using a probabilistic approach to the markets share the same spirit of precision, accuracy and meticulous behavior that physique athletes possess. The only way to ensure that the probabilities play out as expected is to keep feeding consistent data points into the models. Trades should be studied for consistency, and strategies should be screened for cohesiveness. Investors should establish a governing method of uniformity and apply a stable set of mechanics every day if they expect a year-end result or a quarterly P/L that’s the equivalent of a physique competitor’s win on show day. One unique characteristic of the world of options that no other asset class can match is its relationship with probability. The variables of the Black-Scholes Option Pricing
Model, coupled with an introductory understanding of basic statistics, allow investors to know the probability of success on any options position ahead of time, before ever submitting the order. Probability is only one piece to the four-dimensional puzzle of option trading, but it’s an important piece. And when it comes to the puzzle as a whole, consistency afterthe-fact depends on consistency before-the-fact. Otherwise, there’s only one outcome — haphazard inputs leading to haphazard outputs. To succeed, embrace the monotony of routine and welcome the mundane nature of predictability. Why else would physique sports athletes eat chicken and broccolli daily? Chicken breasts aren’t the most flavorful option and broccoli stalks don’t normally get the salivary glands popping. Still, they’re both staples on competitive kitchen tables everywhere. Why? It’s simple—winning Whether it’s winning on the competitive stage or winning on the trading screen, the likelihood that a favorable output correlates directly with the dependability and reliability of input. Think of the robotic arm on an assembly line that tirelessly performs the same task 24-7. Now is not the time for spontaneity.
Jim Schultz, Ph.D., is a derivatives trader, fitness expert, owner of livefcubed.com and the daily host of From Theory to Practice, on the tastytrade network. Jim was named a North American Natural Bodybuilding Federation’s 2017 Novice Bodybuilding Champion. @jschultzf3
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THE POKER TRADE
Play Poker Like a Machine
Game theory has helped AI conquer poker, and now humans can use it to beat their rivals. By Jonathan Little
C
omputers aren’t limited to playing simple games like tic-tactoe, checkers and chess. With enough computing power and time, machines can use math and game theory to comprehend the most difficult games—even poker. A game is considered solved when a computer has determined the Game Theory Optimal (GTO) strategy. The GTO strategy either breaks even (when the opponent plays the same strategy) or wins (when the opponent plays any other strategy). Computers solved simple poker games like limit hold’em a few years ago, and they’re close to solving no-limit hold’em. In 2017, Libratus, a bot developed at Carnegie Mellon University, crushed four of the best heads-up, no-limit hold’em players for more than 14 big blinds per 100 hands. (See “BUT CAN LIBRATUS DO THE THUMB FLIP?” p. 45.) With $1/$2 blinds, that would be $28 per 100 hands, which is an incredibly high win rate. Learning to bluff Some players may not understand how a bot could possibly know how and when to bluff intelligently, but it turns out bluffing’s a common tactic discussed in game theory classes. For example, quite often players find themselves on the river with a polarized range, which consists of premium hands and
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junky hands, while an opponent has a condensed range, consisting of medium-strength hands that lose to premium hands and beat junk. In that situation, the polarized player can win the pot on average simply by betting an amount that results in opponents winning a portion of the time equal to their pot odds. So, if a player’s range consists of 67% premium hands and 33% bluffs (using in-depth range analysis taught at pokercoaching.com), bet an amount that requires an opponent to win 33% of the time. In that case, a pot-sized bet gives opponents 2:1 pot odds, meaning they need to win 33% of the time to break-even. With a polarized range, a pot-sized bet will win the pot on average, no matter what an opponent does. With a range of 83% premium hands and 17% bluffs, betting one-fourth of the size of the pot—giving an opponent 5:1 pot odds—wins the pot on average. As players have more bluffs in their ranges, they can use a larger bet sizing. If the range is perfectly polarized with 51% premium made hands and 49% bluffs, a player could actually bet 24.5 times the size of the pot, which almost no one does. If players study using the two main GTO solvers available today (PioSolver and MonkerSolver) they’ll find patterns that come up all the time. For example, when determining which hands to continually bet on the flop against an oppo-
How could a bot possibly know how and when to bluff intelligently?
nent, the main concern is how the range fares against an opponent’s range. If players have the equity advantage (meaning their equity with their entire range on the flop is higher than an opponent’s equity with an entire range), bet with a large portion of the range using a small bet. Without the equity advantage, bet infrequently using a large size with a polarized range consisting of premium made hands and some draws, while checking marginal made hands and junk, plus a few traps. Using this knowledge, develop an implementable system taught at pokercoaching. com to determine roughly the ideal betting and checking strategy in any situation. While the GTO strategy is powerful, it’s usually the ideal strategy against only the best players in the world. As opponents play worse, adjust to take advantage of whatever they do incorrectly. Playing strictly on the GTO strategy would leave a ton of money on the table. Passive exploitation happens when a player simply plays GTO and whatever an opponent does wrong wins money, while active exploitation is deviating from the GTO strategy to take further advantage of an opponent’s mistakes. The maximally exploitative strategy occurs when a player deviates from the GTO strategy in a way that maximizes profit from an opponent.
