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A Survey of the Factor Landscape

Many equity market researchers assume conventional three-factor (market return, size, book-to-market) and four-factor (plus momentum) models as standards of comparison for discovery of new sources of abnormal returns. Are they the best standards? Could they be derivatives of more economically fundamental sources of differences among individual stock returns? In their March 2007 paper entitled “Too Many Factors! Do We Need Them All?”, Soosung Hwang and Chensheng Lu seek to identify the minimum number of economically fundamental factors needed to explain why different stocks generate different returns. They investigate 16 factors (12 firm characteristics and four macroeconomic measures) that others have found to explain such return differences. Their principal test is to measure returns from zero-cost portfolios that are long stocks with high (top third) values and short stocks with low (bottom third) values of evaluated factors. Using data for a large sample of non-financial stocks during 1963-2005 and contemporaneous macroeconomic data, they conclude that: Keep Reading

Conservatism Bias in Earnings Forecasts

Do earnings forecasts contain information that investors can exploit to generate abnormal stock returns, or does the market efficiently discount these forecasts? In the November 2006 version of their paper entitled “Forecasted Earnings per Share and the Cross Section of Expected Stock Returns”, Ling Cen, John Wei and Jie Zhang investigate whether stocks with high forecasted earnings per share (FEPS) substantially outperform those with low forecasts, after controlling for commonly used risk factors. Using data for a large sample of NYSE, AMEX and Nasdaq-listed common stocks for the period January 1983 through December 2005 (712,563 stock-month observations), they conclude that: Keep Reading

Investors as Social (Relative Wealth) Climbers

Are investors/traders motivated primarily by absolute wealth or relative wealth? Is outperforming peers a strong motivation? In the February 2007 draft of his paper entitled “Why Risk is Not Related to Return”, Eric Falkenstein examines evidence for and implications of relative wealth as the principal motivator of investors. Using a wide range of examples, he argues that: Keep Reading

Does Earnings Acceleration Mean Anything for Investors?

How does the second derivative (acceleration) of earnings relate to stock returns? In their March 2007 paper entitled “Does Earnings Acceleration Convey Information?”, Ying Cao, Linda Myers and Theodore Sougiannis investigate how the change in earnings growth rate (earnings acceleration) relates to stock returns. They examine separately conditions in which earnings growth rate and earnings acceleration have the same and opposite signs. Using a large sample of U.S. non-financial and non-utility firms over the period 1965 to 2002 (66,150 firm-year observations), they conclude that: Keep Reading

A 12-Month Cycle for Stock Returns?

Do stocks have annual rhythms beyond the January effect? In their March 2007 paper entitled “Common Patterns of Predictability in the Cross-Section of International Stock Returns”, Steven Heston and Ronnie Sadka investigate cyclic patterns of return predictability for stocks in Canada, Japan and twelve European countries (chosen based on the number of firms available for analysis). Using monthly returns over the period January 1985 through June 2006 (258 months), they conclude that: Keep Reading

The Size Effect in Up and Down Markets

Does the size effect, the tendency of small capitalization stocks to outperform, hold in both advancing and declining markets? In their March 2007 paper entitled “Stock Market Returns and Size Premium”, Jungshik Hur and Vivek Sharma explore how the size premium differs when the overall stock market is moving up and down. Using monthly return data for a sample of NYSE/AMEX stocks for July 1931 through December 2004 and NASDAQ stocks for June 1975 through December 2004, they conclude that: Keep Reading

Why Gurus Go to Extremes

Are stock market forecasters prone to hyperbole? Is there logic to predicting plunges and melt-ups at probabilities unjustified by rigorous empirical analysis? In their February 2007 paper entitled “Probability Elicitation, Scoring Rules, and Competition among Forecasters”, Kenneth Lichtendahl, Jr. and Robert Winkler apply game theory to model the behavior of forecasters who pit themselves not only against the data, but also against each other. In other words, they examine the logical behavior of a forecaster whose reward depends not only on own accuracy but also on the accuracies of competing forecasters. When forecasters compete, they conclude that: Keep Reading

Testing Benjamin Graham Out of Sample

Does old-fashioned value investing still work? In their recent paper entitled “Testing Benjamin Graham’s Net Current Asset Value Strategy”, Ying Xiao and Glen Arnold test Benjamin Graham’s approach to valuation based on net current asset value to market value (NCAV/MV) to see whether it outperforms in a modern market environment. NCAV is current assets minus all current and long-term liabilities, divided by the number of shares outstanding. The strategy assumes that a stock is substantially undervalued when NCAV/MV is 1.5 or greater. Using accounting and return data for stocks listed on the London Stock Exchange during 1980-2005, they find that: Keep Reading

Shark Attacks?

Do some short sellers employ sharp intraday attacks on targeted stocks to trigger temporary plunges, during which they cover at a profit? In the March 2007 draft of his paper entitled “Predatory Short Selling”, Andriy Shkilko examines empirical evidence of such behavior. Using all trades and quotes in Nasdaq-listed stocks during regular trading hours from April 2005 to April 2006, he identifies 1,482 potential predatory attacks and concludes that: Keep Reading

The Ignored-by-the-MSM (Information Risk) Premium?

How does main-stream media (MSM) coverage of companies relate to returns on their stocks? Does coverage reduce risk by disseminating information? In their February 2007 paper entitled “Media Coverage and the Cross-Section of Stock Returns”, Lily Fang and Joel Peress examine how media coverage (Wall Street Journal, New York Times, USA Today and Washington Post) relates to stock returns. Using article counts and other data (on trading, accounting, analyst coverage and ownership) for all NYSE-lilsted companies and 500 randomly selected Nasdaq-listed companies over the period 1993-2002, they find that: Keep Reading

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