Momentum Investing

Which measure of mutual fund momentum best predicts future fund returns? In his August 2009 paper entitled “The 52-Week High, Momentum, and Predicting Mutual Fund Returns”, Travis Sapp examines the intermediate-term future performance of mutual funds ranked by: (1) nearness to the one-year high of the fund share net asset value; (2) prior six-month fund return; and, (3) fund sensitivity to stock return momentum. Using mutual fund returns for a broad sample of U.S. common stock funds and risk-adjustment data over the period 1970-2004, he concludes that: Keep Reading

A reader wondered about the value of combining momentum and downside risk avoidance for tactical asset class allocation, as follows:

“One of the methods described in The Ivy Portfolio by Mebane Faber is a simple momentum-based asset class rotation system that shifts monthly into the one, two or three highest performing asset classes based on their performance over an average of the prior 3, 6 and 12 months. Instead of using just the 3, 6 and 12 month prior returns, what if we used an asset class Ulcer Performance Index (UPI): UPI = average return over prior 3, 6 and 12 months / average Ulcer Index (UI) over prior 3, 6 and 12 months. Would this modification identify which asset classes are in low-volatility uptrends and therefore the biggest bang for the buck? Would this allow us to invest comfortably in the top two asset classes, or even the top one asset class, instead of the top three as recommended by Faber?”

Calculation of UI over a rolling interval across a long sample period is cumbersome. As a substitute for UI, we use a standard deviation of downside weekly returns over past intervals for three asset classes: S&P Depository Receipts (SPY), iShares Barclays 20+ Year Treasury Bond (TLT) and iShares Russell 2000 Index (IWM) , with historical data limited to July 2002 (by TLT). Every four weeks, we allocate funds to whichever of SPY, TLT or IWM has the highest ratio of prior return to prior downside standard deviation, or to 13-week Treasury bills (T-bills) if all three past returns are less than the T-bill yield. Using weekly adjusted closes for the asset class proxies over the period 7/31/02 through 8/21/09 (369 weeks or about 89 months), we find that: Keep Reading

Does momentum trading (and its contrarian counterpart) work better for certain kinds of stocks? In their August 2009 paper entitled “Systematic Risk and the Performance of Mutual Funds Pursuing Momentum and Contrarian Trades”, Grant Cullen, Dominic Gasbarro, Gary Monroe and Kenton Zumwalt examine mutual fund trading activity and performance to measure the prevalence of and results for momentum and contrarian equity investing strategies. Using the quarterly stock holdings of 2,829 U.S. equity mutual funds and associated stock price data for the period 1991-2006, they conclude that: Keep Reading

In his 2009 book, Quantitative Strategies for Achieving Alpha, flagged by Jeff Partlow, author Richard Tortoriello “seeks to determine empirically the major fundamental and market-based drivers of future stock market returns” by testing over 1,200 alternative investment strategies. He believes “that the quantitative approaches outlined in this book can provide a proven way to generate investment ideas for the qualitative investor as well as a discipline that can help improve investment results.” Richard Tortoriello is an equity research analyst with Standard & Poor’s. The principal elements of the book are: Keep Reading

Is chasing returns a bet on rational analysis or investor overreaction? In the June 2009 version of their paper entitled “Myopic Extrapolation, Price Momentum, and Price Reversal”, Long Chen, Claudia Moise and Xinlei Zhao compare expected and actual momentum returns and explore the detailed relationship between momentum/reversal returns and firm fundamentals. Using monthly stock return data and associated fundamentals for a broad sample of firms spanning 1985-2006, they conclude that: Keep Reading

A reader wondered about the value of combining momentum and simple moving average signals for asset class allocation, as follows:

• Each month calculate the average momentum of each asset class over the prior 3, 6 and 12 months
• Hold the top positions as long as they are also trading above their 10-month SMA (otherwise go to cash)

We test these rules using exchange-traded funds (ETF) as easily tradable asset class proxies. However, many ETFs have very short histories, greatly restricting any such test. We use S&P Depository Receipts (SPY), iShares Barclays 20+ Year Treasury Bond (TLT) and iShares Russell 2000 Index (IWM) as available asset classes, with historical data limited to July 2002 (by TLT). We use the 13-week Treasury bill (T-bill) yield as a proxy for the return on cash. Each month, we allocate funds to the one asset class with the highest average momentum over the prior 3, 6 and 12 months, unless the momentum leader is below its lagged 10-month SMA, in which case we put all funds into T-bills. Using monthly values for SPY, TLT, IWM and the T-bill yield over the period July 2002 through April 2009 (82 months), we find that: Keep Reading

In their 2009 book, The Ivy Portfolio: How to Invest Like the Top Endowments and Avoid Bear Markets, Mebane Faber and Eric Richardson “profile the top endowments and then examine how an investor can hope to replicate their returns while avoiding bear markets. The focus [is] on practical applications that an investor can implement immediately to take control of their investment portfolio.” Mebane Faber “is the portfolio manager at Cambria Investment Management where he manages equity and global tactical asset allocation portfolios” and a co-founder of AlphaClone, an investing research web site. Eric Richardson is Chairman and founder of Cambria Investment Management. The book has a complementary web site that links to source materials. The principal messages of the book are: Keep Reading

The value premium and the momentum effect are arguably complementary drivers of financial asset pricing dynamics, with the latter alternatively creating and extinguishing the former. Does empirical evidence support this view across asset classes? In the February 2009 version of their paper entitled “Value and Momentum Everywhere”, Clifford Asness, Tobias Moskowitz, and Lasse Pedersen investigate the interplay of value and momentum across asset classes worldwide, as follows: (1) stocks within four major countries; (2) country equity indexes; (3) government bonds; (4) currencies; and, (5) commodities. They calculate momentum based on return over the past 12 months, excluding the most recent month, for all asset classes. They estimate value based on measures commonly used for each asset class (such as book-to-market ratio for stocks). Using price and value characteristics data for broad samples of these asset classes, they conclude that: Keep Reading

Do returns associated with the four famous factors (market, size, book-to-market, momentum) vary systematically with the state of the market (such as bull or bear)? In their January 2009 paper entitled “The Effect of Market Regimes on Style Allocation”, Manuel Ammann and Michael Verhofen investigate how returns for the four factors differ between market states as determined by a multivariate two-state model of the overall equity market. Using U.S. stock market and factor data spanning 1927-2004, they conclude that: Keep Reading

Do momentum trading strategies work consistently across country markets? In his December 2008 paper entitled “Are Anomalies Still Anomalous? An Examination of Momentum Strategies in Four Financial Markets “, Daxue Wang applies various tests to measure the profitability of momentum strategies in the two largest stock markets in each of Europe (UK and Germany) and Asia (Japan and China). He tests overlapping equally weighted portfolios formed on returns over the past 3, 6, 9 or 12 months (no wait month) and held for 3, 6, 9 or 12 months. Using monthly stock price data and firm characteristics for companies comprising more than 95% of market capitalization in each country over the period 1990 (1994 for China) through 2006, he concludes that: Keep Reading