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The Mosaic Financial Conditions Index: A New Perspective on Leading Indicators Kevin A. Lenox, CFA

KLenox@Gmail.com 5/12/2010


Abstract This paper introduces the Mosaic Financial Conditions Index (MFCI) as a practical supplement for investors to monitor changes in current financial conditions. The purpose was to provide meaningful and predictive content to aid the investment decision-making process. Financial conditions can be thought of as the current status of financial variables such as corporate bond spreads, asset prices, as well as the cost and availability of credit that can directly impact both investor behavior and future economic growth. The MFCI is updated on a daily/weekly basis, and is comprised of eight variables that represent different aspects of financial conditions within the U.S. financial markets. The cornerstone of the MFCI involves the significant leading indicator qualities of credit market variables such as high yield and corporate bond spreads. Abundant empirical data suggests that the more credit sensitive and potentially illiquid markets such as high yield may be considered a sort of “canary in the coal mine” as a leading indicator of expected changes in external borrowing costs and the bond risk premium. A study by de Bondt (2005), revealed that “the level of and change in the credit market risk premium typically leads the stock market by up to four weeks.” Results indicate that the MFCI has considerable predictive ability with an 2 adjusted R of .749 to the S&P 500 given a two-period (week) lag since inception of the study period on December 11, 1998, particularly before important inflection points. See Figure 1.

The author thanks Dr. Ron Marks for model verification and statistical analysis. The views expressed in this paper are solely the responsibility of the author.

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Figure 1

Mosaic Financial Conditions Index 12/11/1998 - 5/7/2010 1,700 2.00 1,500

1.00

1,300

0.00

S&P 500 1,100

-1.00 MFCI

900

-2.00

700

-3.00

500

-4.00 98

99

00 S&P 500

01

02

03

04

05

06

07

08

09

Mosaic Financial Conditions Index (MFCI)

Introduction Beginning in August of 2007, the U.S. financial markets suffered the most severe financial crisis since the Great Depression. The systemic credit shock resulted in dramatic declines in market liquidity and access to credit. In addition, the flight to higher quality assets, sharp spikes in market volatility and rising risk premiums are further examples of financial conditions that can impact both investor behavior and economic growth. The severity of the financial crisis has highlighted the significance of monitoring the path of financial conditions overall as they relate to forecasts of asset prices and economic activity by market participants. A recent study by Gilchrist, Yankov and Zakrajsek (2009), found that “shocks to credit markets have played an important role in business cycle fluctuations during the past decade and a half.�

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Overview of the Mosaic Financial Conditions Index The Mosaic Financial Conditions Index (MFCI) is designed to provide investors with a timely and practical guide for assessing the level and trend of financial conditions in the U.S. financial system. The goal is to provide a daily/weekly measure of financial conditions that presents an additional level of insight and judgment which improves the investment decision-making process. The MFCI is comprised of eight variables that represent different aspects of financial conditions within the U.S. financial markets such as flight to liquidity, flight to quality, as well as the cost and availability of credit. Credit spreads, measured as the difference in yield between bonds such as high yield and investment grade contain information regarding expected default risks that is not available from traditional leading indicators, Gilchrist and Yankov (2009). This provides an important and daily link between the real economy and the financial markets. During periods of economic uncertainty, the level and trend in the MFCI can provide earlywarning signals that help gauge the degree of strains in financial markets. The cornerstone of the MFCI involves the leading indicator qualities of credit market variables such as high yield and corporate bond spreads. Equity investors often under-appreciate the importance of the credit markets while forecasting returns for the stock market and economic growth. That’s a mistake. According to Gertler and Lown (1999) and Mody and Taylor (2004), there is strong predictive ability regarding industrial production growth and U.S. employment trends provided by the high yield market. In fact, the more credit sensitive and potentially illiquid markets such as high yield and asset backed securities may be considered a sort of “canary in the coal mine” as a leading indicator of expected changes in borrowing costs, economic growth and the risk premium. A study by de Bondt (2005), revealed that “the level of and change in the credit market risk premium typically leads the stock market by up to four weeks.” The model effectively explains the trend in the S&P 500 with a robust adjusted R 2 of .749 given a two-period (week) lag from December 1998 through April 2010. Testing showed that a fourperiod lag produced a similar adjusted R2 of .750. It’s important to note that the sign (+/-) of the daily/weekly composite value is changed in order to provide for a more convenient comparison with other indices. Much of the time, the MFCI can be thought of as a coinciding rather than leading index as financial conditions will often follow the general trend of the stock market. However, the leading indicator nature of the index has frequently diverged in advance of the stock market during important inflection points.

