Momentum Investing

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

Various studies find that returns on individual stocks exhibit tendencies for short-term (one month) reversal, medium-term (3-12 months) momentum and long-term (2-5 years) reversal. The short-term reversal is the basis for the skip-month included in some medium-term momentum strategies. Is there a way to concentrate the short-term reversal? In the March 2010 update of their draft paper entitled “Industries and Stock Return Reversals”, Allaudeen Hameed, Joshua Huang and Mujtaba Mian examine monthly return reversal using stocks grouped into 24 industries, reasoning that such groups share common sources of return correlations. Using return, industry and characteristics data for a broad sample of NYSE/AMEX stocks spanning 1963-2006, they conclude that: Keep Reading

Does positive feedback trading, indicated by an adjusted measure of return autocorrelation, enhance momentum profitability? In the February 2010 version of their paper entitled “Positive Feedback Trading Activities and Momentum Profits” [apparently removed from SSRN, thus casting doubt on its credibility], Thomas Chiang, Xiaoli Liang and Jian Shi examine the relationship between positive feedback trading and profitability of momentum strategies. The momentum parameters for their investigation are a six-month ranking interval followed by a six-month holding interval. Measurement of positive feedback trading is for a six-month window coinciding with the momentum ranking interval. Using daily stock return data for a broad sample of U.S. stocks spanning 1985-2005, they conclude that: Keep Reading

A reader asked whether Lussenheide Capital Management’s momentum timing mechanism (100-day NASDAQ Composite Index moving average crossings, with proprietary filter) beats buy and hold over the long run, noting that the company’s web site presents at “Trend Following Performance” an independently validated annualized return of over 16% for “a very simple trend following system.” The discussion of performance states: “The systems used here at…Lussenheide Capital Management Inc., uses [sic] this basic system, along with a mechanical, proprietary trading filter. Although our returns are comparable or better with those shown below, our system has more desirable characteristics, including fewer trades and less whipsaws amongst others.” The notes at the bottom of the performance table state that results exclude “fund expenses” and “advisory management fees.” Without the specifications for the proprietary filter, we can test only basic concepts directly. Using daily closes of the NASDAQ Composite Index and daily dividend-adjusted closes for various potential trading vehicles through 2/12/10, we find that: Keep Reading

A reader asked: “Have you done any backtesting to compare value investing versus market timing? Magic Formula Investing seems to rank #1 in value investing and Decision Moose seems to stand out for market timing. Is there any direct comparison between Magic Formula Investing vs. Decision Moose?” Keep Reading

A reader asked: “If you have some thoughts on the claims in the article ‘The Capitalism Distribution’ by Blackstar Funds, LLC, I would be most interested in hearing them.” Keep Reading

A reader requested a review of the TimingCube market timing advisory service, which relies “on the Trend Timing Model to detect major trend changes in the broad market and to issue clear, definitive Buy and Sell signals, on average three to five times per year.” The offeror provides a history of “all ‘live’ TimingCube signals since June 18, 2001.” Using this record of 36 signals, daily S&P Depository Receipts (SPY) closes adjusted for dividends over the period 6/17/01 through 12/16/09 and daily closes of the S&P 500 Index over the period 8/30/00 through 12/16/09, we find that: Keep Reading

A reader commented and requested: “I got a lot of ideas from Michael Carr’s recently published Smarter Investing in Any Economy, which focuses on momentum investing. One idea that the author demonstrated works well, and which I don’t recall having been discussed on your web site, is that one can greatly reduce drawdowns in momentum investing, with little impact to returns, by accounting for volatility when determining Relative Strength. For example, defining a low-volatility Relative Strength as the six month return divided by the standard deviation seems to give a much better risk-adjusted reward than Relative Strength alone. If you read the book some time, I’d be interesting in your views on this. The author seems very diligent in thorough, professional testing (good sample sizes, out-of-sample verification, etc).” Keep Reading

Typically, value means unexciting low-beta stocks, and momentum means exciting high-beta stocks. Does “typically” mean always? In their September 2009 paper entitled “The Changing Beta of Value and Momentum Stocks”, Andrea Au and Robert Shapiro investigate the relationships between beta and value and between beta and momentum under varying stock market conditions. Using monthly beta distributions for value (based on book-to-market ratio) and momentum (based on prior 12-month return) sorts of the Russell 3000 stocks over the period December 1978 through March 2009, they conclude that: Keep Reading