Virtue of selfish investing scores big yet again in 2017(2)

Page 1

Virtue of Selfish Investing Scores Big Yet Again in 2017 Kacher and Morales founders of Virtue of Selfish Investing, use their proprietary VIX Volatility Model (VVM) for accurately timing trends in the stock market. Virtue of Selfish Investing' s VVM is on track to score a triple digit percentage gain this year in real-time trading. VVM scored triple digit percentage returns every year from 2009-2015, and +61.8% return in 2016 in backtests and partial real-time trading. BEVERLY HILLS, CA FEBRUARY 17, 2017

Virtue of Selfish Investing' s VIX Volatility Model is on track to score a triple digit percentage gain this year. "The long term results of the model going back to 2009 are triple digit >100% returns each year except for 2016 which finished up +61.8%" said co-founder Dr. Chris Kacher. "A great deal of

work has been put into VVM to debug and improve its reliability, much as software gets debugged and updated. Its profit/loss was improved for each year going back to 2009." Kacher continues, "I believe the risk/reward of this strategy is by far the best I've achieved so far in my 25+ year trading career. But that is no reason to oversize your positions. Make sure you understand the risks involved in trading this model before risking any capital." How did the model fare in challenging years such as 2000-2002 and 2008? The model thrives on volatility. In tests using QQQ as the benchmark since volatility ETFs did not exist in those years, the model continued to score triple digit percentage returns. That said, the model also knows how to sit in uptrends for weeks on end on diminished volatility. Interestingly, 2015 was largely trendless thus hugely challenging, yet the model scored its highest returns that year in backtests of +589.7%. In brief, the VIX Volatility Model (VVM) seeks to turn human emotions into profits by capitalizing on emotion-driven events. These events carry predictive value. Price/volume charts are used as a guide, after all, charts are human emotions on parade. The model contains algorithms which help the model continuously learn as markets change. It could be said to be a manual "machine learning" approach to the markets. It is both systematic and discretionary. It is not a static "black box" strategy. Any system of value should in principle be self-learning thus self-evolving. Such a system learns from new data each day. This is the way both Dr. Chris Kacher and Gil Morales have always operated since the early 1990s and explains their long-term success in the stock market.


Turn static files into dynamic content formats.

Create a flipbook
Issuu converts static files into: digital portfolios, online yearbooks, online catalogs, digital photo albums and more. Sign up and create your flipbook.