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

Joseph Chen, Harrison Hong and Jeremy Stein

No 7687, NBER Working Papers from National Bureau of Economic Research, Inc

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.

JEL-codes: G12 G14 (search for similar items in EconPapers)
Date: 2000-05
New Economics Papers: this item is included in nep-fin and nep-fmk
Note: AP CF
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Citations: View citations in EconPapers (30)

Published as 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.

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Journal Article: Forecasting crashes: trading volume, past returns, and conditional skewness in stock prices (2001)
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