Momentum Investing

What are the momentum and reversion patterns for stocks that have been consistent past winners or losers? In his June 2010 paper entitled “Does Bad Economic News Play a Greater Role in Shaping Investors’ Expectations than Good Economic News?”, Abdulaziz Alwathainani investigates the relationship between the consistency of past monthly stock performance and future returns. He defines consistent past winners (losers) as those ranking in the top (bottom) 30% of monthly returns for at least six of the last 12 months. He defines stocks ranking in the middle 40% for at least six of the last 12 months as a consistently moderate benchmark. Using monthly return and characteristics data for a broad sample of U.S. stocks spanning 1963-2007, he finds that: Keep Reading

A reader asked: “I found Investors FastTrack via a search last night. Do you know anything about them?” Keep Reading

Do measures of momentum portfolio risk affect returns and return components? In their April 2010 paper entitled “Asymmetric Momentum Effects Under Uncertainty”, David Kelsey, Roman Kozhan and Wei Pang investigate how the profitability of a momentum hedge strategy varies with portfolio firm-level risk. They use six measures of firm-level risk: (1) size (market capitalization); (2) age (since listing); (3) number of analysts following; (4) dispersion of analyst earnings forecasts; (5) realized volatility of weekly stock returns over the past year; and, (6) cash flow volatility. Using stock return, firm fundamentals and analyst earnings forecast data for a broad sample of U.S. stocks spanning 1983-2006, they conclude that: Keep Reading

Momentum strategies generally consider returns over past months up to one year ago in constructing signals for future abnormal returns. Is some part of that 12-month history more important than others? Might returns from more than a year ago be informative? In the November 2009 version of his paper entitled “Is Momentum Really Momentum?”, Robert Novy-Marx parses the effectiveness of past returns as indicators of future returns by age from one to 15 months, focusing on: recent past return with a skip-month, six months to two month old (6-2); and, intermediate past return, 12 months to seven months old (12-7). Using data for a broad sample of U.S. stocks spanning 1926-2008 (83 years) and shorter samples for various other assets, he concludes that: Keep Reading

Does the momentum anomaly hold for industries/asset classes over the long run? In his April 2010 draft paper entitled “Relative Strength Strategies for Investing”, Mebane Faber quantifies the effects on gross returns of applying simple momentum/trend following  rules to U.S. equity industry and global asset class portfolios. His “intent is to describe some simple methods that an everyday investor can use to implement momentum models in trading.” Momentum rankings derive from trailing total returns over intervals ranging from one to twelve months, as well as a combination of multiple intervals. Using monthly levels of ten value-weighted U.S. equity industries spanning July 1926 through December 2009 and of global asset classes spanning 1973-2009, he concludes that: Keep Reading

Does designated creditworthiness, closely related to riskiness, drive the performance of many widely acknowledged stock return anomalies? In the April 2010 revision of their paper entitled “Anomalies and Financial Distress”, Doron Avramov, Tarun Chordia, Gergana Jostova and Alexander Philipov use portfolio sorts and regressions to investigate the relationship between financial distress (low credit ratings and downgrades) and profitability for trading strategies based on: stock price momentum, earnings momentum, credit risk, analyst earnings forecast dispersion, idiosyncratic volatility, asset growth, capital investments, accruals and value. Using data for broad samples of U.S. stocks (limited by extensive information requirements) spanning October 1985 through December 2008, they conclude that: Keep Reading

Can investors enhance momentum returns for individual stocks with combination strategies that incorporate other technical and accounting indicators? In the April 2010 draft of their paper entitled “Technical, Fundamental, and Combined Information for Separating Winners from Losers”, Cheng-Few Lee and Wei-Kang Shih investigate combined momentum strategies based on past stock returns, past trading volume and sets of fundamental (accounting) indicators. They consider two distinct sets of fundamentals: Piotroski’s FSCORE for value stocks and Mohanram’s GSCORE for growth stocks. Their combined strategy is long (short) past winners (losers) with weak (strong) past relationship between returns and trading volume and high (low) fundamental scores. Using stock return/volume and firm fundamentals data for a broad sample of NYSE and AMEX non-financial stocks spanning 1982-2007 (26 years), they find that: Keep Reading

A reader observed and asked: “There are two strategies, both of which appear to work, but which also seem contradictory to each other. Momentum says what goes up must go up further. Reversion says what goes up must come down. Both work? There must be something wrong here?!? Keep Reading

Are signals form firm earnings and revenue momentum additive to that from stock price momentum? In their March 2010 paper entitled “Price, Earnings, and Revenue Momentum Strategies”, Hong-Yi Chen, Sheng-Syan Chen, Chin-Wen Hsin and Cheng-Few Lee examine the profitability and of a revenue momentum strategy, both standalone and in combination with price and earnings momentum strategies. They measure price momentum based on past stock returns, and earnings and revenue momentums with respect to historical earnings and revenues (not surprises relative to analyst forecasts). Using stock return, earnings and revenue data for a broad sample of U.S. stocks spanning 1974-2007, they conclude that: Keep Reading

A reader commented and asked: “I am interested in Mebane Faber’s 10-month SMA timing strategy, as it seems to match the market with less risk and outperform other moving average strategies I’ve seen. Based on the results of ‘Is There a Best SMA Calculation Interval for Long-term Crossing Signals?’, it seems that Faber’s strategy is not brittle as far as choosing an 8-, 10-, 12- or 14-month SMA. However, what if I were to trade on a day other than the end of the month? Would I get drastically different results? If so, that might suggest that Faber’s choice of day is ‘data mining’ and the performance of his strategy may not persist.” Keep Reading