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Why Watching the Stock Market Means Also Watching the Credit Markets The high yield market can be thought of as an alternative measure of the premium paid for external financing. As a result, rising credit spreads (lower asset values), measured as the difference in yield between bonds such as high yield and higher quality investment grade bonds, can have an impact on the real economy. For example, rising credit spreads can reflect disruptions in the supply of credit resulting from either a worsening in the quality of corporate balance sheets or from constraints on the financial intermediaries that supply credit. In this context, a contraction in credit supply is typically associated with declining asset values and rising yield spreads as lenders demand compensation for the expected increase in defaults. Figure 2 shows that the negative divergence of the OAS spread between the Merrill Lynch High Yield Master II and the Merrill Lynch Corporate Master versus the S&P 500 should have been seen as a sign of trouble for the economy as well as stock prices. In fact, this spread widened substantially from 190 bps on July 6th to 319 on September 7th. Meanwhile, the S&P 500 corrected only slightly from 1,530 to 1,453 during this same period. It’s also noteworthy that the spread had increased to a whopping 566 bps by September 26th of 2008, while the S&P 500 was at 1,213. Three weeks later, the S&P 500 closed at 899. Please note that the increasing spread is consistent with deteriorating financial conditions because the sign (+/-) of the MFCI composite value is changed. Figure 2

High Yield - Investment Grade OAS Spread January 2007 - October 2008 1,700 1,600 1,500 1,400 1,300 S&P 500 1,200 1,100 1,000 900 800 700

1,050 850 650 450 250

Source: Merrill Lynch

50

07 S&P 500

08 Merrill Lynch High Yield Master II - Merrill Lynch Corporate Master

5

OAS Spread (bps)


Methodology and Component Variables The MFCI was constructed using weekly data series for eight variables over the sample period December 11, 1998 to May 7, 2010. The use of a principal component model was chosen as the most appropriate statistical technique, and improved the forecasting capabilities of the model relative to other statistical methods that were investigated. Principal components analysis is a statistical process that extracts those factors responsible for the correlation among the variables. Assuming that financial conditions represent the primary factor causing the correlation, removing this factor (the principal component) allows for improved predictive abilities. The first factor variant accounts for 63.1% of the total variation explained by the MFCI. The MFCI is constructed in the following sequence: First, each variable is normalized, and then divided by their respective standard deviations. This allows variables with different scales to be compared evenly. The principal components method then utilizes the normalized values to calculate the coefficients for each variable. Then, each normalized value is multiplied by its respective adjusted coefficient. Finally, the sign (+/-) of the composite index value is changed in order to reflect improving financial conditions when the composite value is rising, and deteriorating financial conditions when the value is declining. The individual variables are listed below. Yield Spreads:      

2-Year Swap Spread 30-Year Mortgage Rate – 10-Year Treasury Moody’s Aaa – 10-Year Treasury Moody’s Baa – Moody’s Aaa Merrill Lynch High Yield Master II – Merrill Lynch Corporate Master Merrill Lynch Asset-Backed Securities Index, BBB-AA

Other Indicators:  

CBOE Volatility Index (VIX) Relative Strength of the AMEX Broker/Dealer Index (XBD) to the S&P 500

Sources of Data to Construct the Index:    

Moody’s Economy.com Federal Reserve Merrill Lynch Yahoo! Finance, Yahoofinance.com 6


Broker/Dealer Stocks as a Leading Indicator The S&P 500 is widely considered to be an important leading indicator of financial conditions. Rather than tracking the S&P 500 itself as a leading indicator of financial conditions, the MFCI tracks the relative strength of the AMEX Securities Broker/Dealer Index (XBD) versus the S&P 500. The XBD is thought to provide a much more specific view of current financial conditions by excluding the more diversified bank stocks. Exclusion of the stock market can also provide a different view of financial conditions (particularly to equity investors) without the influence of the stock market itself or sector rotation between cyclical and defensive sectors of the market. The XBD is often compared with the VIX as an inverse indicator. As seen in Figure 3, the XBD began to lose relative strength in July, 2007 and this continued through the remainder of the year. Figure 3

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A Closer Look at Selected Time-Periods Figure 4

Mosaic Financial Conditions Index 5/5/2006 - 5/7/2010 3.00 2.00 1.00 0.00 -1.00 MFCI -2.00 -3.00 -4.00 -5.00

