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

Joseph Chen, Harrison Hong, Jeremy C. Stein

NBER Working Paper No. 7687
Issued in May 2000
NBER Program(s):The Asset Pricing Program, The Corporate Finance Program

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.

Machine-readable bibliographic record - MARC, RIS, BibTeX

Document Object Identifier (DOI): 10.3386/w7687

Published: Chen, Joseph, Harrison Hong and Jeremy C. Stein. "Forecasting Crashes: Trading Volume, Past Returns, And Conditional Shewness In Stock Prices," Journal of Financial Economics, 2001, v61(3,Sep), 345-381. citation courtesy of

Users who downloaded this paper also downloaded* these: