Forecasting Crashes: Trading Volume, Past Returns and Conditional Skewness in Stock Prices

49 Pages Posted: 16 May 2000 Last revised: 2 Jan 2023

See all articles by Joseph Chen

Joseph Chen

University of California, Davis - Graduate School of Management

Harrison G. Hong

Columbia University, Graduate School of Arts and Sciences, Department of Economics; National Bureau of Economic Research (NBER)

Jeremy C. Stein

Harvard University - Department of Economics; National Bureau of Economic Research (NBER)

Multiple version iconThere are 2 versions of this paper

Date Written: May 2000

Abstract

This paper is an investigation into the determinants of asymmetries in stock returns. We develop a series of cross-sectional regression specifications which attempt to forecast skewness in the daily returns of individual stocks. Negative skewness is most pronounced in stocks that have experienced: 1) an increase in trading volume relative to trend over the prior six months; and 2) positive returns over the prior thirty-six months. The first finding is consistent with the model of Hong and Stein (1999), which predicts that negative asymmetries are more likely to occur when there are large differences of opinion among investors. The latter finding fits with a number of theories, most notably Blanchard and Watson's (1982) rendition of stock-price bubbles. Analogous results also obtain when we attempt to forecast the skewness of the aggregate stock market, though our statistical power in this case is limited.

Suggested Citation

Chen, Joseph S. and Hong, Harrison G. and Stein, Jeremy C., Forecasting Crashes: Trading Volume, Past Returns and Conditional Skewness in Stock Prices (May 2000). NBER Working Paper No. w7687, Available at SSRN: https://ssrn.com/abstract=228160

Joseph S. Chen (Contact Author)

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Harrison G. Hong

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