1,600 1,400 S&P 500

1,200 1,000 800 600 06

07 S&P 500

08

09

10

Mosaic Financial Conditions Index

Figure 4 displays how the MFCI diverged from the S&P 500 in 2007, well before the S&P 500 began to sense the impending economic downturn. By December 2008, financial conditions began to rebound in anticipation of an economic recovery that was not yet apparent to equity investors. Figure 5 also reveals the delayed reaction by the S&P 500 to the economic slowdown in 2000 and the subsequent recovery in late 2002. Figure 5

Mosaic Financial Conditions Index 2000 - 2003

S&P 500

1,700

1.00

1,500

0.50

1,300

0.00

1,100

-0.50

900

-1.00

700

-1.50 00

01 S&P 500

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03

Mosaic Financial Conditions Index

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MFCI


Bank Lending Conditions as a Leading Indicator of Economic Growth Credit spreads are significantly related to general economic conditions and according to Swiston (2008), “the correlation of high yield spreads with growth is because the spreads are one way to proxy for the availability of credit.” Credit availability, as measured by bank lending standards, can have a substantial impact on economic growth, and tend to lead changes in real GDP growth. Perhaps the best guide for assessing current credit conditions can be found in the Senior Loan Officer Opinion Survey on Bank Lending Practices (SLOOS). The survey is conducted by the Federal Reserve on a quarterly basis, including approximately sixty large domestic banks and over twenty U.S. branches and agencies of foreign banks. The survey includes questions regarding the changes in the standards and terms of the banks’ lending and the state of business and household demand for loans. Within the survey, Swiston (2008) validated earlier studies by Lown and Morgan (2002, 2006) that standards for commercial and industrial loans (C&I) provided the best aggregate measure for overall credit availability. Similar surveys are also conducted by the European Central Bank, the Bank of England and the Bank of Japan. Figure 6 shows how periods of sharp tightening in lending standards have coincided with the onset of economic downturns. Figure 6

U.S. Bank Lending Conditions & U.S. Real GDP 10.0 8.0 6.0 4.0 2.0 0.0 -2.0 -4.0 -6.0 -8.0

90.0 70.0 50.0 30.0 10.0 -10.0

Source: Federal Reserve

-30.0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Real GDP

C&I Loan Standards for Large and Medium-Size Firms

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Net % Tightening

Real GDP

FRB Senior Officer Loan Survey


Conclusion The most important implication is that monitoring the credit markets as well as the other aspects of financial conditions can serve as a timely and unique leading indicator that adds a new perspective to the asset allocation process. Of particular interest to equity investors is how the credit markets often diverge from the stock market in advance of important inflection points. Indeed, de Bondt (2005) documented how the credit markets typically lead the stock market by several weeks. The core element of the Mosaic Financial Conditions Index (MFCI) involves the leading indicator qualities of credit market variables such as high yield and corporate bond spreads, but also includes other important aspects of financial conditions. Updated on a daily/weekly basis, the model can provide an important link between the real and financial sides of the economy. The model effectively explains the trend in the S&P 500 with a robust adjusted R 2 of .749 given a two-period (week) lag from December 1998 through April 2010. Testing showed that a fourperiod lag produced a similar adjusted R2 of .750. Much of the time, the MFCI can be thought of as a coinciding rather than leading index as financial conditions will often follow the same trend as the S&P 500. However, the leading indicator nature of the variables and the index frequently diverge in advance of the stock market during important inflection points. It’s important to note that a single broad summary of financial condition variables cannot capture all of the potential sources of factors that affect future economic growth. The MFCI focuses on the financial conditions in the U.S. financial system; however, the financial conditions in foreign markets also warrant inspection in today’s global economy. Non-model variables such as trends in emerging markets, international credit markets and currency volatility patterns can yield valuable additional insight.

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References De Bondt, G., 2005 “Does the Credit Risk Premium Lead the Stock Market?” Applied Economic Financial Letters, 2005, 1, 263-268. Gertler, M. and Lown, C.S. 1999. “The Information in the High-Yield Bond Spread for the Business Cycle: Evidence and Some Implications.” Oxford Review of Economic Policy 15(3), 132150. Gilchrist, S., Yankov, V., and Zakrajsek, V. (2009). “Credit Market Shocks and Economic Fluctuations: Evidence from Corporate Bond and Stock Markets.” Mody, A., and M.P. Taylor (2004): “Financial Predictors of Real Activity and the Financial Accelerator,” Economic Letters, 82, 167-172. Swiston, A., (2008): “A U.S. Financial Conditions Index: Putting Credit Where Credit is Due.” IMF Working Paper. Western Hemisphere Department.

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Mosaic Financial Conditions Index  

To monitor current financial conditions in order to help investors improve their decision-making process.

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