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Detecting opponents’ errors While it’s sometimes difficult to know what a specific opponent does incorrectly, many times it’s obvious. For example, many small-stakes players simply never bluff on the river. So, if a player gets to the river and an opponent with that tendency bets, fold all but the best-made hands. Other players bluff far too much, allowing a player to easily call down with all sorts of marginal made hands. Those are both examples of actively exploiting your opponent. The major problem with using the maximally exploitative strategy is that an assessment of an opponent’s strategy could simply be wrong. If a player thinks an opponent never bluffs yet that opponent actually bluffs a lot, or if the player folds to most bets, then the player will get demolished. If a player thinks an opponent bluffs a lot, and thus calls
down with lots of marginal made hands, but it turns out the opponent essentially never bluffs, a player will also get demolished. If an opponent quickly and correctly counter-adjusts to combat a maximally exploitative strategy, a player will lose much more than could have potentially been won by making the initial adjustment. Playing the GTO strategy sidesteps this dilemma, but will win less money in the long run, assuming your assessments are generally correct. So, until you are fairly certain about what your specific opponent does incorrectly against you, it is wise to play a fundamentally sound strategy. Jonathan Little, a professional poker player and WPT Player of the Year, has amassed more than $7 million in live tournament winnings, written 14 best-selling books and teaches at PokerCoaching.com. @jonathanlittle
BUT CAN LIBRATUS DO THE THUMB FLIP? Libratus, a poker bot created by Noam Brown and others at Carnegie Mellon University, beat four human professional players in 120,000 hands of heads-up, no-limit hold’em, in early 2017. Four distinguished professional poker players each played 30,000 hands. Each was summarily beaten by Libratus. To reduce the luck factor, special rules ensured no party could just run hot over the course of the challenge. After 20 days, Libratus convincingly beat each pro at a win rate of 14.7 big blinds per 100 hands. Despite the roughly 316,000,000,000,000,000 possible game situations, John Nash, the winner of the 1950 Nobel Prize in Economics, would deem headsup, no-limit hold’em a game with a finite number of situations. Consequently, a Nash Equilibrium exists, which ensures that players using a Nash equilibrium strategy cannot lose against any other player in the long run. A human poker player could never accurately recall, compute or apply the Nash equilibrium strategy to quadrillions of scenarios — but Libratus could. Nash equilibrium means that guts, bluffs, tells, reads and other differentiating strategies employed by the top pros, really don’t matter in the end. That has implications for the online poker industry, which posted more than $1 billion in revenue last year. The poker sites have the challenge of ensuring that no online player is using AI, while convincing players of a level playing field. For a deeper discussion of AI achievements at poker, listen to MIT’s Artificial Intelligence 12.28.18 episode podcast, which includes an interview of a Libratus co-creator, “Tuomas Sabdholm: Poker and Game Theory”. (See podcast review in Arts & Media on p. 40.)
Learn the poker chip thumb flip trick
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TRADER
TONY BATTISTA Birthplace Brooklyn, NY
1 Clock from India 2 Battista’s personal trading account & BOB’s IRA account (BOB The Trader is an app that lets you follow trading guru Tom Sosnoff as he trades every day during market hours)
Age 56 Residence Glenview, IL 1
Years trading 26 years (22 at the Chicago Board Options Exchange)
Favorite options trading strategy Everything we do is based on a math model around probability of success, and, on entry, the stock must have a high IV rank. A “strangle”—the simultaneous sale of a call and put—has the highest probability of success and benefits the fastest from contracting IV rank. Your best trading day ever The day of the crash Monday Oct. 19, 1987. The crash was the week of options expiration so my existing positions were already buttoned up, allowing me to react and not think about what was going on. In other words, I was able to just trade! What percentage of your outcomes do you attribute to luck? 30%
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8
3 Bulgari watch 4 Tony’s favorite book 5 Controls monitor
7
6 iPhone 7 3
6
5 4
Tony Battista trades options every day live on the tastytrade network
7 Monitor displays what’s live on tastytrade 8 Sossnoff’s live trading account
“THE BAT” TAKES PITCHES FROM LUCKBOX READERS I like to buy beaten-up stocks, but the IV is always so low that selling puts and covered calls isn’t worth it. Suggestions? —Jason Ruble, Dallas Vertical debit spreads are the answer! Buy a call two or three strikes in-themoney and sell a call two or three strikes out-of-the-money. You use significantly less buying power than a covered call or naked put and pay no extrinsic value to the stock. It benefits from an up move in the underlyings. I hear Tom Sosnoff or Tony Battista say on the tastytrade program that a stock has an expected move of X just by looking at the Delta or some other factor. How is this done? A caller called in about an account that was going sideways. Tom then told the caller what the delta was of the positions he was holding. The
caller said, “Oh, well, you are losing money,” and Tom agreed. How was this known from this conversation? —Paul Bursey, Lewis Center, OH We are looking at implied volatility. Implied volatility is the market’s view of what will happen to a given security’s price in the future. It is a metric used by investors to estimate future fluctuations (volatility) of a security’s price based on certain predictive factors. Implied volatility can often be thought to be a proxy of market risk. It is commonly expressed using percentages. An expected move is the amount that a stock’s range is predicted to move from its current price, based on the current level of implied volatility. Delta equals odds that an option will be in-themoney at expiration. A 30 delta equals a 30% chance that an option will be in-the-money at expiration. —@Tony_BATtista
How I learned to Trade like Tom Sosnoff and Tony Battista: Book One, Trade Mechanics By Tony Rihan Volume 1, 2013 $41.94 (Amazon) Paperback (220 pages)
Tony Battista: from floor trader to tastytrader
PHOTOGRAPH: GARRETT ROODBERGEN
Average number of trades per day Typically 10 today, more than 500 a day from 1983-2005
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CALENDAR
TRADING WITH THE STARS Sun’s peak at the summer solstice could mark changing market trends. By Susan Abbot Gidel
PHOTOGRAPHS: (FIREFLY) COURTESY OF FIREFLY MUSIC FESTIVAL; (ALL OTHERS) SHUTTERSTOCK
T
o legendary trader and financial astrology pioneer W.D. Gann, the change of seasons often heralded changes in market trends. Most recently, note that the S&P 500 peaked on the fall equinox in 2018, bottomed just after the winter solstice last year and made a short-term high at the spring equinox in March of this year. Will the summer solstice follow suit? Some signs are indicating the end of the economic expansion could come this month. Also note that the crude oil market could be in for a change in trend, too, because its astrological ruler, Neptune, turns retrograde on the summer solstice. In 2014, the crude oil market topped at $107 per barrel the week Neptune retrograded, falling $34 by the time the planet turned direct in motion in early November. In 2017, crude oil bottomed near Neptune’s retrograde start and the summer solstice at $42. It rallied $17 by the time the planet turned direct in November. Here are some actionable astro dates to watch for potential market turning points in June, based on how the planets are lining up with each market’s first-trade horoscope. See how they align with other favorite technical indicators:
J U NE 5–6 Robotics Summit and Expo Boston 15–16 Moneyshow* Seattle 21 Summer Solstice Change of trend 21–22 AI Blockchain Summit Washington D.C.
21–23 Firefly Music Festival Dover, DE 26–30 Glastonbury Music Festival United Kingdom
J U LY
June 3: High in soybeans as the New Moon and Jupiter are
activating the very sensitive first-trade Moon from opposite directions.
