Forecasting the Size Effect

44 Pages Posted: 6 Oct 2016 Last revised: 11 Jun 2020

See all articles by Bruce I. Jacobs, Ph.D.

Bruce I. Jacobs, Ph.D.

Jacobs Levy Equity Management

Kenneth N. Levy

Jacobs Levy Equity Management

Date Written: October 12, 1988

Abstract

It has been known for some time that the returns of small firms often differ from those of large firms, and that asset pricing theories, including the Capital Asset Pricing Model and Arbitrage Pricing Theory, cannot account for the difference. Small-capitalization stocks have provided higher average returns than large-capitalization stocks, and the out-performance has been strongest in the month of January. Various researchers have sought to explain this size effect as the result of differential transaction costs, liquidity, informational uncertainty and year-end tax-loss selling. Others have suggested that small stocks outperform because they tend to have lower P/E ratios.

A multifactor analysis "disentangles" the effect of firm size from related factors that may influence return. These factors include cross-sectional effects, such as firm neglect and low P/E, and calendar effects, such as tax-loss selling. Disentangling provides "pure" returns to size that avoid the confounding associated with proxy effects. For instance, disentangling reveals the January small-firm seasonal to be a mere surrogate for the rebound that follows the abatement of tax-loss selling.

An analysis of pure returns reveals that the size effect is buffeted by economic forces. There are times when small stocks outperform the market, and other times when they lag. But while the payoffs to the size effect are not at all regular to the naked eye, they are predictable in a broader empirical framework that incorporates macroeconomic drivers such as interest rates and industrial production. An examination of various forecasting models, including univariate and multivariate time-series techniques, indicates that one that imposes a Bayesian random-walk prior belief on the coefficients of a vector autoregressive model provides the best results.

Keywords: Forecasting Models, Size Effect, Small-Cap Stocks, Forecasting Equity Returns, Return Regularities, Macroeconomic Drivers, Disentangling, Pure Returns, Multivariate Regression, January Effect, Tax-Loss Selling, Market Efficiency

JEL Classification: G14

Suggested Citation

Jacobs, Bruce I. and Levy, Kenneth N., Forecasting the Size Effect (October 12, 1988). Financial Analysts Journal, Vol. 45, No. 3, pp. 38-54, May/June 1989, Available at SSRN: https://ssrn.com/abstract=1621841

Bruce I. Jacobs (Contact Author)

Jacobs Levy Equity Management ( email )

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P.O. Box 650
Florham Park, NJ 07932-0650
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973-410-9222 (Phone)
973-410-9333 (Fax)

HOME PAGE: https://jlem.com/who-we-are#/nav/founders

Kenneth N. Levy

Jacobs Levy Equity Management ( email )

100 Campus Drive
P.O. Box 650
Florham Park, NJ 07932-0650
United States
973-410-9222 (Phone)
973-410-9333 (Fax)

HOME PAGE: https://jlem.com/who-we-are#/nav/founders

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