Size Effect

In their March 2011 paper entitled “The Shrinking Space for Anomalies”, George Jiang and Andrew Zhang investigate the robustness of ten well-known anomalies by iteratively “shrinking the stock space” in two ways to determine whether and how the anomalies really work. The ten anomaly variables are: size, book-to-market ratio, momentum, two liquidity measures, idiosyncratic volatility, accrual, capital expenditure, sales growth and net share issuance. The first way of “shrinking the stock space” involves: (1) ranking the universe of stocks by each of the ten anomaly variables into deciles; (2) iteratively trimming deciles from side of a variable distribution that a hedge portfolio would sell and the side that a hedge portfolio would buy; and, (3) retesting the strength of the anomaly associated with the variable after each iterative trimming. The second way of “shrinking the stock space” involves: (1) trimming from the sample stocks with the smallest market capitalizations and the most extreme book-to-market ratios until size, book-to-market and momentum no longer have significant four-factor alphas for value-weighting and equal equal-weighting (thereby “perfecting” the sample for the four-factor model); and, (2) retesting the strength of the anomalies associated with the other seven variables using the perfected sample. This approach obviates weaknesses in alpha measurement via the commonly applied but imperfect three-factor (market, size, book-to-market) and four-factor (plus momentum) risk models. Using firm characteristics and trading data for all non-financial NYSE, AMEX, and NASDAQ common stocks over the period July 1962 through December 2007, they find that: Keep Reading

How do widely recognized stock return anomalies (return variations unexplained by asset pricing models) mesh with efficient portfolio selection theory? In their paper entitled “Investing in Stock Market Anomalies”, Turan Bali, Stephen Brown and Ozgur Demirtas examine five prominent stock market anomalies whose existence is robust through time and across markets (size, book-to-market, short-term reversal, intermediate-term momentum and long-term reversion) in contexts of efficient portfolio selection via mean-variance and stochastic dominance methods. In other words, they test whether portfolios that apply these anomalies exhibit exceptionally good combinations of return and volatility, or obviously outperform on a purely statistical basis. Both these portfolio selection methods have shortcomings related to their inclusion of extreme, impractical choices. The authors consider relaxed (“Almost”) versions of these methods that prohibit such choices as “pathological.” The authors form value-weighted size and book-to-market portfolios annually and value-weighted reversal, momentum and reversion portfolios monthly. Using monthly data for July 1926 through December 2008 (990 months) for a broad sample of U.S. stocks to construct diversified anomaly portfolios, they find that: Keep Reading

Which firm fundamentals predict associated stocks returns, and which ones do not? In their February 2011 paper entitled “Returns Premia on Company Fundamentals”, Kateryna Shapovalova, Alexander Subbotin and Thierry Chauveau assess the significance, stability and interplay of excess returns for individual stocks as predicted by widely used firm fundamentals. Specifically, they consider: book-to-price ratio; earnings-to-price ratio; sales-to-price ratio; cash flow-to-price ratio; dividend yield; market capitalization; growth in sales per share over the past one, three and five years; growth in earnings per share over the past one, three and five years; forecasted growth of earnings per share next year; forecasted long-term growth in earnings per share; forecasted earnings-to-price ratio; five-year average reinvested fraction of return on equity (internal growth); and, for control purposes, past returns over one, three and 12 months. Their methodology is direct stock-by-stock rather than portfolio-mediated, with the values of fundamentals across stocks normalized to a range of zero to one. They impose a three-month lag for accounting data to ensure public availability. Using monthly/quarterly firm fundamentals and monthly total stock returns for 9,363 NYSE-listed firms during 1979 through 2008, they find that: Keep Reading

How and why do the value premium and size effect work? In their February 2011 paper entitled “Value and Size Puzzles: A Commented Survey”, Kateryna Shapovalova and Alexander Subbotin review and assess prior research on the value premium and size effect, which play key roles in the most widely use factor models of stock prices. Based on the body of research, they conclude that: Keep Reading