June 10: High in 10-year T-notes as both significant axes in
the first-trade horoscope chart are activated by the transiting Moon and Venus.
June 11: High in gold as Mars triggers the first-trade
horoscope Mercury while transiting Mercury and Moon trigger the first-trade Sun. June 13: Low in euro FX as Mercury and Mars make a
tension-filled, 90-degree square to the position of Venus in the first-trade horoscope.
June 19: Low in gold as Mars moves on to trigger the first-trade horoscope Venus, joined by transiting Mercury, Moon and Pluto. Susan Abbott Gidel, author of Trading In Sync With Commodities—Introducing Astrology To Your Financial Toolbox, also edits Red Letter Trading Days, a monthly newsletter.
10–14 Taste of Chicago Chicago 13 Geeks on Parade* Chicago 21–23 Traders Expo* Chicago 22–8/16 NYC Restaurant Week New York City 26–28 Festival of Ballooning Readington, NJ *For more information visit tastytrade (events)
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LIGHT THIS CANDLE
Candlestick chart analysis for intermediate-term trading
MCHP: Option This Breakout By Doug Busch
M
icroChip Technology Inc. (MCHP) is offering a best in breed semi growth play with a dividend yield of 1.5%. The company’s backto-back positive earnings gains have pushed volatility higher than most traded stocks. Taut action of high volatility stocks often leads to explosive moves higher. Enter with buy stop above bull flag trigger of $100.25. The breakout suggests a measured move to $120. Or, for a higherprobability options trade, consider a butterfly—this has a low cost and a high payout. For example, with the stock at 99, consider selling two of the 105 puts and buying one 100 put, and one 110 put. The maximum potential is the price paid minus the width of the spread. So, for example, with a price of $65, the risk is $65 to make a profit of $435 ($500 - $65 = $435). Douglas Busch, CMT, trades U.S. equities using technical analysis with an emphasis on Japanese candlesticks. @chartsmarter
MicroChip Technology Inc. (MCHP)
CNK BUY $100.25 STOP $95
Source: ChartSmarter
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THE TECHNICIAN
A veteran trader tackles technicals
Trading Robotics Like a Robot By Tim Knight
I
ntuitive Surgical (ISRG), one of the world’s best-known and most heavily traded robotics stocks, has climbed in value from as little as $2 to more than $500 per share in the nearly two decades it’s been a public company. For “buy and hold” investors, this stock has worked out well. However, it makes an interesting trading vehicle, too, so it’s instructive to explore opportunities that have arisen because of its upswings and downturns. After all, it didn’t make the move from $2 to $500 in a straight line. A couple of good basic choices for entry and exit signals include the Williams %R and the exponential moving average (EMA). In the spirit of robotics, investors can test these trading signals mechanically and use automated processing of past data to help find good figures to use as the parameters. When using these indicators, investors can use well-established, popular parameters, such as a 50-day moving average or 14-day %R. Nearly everyone else uses those values, but why not study the stock’s history to tease out which ones worked? Let’s start with the Williams %R and use past data to test hypothetical trades for all possible parameters. The basis of the hypothetical trades is that the investor would buy Intuitive Surgical if the Williams %R crosses above the -75 line based on “N” days, and that position would be sold when it crosses back below the -25 line. Instead of simply guessing what value to use for “N,” the computer surveys the historical database and offers its own recommendation of 200 days.
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Minimizing guesswork Rather than guess for “N,” the computer surveys the historical database and offers its own recommendation of 200 days, with mostly gratifying results.
Based on analysis of past price data, the most profitable value to use for the symbol ISRG is 199 for long positions. The slider is moved to 200. The values are based on available information, and no assurance is offered as to their accuracy or profitability.
WILLIAMS %R An oscillator measures overbought (top of chart) or oversold (bottom) conditions, with a signal at crossing the dashed midline that indicates the overbought or oversold condition is probably complete and momentum has shifted the other way.
Stellar Results Using the Williams %R based on historical performance, most of the resulting trades were impressively profitable.
Using that value of 200, one can find what the results would have been if this rule were followed through the entire history of the stock. The results are impressive: 83% of the trades were winners, and the percentage gains were much larger than the losses. Overall, each trade produced a 25% return. It’s also interesting to know the quantity of trades was quite modest and
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reasonable: just a dozen over the entire test period. As good as those results are, it makes sense to try a similar experiment, this time with the exponential moving average indicator. In this instance, the computer assumes it would have purchased Intuitive Surgical when the closing price crosses above the “N”-day EMA and would have sold the position when crossing below the same EMA. Having analyzed all the past data, it recommends a 199-day EMA. The trading results, however, are dismal. First, the quantity of trades is much greater: 101. And even though the percentage gains from the winning trades was impressive, the number of losing trades dwarfed the winners, dragging the overall average result to 6.64%, about one-quarter as good as our %R idea. Investors can apply this mechanical and “robotic” approach to trading any financial instrument, whether it is involved with robots (as Intuitive Surgical is) or not. What makes Intuitive Surgical interesting is the strength and regularity of its up-and-down moves. With just a small amount of testing, by way of the two aforementioned indicators, investors can hone in on a simple and potentially profitable trading system, whose historical results are portrayed in this chart (with green marking the winning trades and red marking the couple of lonely losers).
Below average
So much for so little
Computer testing indicated a 199-day exponential moving average that produced lackluster results.
The exponential moving average indicator recommended 101 trades, most of them losers that dragged down the average from the single highly profitable trade.
Based on analysis of past price data, the most profitable value to use for the symbol ISRG is 199 for long positions. The slider is moved to 200. The values are based on available information, and no assurance is offered as to their accuracy or profitability.
Testing produces winners Using just two indicators, investors can create a potentially profitable trading system. In the Intuitive Surgical example, green marks winning trades and red indicates losers.
Tim Knight has been using technical analysis to trade the markets for 30 years. He founded Prophet Financial Systems and offers free access to his charting platform at slopecharts.com.
Using the (Williams %R) value of 200 brought impressive results: 83% of the trades were winners june 2019 | luckbox
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MACRO TRADER
Opportunistic global market directional trends
An Aussie Currency Trade By Amelia Bourdeau
T
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One in a series On Oct. 7, 2016, the British pound fell 9% relative to the U.S. dollar in early Asian trading but soon recovered. The Bank of International Settlements viewed it as part of a pattern. OTC FX TURNOVER, NET-NET BASIS, DAILY AVERAGES 6,000
Total all instruments Spot FX
5,000
4,000 BILLIONS USD
he Bank of International Settlements (BIS) operates as a bank for central banks, offering financial services to help central banks manage foreign reserves. It’s also known for its Triennial Survey of Foreign Exchange and OTC Derivatives Trading. That survey tracks foreign exchange turnover—total and by currency. The BIS released the latest full survey in 2016 and showed that daily foreign exchange (FX) turnover was U.S. $5.07 trillion (See “One in a series,” right). In September 2018, the BIS released the report called Monitoring of Fast-Paced Electronic Markets. It defined fast-paced electronic markets (FPM) as “markets where the price discovery process predominantly occurs via electronic means and which are characterized by a sizeable penetration of high-speed, algorithmically driven order placements.” Spot FX in the major currencies is one such market. In its September 2018 FPM report, the BIS found that for spot FX, the “share of trading volume executed electronically has almost doubled over the last decade.” Also, “Survey data suggest that, since 2013, more than 70% of spot trading is executed electronically, while an estimated 70% of orders on EBS, a primary central limit order book and a major interdealer platform for spot FX, are now submitted by algorithms, rather than manually.” The BIS also found that the nature of market participation has changed. Liquidity is still concentrated among the large banks, and other banks have found it hard to compete and have exited or scaled back their activity. In addition, a new set of non-bank intermediaries—proprietary trading firms—have become more important in the industry. That’s reflected in the 2018 Euromoney FX Survey, which ranks the top FX liquidity providers by market share. The three biggest providers that year with respective market shares were JP Morgan with 12.13%, UBS, 8.25%, and XTX Markets, 7.36%. Non-bank XTX Markets had
3,000
2,000
1,000
0
2016
2013
2010
2007
2004
2001 Source: Bloomberg LLC
increased its standing to third, up from 12th the previous year—which is a big move. As a result of the changing market structure, end-users have more access to a wider choice of trading venues. Advances in technology and increased competition for flow have resulted in more competitive pricing—in other words, narrowed bid-ask spreads in FX. End-users also have demanded reduced market impact when putting trades through. That has led, according to the BIS, to “new types of venue, including electronic single and multi-bank platforms and other venues designed to allow end-users to compare and/or aggregate quotes from a number of dealers.”
The share of trading volume executed electronically has almost doubled during the last decade
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While the rise of electronic trading has brought benefits, some of the challenges associated with it center around monitoring, harnessing and understanding the increased data flow. The BIS found that, “the frequency of activity and speed of information flows in FX markets has increased drastically.” That affects end-users, banks, non-banks and central banks alike. It has become more difficult to understand, at times, the factors moving the FX market or certain currencies. The BIS report notes that “Algorithmic execution designed to minimize market signature (e.g., by decomposing orders into multiple smaller blocks) can mask trading patterns and volume while prime brokerage on electronic communication networks masks the identity of the economic counterparty to the trade. Traditional market contacts (such as voice dealers) may have less visibility over flows that are driving short-term price formation.” It’s not unusual for clients to call a major bank’s FX trading desk and ask what’s happening with a sudden price movement. At times, it’s difficult to know the answer to that question, and that will likely remain the case. Occasionally, mini “flash-crashes” can occur between trading sessions, when liquidity tends to be thinner. For central banks, monitoring sudden FX movements is important for financial stability mandates. One instance that highlights that importance is the Oct. 7, 2016, flash crash of Sterling (Great Britain pound—U.S. dollar, PUSD, see Triennial Reports, above). Sterling fell around 9% versus the USD in early Asia market trading, before quickly retracing most of the move. The BIS investigated that flash crash and in its January 2017 report said: “This event does not represent a new phenomenon but rather a new data point in what appears to be a series of flash events occurring in a broader range of fast, electronic markets than was previously the case in the post-crisis era, including those markets whose size and liquidity used to provide some protection against such events.”
Triennial Reports Research by The Bank of International Settlements tracks daily foreign exchange and is shown here in U.S. dollars.
Source: BIS
The Trade Turning from the e-trading market structure to the current landscape of G10 FX markets, Australia’s firstquarter Consumer Price Index came in weaker than expected. That has brought a possible 25 basis point rate cut by the Royal Bank of Australia (RBA) onto the radar screen. Debate on the timing of an RBA policy rate cut and whether Australia’s employment will remain strong, should weigh on AUD vs. USD. Short AUD/USD by buying a three-month 0.6500 AUD/USD put.
FX liquidity is still concentrated among the large banks
Amelia Bourdeau is CEO at marketcompassllc.com, an advisory firm that provides global macro education and trading strategy to investors at every level. @ameliabourdeau
Big 3 FX liquidity providers by market share: JP Morgan, 12.13%
UBS, 8.25%
XTX Markets, 7.36%. june 2019 | luckbox
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DO DILIGENCE
Financial technology helps proactive investors understand their portfolios
Robo-Advisors: Not ‘On Track’ By James Blakeway
T
raditional exchanges closed their open outcry pits as markets moved to laptops and smartphones, giving virtually everyone in the country access to the stock and derivative markets from the comfort of home or on the go. While many have welcomed their new-found investment freedom, some remain reluctant to take the plunge, blaming lack of time and a dearth of knowledge. The latter still turn to financial advisors for investing decisions on all or part of their wealth. Some want the advice of an “expert” but don’t want to leave home or even talk to anyone. The robo-advisor, the newest disruptor of the financial advice industry, dispenses lower-cost investment advice based on algorithms instead of human interaction. The algorithms use the investor’s income, financial standing, age and retirement goals to determine investment allocations. Betterment, a company launched in 2010, occupies a position near the forefront of the robo-advisory wave, managing more than $14 billion for its customers. It offers low costs and minimal barriers to entry with and a 0.25% annual management fee. A Betterment account provides customers with access to their asset management program, weighting a diverse portfolio of stocks and bonds through the use of exchange-traded
Automatic pilot Here’s a look at Betterment’s 90/10 General Investing portfolio allocation.
