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Size Effect

Do the stocks of small firms consistently outperform those of larger companies? If so, why, and can investors/traders exploit this tendency? These blog entries relate to the size effect.

Equity Investing Based on Liquidity

Does the variation of individual stock returns with liquidity support an investment style? In the January 2014 update of their paper entitled “Liquidity as an Investment Style”, Roger Ibbotson and Daniel Kim examine the viability and distinctiveness of a liquidity investment style and investigate the portfolio-level performance of liquidity in combination with size, value and momentum styles. They define liquidity as annual turnover, number of shares traded divided by number of shares outstanding. They hypothesize that stocks with relatively low (high) turnover tend to be near the bottom (top) of their ranges of expectation. Their liquidity style thus overweights (underweights) stocks with low (high) annual turnover. They define size, value and momentum based on market capitalization, earnings-to-price ratio (E/P) and past 12-month return, respectively. They reform test portfolios via annual sorts into four ranks (quartiles), with initial equal weights and one-year holding intervals. Using monthly data for the 3,500 U.S. stocks with the largest market capitalizations (re-selected each year) over the period 1971 through 2013, they find that: Keep Reading

Stock Markets Have Value and Size, Too?

Do country stock markets exhibit useful aggregate value and size metrics? In his December 2013 paper entitled “Macro Model for Macro Funds”, Adam Zaremba investigates whether macro size and value factors for country stock markets predict country stock index returns. Specifically, he calculates size and value factors at the country level in each of 66 countries. The size factor is the market capitalization of all listed firms in a country index. The value factor is the book-to-market value ratio (B/M) of all firms in a country index aggregated according to the index weighting methodology. He uses both MSCI country indexes and extant local country indexes to measure country market returns. He tests relationships between country-level size and value factors and future returns by each month separately constructing portfolios of the equally weighted top 30%, middle 40% and bottom 30% of country markets based on aggregate size and value factors. He also measures the performance of fully collateralized portfolios that are each month long (short) the equally weighted top (bottom) 30% of country markets based on aggregate size and value factors separately. To test sensitivity to the currency used, he performs all calculations separately in U.S. dollars, euros and yen. Using monthly accounting and return data as specified during June 2000 through November 2013, he finds that: Keep Reading

Value and Momentum Behaviors in Developed Markets

How do value and momentum interact with each other and with size, economic and liquidity factors worldwide? In the November 2013 version of their paper entitled “Size, Value, and Momentum in Developed Country Equity Returns: Macroeconomic and Liquidity Exposures”, Nusret Cakici and Sinan Tan address this question for developed markets. They use long-short, factor-sorted portfolios to measure size, value and momentum premiums. They consider future Gross Domestic Product (GDP) growth and future consumption growth as economic factors. They consider both funding liquidity (a potential indicator of investor margin cost, focusing on the difference between interbank lending rate and short-term deposit yield) and stock market liquidity (the estimated cost of trading stocks). Using monthly stock returns, firm accounting data and economic data for 23 developed countries during January 1990 through March 2012, they find that: Keep Reading

Mutual Funds Successfully Exploiting Academic Research?

Can equity funds exploit widely accepted stock return anomalies? In their July 2013 paper entitled “Academic Knowledge Dissemination in the Mutual Fund Industry: Can Mutual Funds Successfully Adopt Factor Investing Strategies?”, Eduard Van Gelderen and Joop Huij investigate whether mutual funds that materially adopt investment strategies based on published asset pricing anomalies consistently outperform the stock market. They first use monthly regressions to measure degrees of use of six factor investing strategies (low-beta, small cap, value, momentum, short-term reversal and long-term reversion) across U.S. equity mutual funds. They then calculate market-adjusted returns to determine whether funds employing the strategies outperform those that do not and the market. Using monthly returns for 6,814 U.S. equity mutual funds, and contemporaneous monthly returns for the specified factors, during 1990 through 2010, they find that: Keep Reading

Profitability as a Fourth Stock Return Forecast Factor

Does adding profitability (see “Gross Profitability as a Stock Return Predictor”) to the Fama-French three-factor model of future stock returns result in a better model? In the June 2013 draft of their paper entitled “A Four-Factor Model for the Size, Value, and Profitability Patterns in Stock Returns”, Eugene Fama and Kenneth French examine whether profitability usefully augments their three-factor model. They consider evidence from monthly double sorts into: (1) size and book-to-market capitalization ratio (B/M) quintiles (25 portfolios); and, (2) size and pre-tax profitability (PTP) quintiles (25 portfolios). They also consider monthly triple sorts by size, B/M and PTP. Using price and firm accounting data for a broad sample of U.S. common stocks during July 1963 through December 2012, they find that: Keep Reading