A reader noted and asked: “I have seen on the net that it is better to be in large capitalization stocks when the Federal Funds Rate (FFR) target is increasing and small capitalization stocks when the FFR target is decreasing. Is there any serious study about this belief?” An argument supporting this proposition is that investors view small firms as more sensitive to changes in interest rates than large firms. Using FFR target actions and daily closes of the S&P 500 Index (representing large firms) and the Russell 2000 Index (representing small firms) for January 1990 through December 2010, we find that: Keep Reading

Do stocks trading on Over-the-Counter (OTC) markets, generally off limits for institutional traders, present in aggregate a good opportunity for individual investors? In their December 2010 paper entitled “Do Investors Overpay for Stocks with Lottery-Like Payoffs? An Examination of the Returns on OTC Stocks”, Bjørn Eraker and Mark Ready examine returns on U.S. OTC Bulletin Board and Pink Sheet stocks. Using stock price and firm data for 11,260 OTC companies (about a third of which were once listed) over the period 2000 through 2008, they find that: Keep Reading

Does the relatively illiquid, opaque, retail environment of over-the-counter (OTC) stocks make them behave differently from comparable listed stocks? In their November 2010 paper entitled “The Cross Section of Over-the-Counter Equities”, Andrew Ang, Assaf Shtauber and Paul Tetlock test the abilities of market capitalization, book-to-market ratio, liquidity, return momentum and idiosyncratic volatility to predict OTC stock returns and compare results to those for listed stocks with comparable market capitalizations. As a part of the study, they examine hedge portfolios that are long/short extreme fifths of OTC stocks ranked by these characteristics to estimate of the magnitudes of the respective  premiums. Using trading volumes, market capitalizations, book-to-market ratios (as available) and closing, bid and ask prices for a large sample of OTC-only firms with at least one Financial Industry Regulatory Authority market maker, and for comparable listed firms, during 1975 through 2008, they find that: Keep Reading

Is the size effect broad and dependable, or narrow and erratic (even gone)? In the November 2010 version of his paper entitled “A Literature Review of the Size Effect”, Michael Crain summarizes past research on the size effect in equity returns, with size measured conventionally as market capitalization. Surveying the major papers on this anomaly, he finds that: Keep Reading

Market capitalization is the most frequently used metric for weighting the individual stock components of market indexes. Other approaches range from equal weighting to weighting on firm fundamentals to weighting generated by return-risk optimization. How do such alternative metrics work empirically? In the October 2010 draft of their paper entitled “A Survey of Alternative Equity Index Strategies”, Tzee-man Chow, Jason Hsu, Vitali Kalesnik and Bryce Little examine several popular passive index weighting alternatives to market capitalization. They impose common assumptions to backtest these alternatives on U.S. and global equity data over long periods with either annual or quarterly rebalancing. They also apply the Fama-French three-factor model to investigate sources of outperformance relative to capitalization-weighted benchmarks. Using stock/firm data for the 1,000 largest global firms spanning 1987-2009 and for the largest 1,000 U.S. firms spanning 1964-2009, they find that: Keep Reading

Studies of the U.S. stock market indicate that some factors and indicators may have predictive power for future returns. Do these findings consistently translate to other large equity markets? In the July 2010 version of their paper entitled “The Cross-Section of German Stock Returns: New Data and New Evidence”, Sabine Artmann, Philipp Finter, Alexander Kempf, Stefan Koch and Erik Theissen apply a new set of single-sorted and double-sorted factor portfolios based on market beta, size, book-to-market ratio and momentum to test for beta effect, size effect, value premium and momentum in the German equity market. In the July 2010 version of their paper entitled “The Impact of Investor Sentiment on the German Stock Market”, Philipp Finter, Alexandra Niessen-Ruenzi and Stefan Ruenzi test the predictive power of a composite sentiment measure combining consumer confidence, net equity mutual funds flow, put-call ratio, aggregate trading volume, initial public offering (IPO) returns, number of IPOs and aggregate equity-to-debt ratio of new issues. Using data for 955 non-financial German firms for which sufficient data is available during the period 1960-2006 for the factor portfolios and 1993-2006 for the sentiment measure, these studies find that: Keep Reading