Stocks 90%
Bonds 10%
Asset Class
ETF Ticker
% Allocated
U.S. Total Stock Market
VTI
31.8%
International Developed
VEA
23.0%
Emerging Market
VWO
14.0%
U.S. Large-Cap Value
VTV
8.5%
U.S. Mid-Cap Value
VOE
6.9%
U.S. Small-Cap Value
VBR
5.8%
U.S. Municipal
MUB
3.8%
International Developed
BNDX
2.9%
Emerging Market
EMB
1.5%
U.S. High Quality
AGG
1.1%
Inflation Protected
VTIP
0.7%
funds (ETF). It’s all algorithmic, with no contact with a registered advisor. However, for a slightly higher annual fee of 0.40%, customers can “upgrade” their accounts to include actual human contact with a Betterment advisor — providing they have $100,000 at the firm. On Betterment’s frontend website, a planned portfolio for anyone under the age of 50 (regardless of income) includes 90% stocks and 10% bonds. A deeper dive shows the full spectrum of the portfolio composition (see “Automatic pilot,” above). Betterment relies on ETFs, which typically have lower net expense
ratios than managed mutual funds. A portfolio with Betterment’s weightings, initiated at the beginning of 2018, lost 9.1%. For comparison, the S&P 500 ETF (SPY) lost 6.4% in 2018. A portfolio split 90/10 between SPY and the iShares 20+ Year Treasury Bond ETF (TLT) lost 5.9%. (Continued on p. 56)
tastytrade’s Tom Sosnoff rips on robo-advisors
The robo-advisor, the newest disruptor of the financial advice industry, dispenses lower-cost investment advice based on algorithms instead of human interaction
Past performance is no guarantee of future results. Information provided in an EPI Report does not consider the specific profile, objectives or circumstances of any particular investor or suggest any specific course of action. Investment decisions should be made based on an investor’s objectives and circumstances and in consultation with his or her investment professional. Investment suitability must be independently determined for each individual investor. QF does not make suitability determinations or investment recommendations for investors. EPI utilizes the S&P 500 as its benchmark given that the S&P 500 is considered a barometer of stock performance in the United States. Aspects of the analysis and information found in an EPI Report is based upon simulated and/or hypothetical performance. Simulated and hypothetical performance have inherent limitations and do not represent the actual performance results of any particular investment products. The EPI Report does not guarantee any results or outcomes in the financial markets. Investors should be aware of the methodology used to produce an EPI Report and the inherent limitations when placing reliance on the results. For additional information about EPI Reports, visit the QF website: quietfoundation.com. Betterment portfolio info. at betterment.com.
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FUTURES
A savvy futures trader’s take on the markets
Oil and the Dollar By Pete Mulmat
C
rude oil and the U.S. dollar have a marriage made in a therapist’s office. Sometimes there’s frustration, sometimes there’s tension—but they are forever tied to each other. As if to celebrate this union, crude oil and the dollar are doing something they’ve only done 11 times in the past 35 years. They’re moving in the same direction. Traders often ask if the value of the dollar relative to other key global currencies works as a major factor in driving oil prices. Well, when filling up a car’s gas tank, Americans pay with dollars, not with euros or Japanese yen. So, why would a relationship exist between currencies and crude? Typically, the price of oil is inversely related to the price of the U.S. dollar. What’s more, barrels of oil are priced in U.S. dollars across the world. The easiest way to think about this is from a non-U.S. oil producer’s point of view. In Saudi Arabia, for example, an oil producer needs riyals to spend but has to sell oil in dollars. When the dollar’s strong, he can sell oil at a lower price and convert fewer but stronger dollars into riyals. When the dollar’s weak, he needs to sell oil at a higher price to convert a larger quantity of weaker
/CL
Crude and the euro When the dollar rises, the euro falls, and vice versa.
dollars into the riyals. Because all currencies are interrelated, this activity trickles through to other currencies—like the yen and euro, for example. This works for oil buyers, too. Because crude is a global commodity priced in U.S. dollars, it’s logical to think that when the value of the dollar declines, buyers would need more dollars to purchase the same 42-gallon barrel
of oil. In other words, the dollar and crude oil should be inversely correlated, moving in opposite directions. But now, that relationship is flipped on its head. Oil prices and the U.S. dollar are rallying in tandem—a correlated movement that has occurred only 11 times since 1983. Crude (/CL) was up 12% in March 2019 (see “Crude and the euro,” above), (Continued on p. 56)
Crude and U.S. dollar correlation Historically, crude oil has had a -0.25 correlation to the dollar, or about a +0.25 correlation to the euro (left chart). With a looser correlation of just -0.25, however, the market goes through these periods of divergence, but always seems to revert back to normality (right chart).
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DO DILIGENCE
(Continued from p. 54) As with any portfolio comprised of stocks, ETFs and mutual funds, Betterment’s portfolio can also be run through the free Exploratory Portfolio Intelligence (EPI) analysis service provided by Quiet Foundation. This portfolio was entered based on the weightings included in the table, initiated at the beginning of 2019. The result was a score of 50 (out of 100), earning the portfolio a rating of “Satisfactory.” The “Diversification Wellness” score on the EPI report was low because of a high internal correlation between the positions. Of the stockbased ETFs, five of the six (76% of the total portfolio) had a correlation with the S&P 500 above 0.9. These holdings tend to move in the same direc-
tion as each other and the overall U.S. stock market. This portfolio also lagged behind the S&P 500 in the last three months, gaining 11% compared to the S&P’s 13%. However, the bond allocation does help the portfolio see slightly lower volatility, 12.7% versus 13.2% for the S&P. The EPI report gave a higher score in liquidity, as eight of the 11 ETFs have more than 2 million shares traded on average per day. The opportunity score was lower, indicating that most of these symbols do not have liquid options markets. This indicates limited prospects for enhancement strategies, using options against long holdings. All in all, robo-advisors such as Betterment may be a practical choice for the passive investor looking to delegate investment author-
ity over their assets. However, it may not be the best choice for the financially literate, confident, pro-active, self-directed (luckbox-subscribing) investor. James Blakeway is CEO of Quiet Foundation, a data science-driven subsidiary of tastytrade that provides a fee-free investment advisory service for self-directed investors.
