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Forecasting asymmetries in aggregate stock market returns: Evidence from conditional skewness
Authors:C. James Hueng  James B. McDonald
Affiliation:aDepartment of Economics, Western Michigan University, Kalamazoo, MI 49008-5330, United States;bBrigham Young University, United States
Abstract:
This paper provides a time-series test for the Differences-of-Opinion theory proposed by Hong and Stein (2003) [Hong, H., Stein, J.C., 2003. Differences of opinion, short-sales constraints and market crashes. Review of Financial Studies 16, 487–525.] in the aggregate market, thus extending the cross-sectional test of Chen et al. (2001) [Chen, J., Hong, H., Stein, J.C.. 2001. Forecasting crashes: trading volume, past returns and conditional skewness in stock prices. Journal of Financial Economics 61, 345–381.] for this theory across individual stocks. An autoregressive conditional density model with a skewed-t distribution is used to estimate the effects of past trading volume on return asymmetry. Using NYSE and AMEX data from 1962 to 2000, we find that the prediction of the Hong–Stein model that negative skewness will be most pronounced under high trading volume conditions is not supported in our time-series analysis with market data.
Keywords:Differences of opinion   Asymmetry   Skewed-t distribution   Autoregressive conditional density models
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