Size Effect

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

Attempting to follow long stock market trends is a common investment approach, with much guru attention focused on calling long-term tops and bottoms. Is this approach meaningful for investors as an avenue to improve upon buy-and-hold performance? In the December 2006 version of his paper entitled “Analyzing Regime Switching in Stock Returns: An Investment Perspective”, Jun Tu investigates the potential importance to investors of exploiting differences between bull and bear markets within a Bayesian framework that accommodates considerable uncertainty. Using monthly value-weighted stock return and volatility data for July 1963 to February 2006 (512 observations), he finds that: Keep Reading

Why do small capitalization stocks as a group tend to outperform the broad market? Do small firms represent relatively high risk of financial distress (with attendant reward), or are they victims of systematic investor overreaction to past poor performance? In the 2006 update of their paper entitled “Can Overreaction Explain Part of the Size Premium?” Ozgur Demirtas and Burak Güner investigate irregularities in the historical returns of small capitalization stocks to identify the source of the size effect. Using returns and financial data for NYSE/Amex/Nasdaq stocks over the period July 1971 through June 2001, they conclude that: Keep Reading

Are there investing/trading strategies that can turn stock price noise into alpha? More specifically, are there types of stocks for which the noise has a systematic effect on price? In the October 2006 draft of their paper entitled “Does Noise Create the Size and Value Effects?”, Robert Arnott, Jason Hsu, Jun Liu and Harry Markowitz model the cross-sectional effects of mean-reverting noise on randomly walking stock values. Noise (for example, from overreacting, informationally challenged and/or liquidity-driven investors/traders) introduces random transients of inefficiency. Based on this model, they conclude that: Keep Reading

Are there diversification and return advantages from getting off the beaten path (to small-capitalization stocks) when diversifying internationally? In their September 2006 paper entitled “International Diversification with Large- and Small-Cap Stocks”, Cheol Eun, Wei Huang and Sandy Lai compare the benefits of using large-capitalization and small-capitalization stocks to diversify across countries. Taking the perspective of a dollar-based investor, they examine diversification across ten countries with open capital markets (Australia, Canada, France, Germany, Hong Kong, Italy, Japan, the Netherlands, the United Kingdom and the United States). Using monthly size and return data for three market capitalization-based funds (large-cap, mid-cap and small-cap) for each country over the period 1980-1999, they conclude that: Keep Reading

If noise is a significant component of stock prices, does a portfolio that favors large market capitalization stocks automatically underperform? In the May 2006 draft of their paper entitled “Pricing Noise, Rejecting the CAPM and the Size and Value Effects”, Robert Arnott and Jason Hsu examine the implications of a very simple model that assumes stock prices deviate from fundamental value based on a single source of unknown risk (noise). They assume the deviations revert to a mean of zero, with no long-term effect on stock returns. Based on this model, they conclude that: Keep Reading

As companies evolve, their characteristics may migrate from one category to another (for example, from small to large, or from growth to value). Does such migration, in aggregate, help explain differences in average returns for different categories of stocks? In the August 2006 draft of their paper entitled “Migration”, Eugene Fama and Kenneth French investigate how migration of firms across categories contributes to the size effect and the value premium. Specifically, at the end of each June from 1926 through 2004 they construct six value-weighted portfolios of stocks from the major U.S. exchanges based on market capitalization and price-to-book ratio. They then examine the effects on portfolio returns of four kinds of annual rebalancing actions: (1) firms that do not move (Same); (2) firms that change size (dSize); (3) firms that improve toward growth, or are acquired (Plus); and, (4) firms that deteriorate toward value, or are delisted (Minus). Using subsequent-year return data for 1927-2005, they conclude that: Keep Reading

Can you trade on the CBOE Volatility Index (VIX), the “investor fear gauge,” or not? If so, what should you trade and should your trades be short-term or long-term? In their September 2005 paper entitled “VIX Signaled Switching for Style-Differential and Size-Differential Short-term Stock Investing”, Dean Leistikow and Susana Yu test the usefulness of VIX level as a signal for short-term switching between: (1) value and growth stock indexes; and, (2) small-capitalization and large-capitalization stock indexes. They note that “…VIX can be viewed as a market-determined forecast of short-term market volatility that, by construction, has a constant one-month forecast horizon.” They determine signals according to whether VIX is high or low compared to its 75-day moving average. They examine index returns for 1 day and 5 days after a VIX signal. Using data for the VIX and for various Standard & Poor’s and Russell stock indexes from the early 1990s through 2004, they find that: Keep Reading

We have selected for retrospective review a few all-time “best selling” research papers of the past few years from the General Financial Markets category of the Social Science Research Network (SSRN). Here we summarize the August 2003 paper entitled “Bad Beta, Good Beta” (download count over 1,700) by John Campbell and Tuomo Vuolteenaho. In this research, the authors separate stock beta into two components, one reflecting news about cash flows and one reflecting news about discount rates. They apply this decomposition to explain the size effect and the value premium. They hypothesize that:

[Market] “value…may fall because investors receive bad news about future cash flows; but it may also fall because investors increase the discount rate…that they apply to these cash flows. In the first case, wealth decreases and investment opportunities are unchanged, while in the second case, wealth decreases but future investment opportunities improve. …[A]n investor may demand a higher premium to hold assets that covary with the market’s cash-flow news than to hold assets that covary with news about the market’s discount rates, for poor returns driven by increases in discount rates are partially compensated by improved prospects for future returns. …The required return on a stock is determined not by its overall beta with the market, but by its bad cash-flow beta and its good discount-rate beta. Of course, the good beta is good not in absolute terms, but in relation to the other type of beta.” [Underlining is ours.]

Using monthly returns from an early period (January 1929 through June 1963) and a modern period (July 1963 through December 2001) to test this idea, the authors conclude that: Keep Reading

Which cheap (high book-to-market value) stocks drive the value premium? Can investors capture the value premium by simply buying a broad index of value stocks, or should they focus on some easily identifiable subset. The paper “Institutional Ownership and the Value Premium” by Ludovic Phalippou from April 2005 evaluates level of institutional ownership as the driver of the value premium, hypothesizing that mispricing of stocks is mostly like to come from unsophisticated individual investors. Using data for 1980-2001, he concludes that: Keep Reading