Evaluate any portfolio with Quiet Foundation
50: Satisfactory
FUTURES
(Continued from p. 55) while the dollar (UUP) is also up 3.5%. When looking at the dollar, use EuroFX (/6E) as a currency proxy. Remember when the dollar rises, the euro falls, and vice versa. There’s a negative correlation (statistically significant inverse relationship) between changes in the value of the dollar and the price of oil. Historically, crude oil has had a -0.25 correlation to the dollar (or about a +0.25 correlation to the euro). With the looser correlation of just -0.25, however, the market goes through periods of divergence but always seems to revert to normality. You can see how an example of this in “Crude and U.S. dollar correlation,” page 55). With a dynamic correlation and large price movements in both underlyings, a “pairs” trade in EuroFX and crude could be interesting. If investors want to get short oil, then selling it against the euro would present a greater extreme than the dollar. Pete Mulmat, chief futures strategist at tastytrade, serves as host for a number of daily futures segments on the tastytrade network under the main flagship programming slot called Splash Into Futures.
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Crude in euros Looking at the price of crude oil in EuroFX terms, observers see a larger percentage rally than they would observe looking at crude priced in dollars.
Trade ideas Here are three ways to construct a “pairs” trade in EuroFX and crude with differing levels of exposure to the products. Crude Oil Trade
Euro Trade
TYPE
Long Put Spread
Long Call Spread
Small, Slow Trade
Short Call
Short Put
Medium, Faster Trade
Short Future
Long Future
Large, Fast Trade
Crude oil and the dollar are doing something they have only done 11 times in the past 35 years.
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CHERRY PICKS
Ripe & juicy trade ideas
Reading VIX & Spotting Volatility By Michael Rechenthin
A
t the time of this writing, the S&P 500 (SPX) has risen by 16% since the beginning of the year to near all-time highs. With that increase, the CBOE’s Volatility Index (VIX)—a measure of fear in the market—has decreased because fear and price are inversely related. In other words, the higher the S&P 500 price climbs, the more the market feels complacent and the less it fears. That equates to a lower VIX price (see “Fall and rise of the VIX,” right). So, how exactly would an investor interpret the VIX? How can an investor use it to provide a better expectation of movement within an account? With the VIX at 13 at the time of this writing, the 1-month expectation of price movement in the S&P 500 is ±3.8%. That means that traders are expecting the S&P 500 to rise or fall by 3.8% over the next month 68% of the time. Having this cheat sheet provides a better understanding of the market and enables one to make better-informed decisions in the market. But while the S&P 500 is relatively muted with respect to the expectation of movement, the same can’t be said about other indices and sectors. For example, the Biotech ETF (XBI) is expecting moves of ±9.4% over the next month. Brazil (EWZ) and oil production and service (OIH and XOP) are also seeing a large move expectation, as is shown in “Sectors at a glance,” right. That, luckbox reader, is how to take advantage of volatility. Michael Rechenthin, Ph.D., (aka “Dr. Data”) is head of research and data science at tastytrade.
Fall and rise of the VIX The higher the S&P 500 price climbs, the more the market feels complacent and the less it fears (lower VIX price).
Sectors at a glance While the S&P 500 is relatively muted with respect to the expectation of movement, the same can’t be said about other indices and sectors. Symbol
Description
1-Month Expectation of Price
XBI
SPDR Biotech ETF
± 9.4%
EWZ
iShares MSCI Brazil ETF
± 9.3%
OIH
Vaneck Oil Services ETF
± 8.9%
XOP
SPDR S&P Oil & Gas Exploration and Production ETF
± 8.7%
GDXJ
Vaneck Jr. Gold Miners ETF
± 8.3%
XME
SPDR S&P Metals and Mining ETF
± 7.1%
GDX
Vaneck Gold Miners ETF
± 6.9%
KRE
SPDR Regional Banking
± 6.8%
FXI
iShares China Large-Cap ETF
± 5.7%
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XBI bullish, short put
GDXJ neutral strangle
XBI is down 13% over the past month while the overall market is up over the same period. For the trade idea, we’ll take a bullish stance by selling a put, five strikes below the last sale using the next month’s expiration. For example, with the price of XBI currently at 84, this would involve selling the 79 strike for a price of $2.40.
The Gold Junior Miners—exploration companies that are often considered growth stocks—has been stuck in a range. Here, investors can take advantage of the high expectation of price movement by selling a $2 wide strangle—in other words, sell a put $2 below the current price and a call $2 above the last price. That will profit if the price stays between the strikes.
june 2019 | luckbox
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techniques essential trading strategies
BASIC
The Power of Diversification Stock prices don’t all move in the same direction at the same time, so diversifying a portfolio helps control risk By Michael Rechenthin
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espite what financial advisors say, perfect diversification doesn’t exist. Advisors might suggest a little big cap here, small cap there, international this and fixed income that. Then they wave a diversification wand and call upon the magic financial fairy to eliminate risk from the portfolio. All of this works well as long as the market keeps going up. When the market heads south, that fairy is nowhere to be found. Neither is that financial advisor. But investors who learn a few techniques can succeed no matter what direction the overall market takes. Real diversification doesn’t guarantee high rates of return—its purpose is to gain greater control of the risk in the portfolio through careful selection of uncorrelated products and the mechanical application of selling options. Diversification provides control of investments by treating them as a portfolio of correlated and uncorrelated positions. Let’s examine a simple portfolio of four symbols and then explore how using options can create positive cash flow each month. Take a look at a chart showing a portfolio of stock indices (see “Four portfolio stock indices,” right). While they’re all moving in (mostly) the
same direction, a slight amount of diversification is gained because the indices contain a large number of stocks and different allocations of components. Thus, the investor is dealing with “unsystematic risks,” which are specific to a company, industry or sector and can be reduced through diversification. But one can do better. Now take a look at a portfolio of
Four portfolio stock indices Take a look at a portfolio of stock indices.
the S&P 500, along with the addition of utilities, gold and bonds in “Adding elements,” below. Even though taking a long position in all of them, the positions don’t all move in the same direction all of the time. So, when equities decline, not all of the portfolio’s positions decline in value. Often during equity declines, gold and bonds increase in value as the market deems them
Adding elements Here is a portfolio of the S&P 500, along with the addition of utilities, gold and bonds.