Accidental Alpha

How can equity weighting strategies and their opposites both outperform the stock market? In the October 2012 version of their paper entitled “The Surprising ‘Alpha’ from Malkiel’s Monkey and Upside-down Strategies”, Rob Arnott, Jason Hsu, Vitali Kalesnik and Phil Tindall challenge beliefs underlying a variety of stock investment strategies that beat a capitalization-weighted benchmark by examining the performance of portfolios based on opposite beliefs. If the original beliefs determine success, then their opposites should underperform. They limit their investigation to long-only stock weightings based on original beliefs and opposites based on inverse weights or complement weights. To ensure portfolio feasibility, they restrict U.S. and global universes to large-capitalization stocks. They reform portfolios at the end of each year. When needed in portfolio construction, they estimate historical parameters (such as volatility) using five years of lagged monthly data. They consider capitalization-weighted, equal-weighted and diversity-weighted benchmarks and use a conventional four-factor (market, size, book-to-market and momentum) model to calculate strategy alphas. They ignore trading frictions. Using monthly returns for the top 1,000 U.S. stocks by market capitalization during 1964 through 2010 and for large-capitalization global stocks during 1991 through 2010, they find that: Keep Reading

Simple Market Capitalization Concentration Trading Strategy

“Market Capitalization Concentration as Stock Market Predictor” summarizes research finding that the change in the level of concentration of total market capitalization in the largest firms may be a useful predictor of stock market returns. Does a simple trading strategy based on this finding beat the market? To investigate, we examine the ratio of the S&P 500 Index (representing large stocks) and the Russell 2000 Index (representing small stocks). When the concentration of total market capitalization in large firms is high (low), this ratio is high (low). In concert with the referenced research, we derive trading signals from the lagged annual change in this index ratio. Using monthly levels of the S&P 500 Index, the Russell 2000 Index and the monthly yield on 13-week Treasury bills (T-bills) from inception of the Russell 2000 Index in September 1987 through September 2012, we find that: Keep Reading

Market Capitalization Concentration as Stock Market Predictor

Do changes in total market capitalization shares of large-capitalization and small-capitalization stocks predict future equity returns? In their September 2012 paper entitled “Davids, Goliaths, and Business Cycles”, Jefferson Duarte and Nishad Kapadia investigate whether a predictor based on concentration of market valuation predicts market returns. Specifically, they test the power of annual change in the logarithm of the fraction of total stock market capitalization captured by the largest 250 firms to predict future stock market returns. They call this indicator Goliaths Versus Davids (GVD). They compare the predictive power of GVD to those of eight other variables: (1) the default spread (difference between BAA and AAA corporate bond yields); (2) the term spread (difference between 10-year Treasury note and the 1-month Treasury bill yields); (3) the stock market dividend-price ratio; (4) the cyclically adjusted price-earnings ratio; (5) the consumption, wealth, income ratio; (6) the investment-to-capital ratio; (7) the book-to-market ratio of the Dow Jones Industrial Average; and, (8) the net payment yield of all stocks. Using quarterly data for a broad sample of U.S. common stocks and U.S. stock market returns during April 1926 through April 2011, they find that: Keep Reading

Common Factor Exposures of Specialized Stock Indexes

How do specialized stock indexes relate to commonly used equity risk factors? In his February 2012 paper entitled “Evaluating Alternative Beta Strategies”, Xiaowei Kang examines risk exposures (betas), construction methodologies and historical performances of alternative stock indexes such as those based on value, low-volatility and diversification strategies. He considers five risk factors: (1) market, representing excess return of the market capitalization-weighted U.S. stock market; (2) size, representing return from a portfolio that is long small-cap stocks and short large-cap stocks; (3) value, representing return from a portfolio that is long high book-to-market stocks and short low book-to-market stocks; (4) momentum, representing return from a portfolio that is long past winning stocks and short past losing stocks; and, (5) volatility, representing return from a portfolio that is long high-volatility stocks and short low-volatility stocks. Using monthly returns for several specialized indexes and the specified risk factors as available through 2011, he finds that: Keep Reading

Growth Investing Success Factors

What is growth investing, and how well does it work? How can investors enhance this investment style? In his July 2012 paper entitled “Growth Investing: Betting on the Future?”, Aswath Damodaran examines different approaches to growth investing: focusing on companies with small market capitalization; playing initial public offerings (IPO); seeking growth at a reasonable price (GARP); and, activist venture capital-like investing. He defines growth investing as pursuit of market undervaluation of future growth, looking for bargains based on overlooked growth potential. Based on the body of growth investing research, he finds that: Keep Reading

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