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techniques
“safer.” Utilities comprise less than 5% of the S&P 500, so many investors’ portfolios are underrepresented in that important sector of the economy. Many long-term investors like utilites because of their historical stability and relatively high dividends (3%), compared to the S&P 500 (1.8%). Take a look now at a few big declines in equities and see how all of the symbols fared in “Symbol selection,” below. In all of the scenarios, the S&P 500 declined by significant amounts, yet gold, bonds and utilities either didn’t fall by as much or actually increased. That’s real diversification, and it significantly reduces overall account volatility by lessening the severity of the declines. Symbol selection isn’t the only way to achieve diversification. Another way is through strategy selection— selling calls against long positions to reduce risk and create a bit of buffer. Take a look at a portfolio of the four symbols along with a covered call strategy in each in “Power of diversification,” right. In this diversified portfolio, the investor bought 100 shares of each of the symbols and then sold a call using the first, out-of-the-money strike in the following month’s expiration. In other words, if XLU has a price of $57.25 in June, a trader would buy 100 shares and then sell
the 58 call using the July expiration. Using another example, if TLT has a price of $121.10 in June, a trader would buy 100 shares, and sell the $122 call using the July expiration. Owning the stock has the advantage of being able to collect the dividend, while the call works by providing additional cash flow in the account. When the call is near expiration, simply close the call and open another one using the nearest out-ofthe-money call. Rinse and repeat! If these numbers are annualized, which is the equivalent of doing these strategies every month on the stocks held, it provides roughly $5,000 worth of premium. This means the stocks could decline by 9% before we theoretically begin losing money.
Selling calls against long positions reduces risk and creates a bit of a buffer Buying stock alone doesn’t have the same ability to reduce costs. Options provide this value. The drawback is that returns are sometimes capped during strong upward swings, but historically selling the call has the ability to outperform during longer stretches of times. This is the power of diversification. Michael Rechenthin, Ph.D. (aka “Dr. Data”), is head of research and data science at tastytrade.
Power of diversification Take a look at a portfolio of the four symbols along with a covered call strategy in each. If these numbers are annualized, which is the equivalent of doing these strategies every month on the stocks held, it provides roughly $5,000 worth of premium.
Description
Symbol
Value of 100 Shares
Cash flow from selling 1 OTM call (next month’s expiration)
Annualized downside protection gained
S&P 500
SPY
$28,700
$320
11%
Utilities
XLU
$5,700
$40
7%
Bonds
TLT
$12,300
$70
6%
Gold
GLD
$12,100
$70
6%
$58,800
$500
9%
Symbol selection Take a look now at a few big declines in equities and see how all of the symbols fared.
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techniques
INTERMEDIATE
At-the-Money Long Call Spread Have a hunch a stock will go higher? Here’s a way to buy in at a lower cost and with less risk By Anton Kulikov
have the chance of making $50. How does one calculate that? Take the probability of profit, 50%, and multiply it by the width of the spread, $50.50 minus $49.50, which equals $1.00. 50% times $1.00 equals $0.50, and we multiply that by 100 to get the net debit paid for the spread. Because the width of the spread is $1.00 and the investor is paying $0.50, the goal is for the spread to be worth $1.00 by expiration, yielding a $0.50 profit, or a payoff of 1:1. When an investor can’t get perfect symmetry around the stock price, buy the first in-the-money call and sell the first out-of-the-money call. The probability will be around 50%, and investors can multiply that by the width of the spread to calculate how much they’re risking and the payoff. The amount the investor actually pay for the spread varies but in liquid underlyings, the amount paid should roughly equal the amount the investor stands to make. What if the amount one stands to make seems too small? Just increase the number of contracts so that the desired risk matches the spread risk. It will always be a 1:1 payoff, but the absolute amount risked can be determined by the number of spreads purchased. That’s the scalability factor.
Fully in or out This $1 wide spread has a high probability of expiring either fully in-the-money or fully out-of-the-money, thus yielding either a 1:1 payoff or loss of the debit paid.
$60 $40 Profit/Loss
S
ometimes an investor has a bullish hunch and wants to take a shot on a stock going higher. What are the ways of doing that? Well, an investor could buy the stock outright, but that’s usually expensive, carries more risk than a portfolio can handle and ties up capital needed for core positions. A smarter way reduces the big numbers and works with a smaller account. It requires constructing a position that enables an investor to take a 50/50 shot to the upside (just like buying stock), while limiting risk to a known level (which stock can’t do) and taking up only a little capital. It doesn’t overshadow the core positions, either. That’s known as a long at-themoney call spread. It has a 50% chance of winning, and it pays 1:1— risk $1 to make $1. Additionally, the strategy is scalable, which means the investor can define the risk to whatever amount they choose, according to the size of the account. Look at an example. Stock XYZ is trading at $50, and the investor buys a $49.50 call expiring around 45 days from now and sells a $50.50 call with the same expiration date. That’s known as a long call vertical. Because that trade has a 50% chance of winning, the payoff has to be 1:1 to make it worthwhile. So for this particular spread, an investor should expect to pay around $50 to
$20 $0 $-20 $-40 $-60 44
46
48
50 52 Stock Price
54
56
50
This strategy has a
%
chance of winning and pays 1:1
Anton Kulikov is a trader, data scientist and research analyst at tastytrade.
In liquid underlyings, the amount paid for the spread should roughly equal the amount the investor stands to make june 2019 | luckbox
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ADVANCED
The Mullet Trade Calendar spreads: short in front, long in back By Michael Gough
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Time sensitive The aptly named calendar spread offers a low-risk, directionally neutral strategy that profits from the passing of time between two different expiration cycles. Calendar Spread Risk Profile
Stock Price P&L at Front Month Expiration
the current stock price for a slightly bullish strategy or at the current stock price for a neutral strategy. A calendar spread, comprised of one long option and one short option, has the same strike price and different expiration dates. To construct one, sell a front month option and purchase a longer dated option. Like the mullet haircut, calendar spreads are short in front and long in back. Investors construct them using either puts or calls, but generally with the same type of option—both calls or both puts. Calendar spreads are an inexpensive trade placed for a debit. Because they’re slow-moving and benefit from an increase in implied volatility, manage them at a profit of 10% to 25% of the debit paid. If, for example, it costs $100, manage at $125 for a 25% profit. When placing a calendar spread,
Strike Price
look for an underlying with plenty of option liquidity and low implied volatility. Look at SPY, one of the most-liquid ETFs, which tracks the S&P 500 Index. Each day, investors trade more than 1 million option contracts on SPY, and most have strikes and expirations with penny-wide spreads. Tight markets and low implied volatility make SPY an excellent candidate for a calendar spread. If the current expiration months for SPY are June and July, investors can initiate a put calendar spread by selling the at-the-money put expiring in June and buying the at-the-money put expiring in July. This trade uses only $150 in buying power, and if managed at 25% the trader nets a profit of roughly $38. Michael Gough, a self-taught coder who became an options trader, serves as co-host of tastytrade’s Research Specials Live.
Tight markets and low implied volatility make SPY an excellent candidate for a calendar spread
PHOTOGRAPH: REUTERS/MPTVIMAGES.COM
S
ome investors hold off on trading until periods of high implied volatility. But if they consider volatility high only when the VIX “fear gauge” surpasses 20, they’ll be sitting on their hands 60% of the time. Using calendar spreads, traders can stay engaged during all market environments and profit from the passing of time. Option contracts contain an embedded time component nonexistent in stocks. While investors can hold stock positions indefinitely, option contracts have a listed expiration date. This time component gives traders an edge that traditional stock traders don’t have. Standard option contracts expire the third Friday of each month, and most liquid stocks list options expiring several months in advance. Traders can buy and sell around different expiration cycles. One such trade that benefits from different expiration dates, the aptly named calendar spread, offers a low-risk, directionally neutral strategy that profits from the passing of time between two different expiration cycles. When volatility’s low, it enables traders to stay engaged with a small capital outlay. The goal of the calendar spread is for the stock or index to be at or close to the strike price of the calendar close to expiration. Then the short front-month option will be cheaper, while the long back month option retains value. That’s when the price of the calendar should be greater than the debit paid initially. Investors can place calendar spreads at a strike price below the current stock price for a slightly bearish strategy, above
luckbox | june 2019
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luckbox of the month
ROBO INVESTORS Wolf Richter, a keen observer of the markets (see p. 30), recently noted the lift the broader U.S. equity market has enjoyed as the result of the record pace of equity buybacks. luckbox couldn’t help but note the beneficiaries: the robotic investors who buy and hold. Thus, that legion of human robots has collectively earned the title of luckbox of the month for June. They qualify for the dubious title because their investment outcomes have exceeded their skills...for now.
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Without stock buybacks, demand for shares would fall dramatically. It’s too painful even to imagine Buyback bliss
2015
2014
2013
2012
S&P 500 Company Buybacks (in billions)
2016
SPY AAPL
In addition, earnings-per-share would dwindle. Share buybacks reduce the number of shares outstanding, and total earnings divided by fewer shares outstanding gives a larger earnings-pershare number. But without share buybacks, earnings-per-share growth and actual earnings growth would be the same. That would be devastating. They note that during the past 15 years, for the median S&P 500 company, earnings-per-share growth, powered by the reduction in the stock outstanding, was on average 2.6% higher than actual earnings growth. So in a world without buybacks, “forward EPS (earnings per share) growth could be trimmed by 250 basis points,” they said. That type of reduction, they said, has historically corresponded to a 1-point decline in forward price-earnings multiples.” In other words, valuations would fall. And then comes the big question of what happens to “demand.” “Eliminating the largest source of equity demand could lower the demand curve if other investor categories do not replace the corporate bid from buybacks,” they warned. And the bull market would lose the force that powered it. Letting the stock market fend for itself without relentless buybacks would become a true nightmare. Virtually no buy-and-hold luckboxes could hope to prosper. —Wolf Richter
2017
stocks in a “world without buybacks?” Share buybacks were considered securities fraud under most conditions until 1982, but then became legal under a new set of loose rules. Now, members of Congress from both parties have targeted share buybacks and have proposed legislation. Goldman is apparently worried that notion might gain some traction, and so it created its scenario of a world without buybacks. It would be a truly unspeakable, nay, an unthinkably gruesome nightmare, and no politician would want to take responsibility for it. Imagine a world in which stock prices would decline! “Repurchases have consistently been the largest source of U.S. equity demand,” the Goldman strategists wrote in their note. “Without company buybacks, demand for shares would fall dramatically.” Volatility would rise. To figure that out, the strategists looked at 25 years of quarterly blackout periods that restrict some buybacks around earnings release dates. The blackout periods start five weeks before earnings releases and last until two days afterwards. But they’re not blackout periods: They restrict only spur-ofthe-moment buybacks. Scheduled buybacks around earnings release dates are not restricted. By looking at stock performance during those blackout periods, the strategists discovered that, according to Bloomberg, “return dispersion and volatility during blackout windows have been higher compared with non-blackout periods: 16% versus 14%, and 16.4 points versus 15.8 points, respectively.”
2018
G
oldman Sachs asked a nerveracking question and came up with an equally nerve-racking answer: What would happen to stocks “in a world without buybacks?” The short answer? A lot would go wrong without buybacks, which raise stock prices, inflate earnings per share and prop up the markets. What’s more, they’ve been happening a lot lately. In the fourth quarter of 2018, share repurchases soared 62.8% from a year earlier to a record $223 billion, beating the quarterly record set in the third quarter last year of $204 billion. It was the fourth quarterly record in a row, the longest such streak in the 20 years of the data. For the whole year 2018, share buybacks soared 55% year-over-year to a record $806 billion, beating the prior record of $589 billion set in 2007 by a blistering 37%! Share buybacks had already peaked in 2015 and ticked down in 2016 and 2017. Then the Tax Cuts and Jobs Act of 2017 became effective on Jan. 1, 2018, and share buybacks skyrocketed. The record buybacks in Q4 came even as stock prices declined on average by 5.3%. On some bad days during the quarter, corporations were about the only ones left buying their shares. The scale was enormous. For the year 2018, Apple (AAPL) topped all of the other buyback queens, repurchasing shares valued at $74.2 billion. But it all worked out. As investors were selling, companies were buying back their own shares. And markets boomed. But what would happen to
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