title={Asymmetric Return and Volatility Responses to Composite News from Stock Markets},
author={Thomas Chiang and Cathy Chen and Mike So},
journal={Multinational Finance Journal},
publisher={Multinational Finance Society; Global Business Publications},
keywords={asymmetry; threshold GARCH; volatility; Bayesian estimation; posterior-odds ratio},
abstract={This paper examines the hypothesis that both stock returns and volatility are asymmetric functions of past information derived from domestic and U.S. stock-market news. The results show the presence of negative autocorrelation, which is consistent with the dominance of positive-feedback trading behavior. By employing a double-threshold autoregressive GARCH model to investigate four major index-return series, the study finds significant evidence to sustain the asymmetric hypothesis of stock returns. Specifically, this paper finds that negative news will cause a decline in national stock returns that is larger than the gain caused by good news of an equivalent magnitude. This also holds true for the conditional variance. The return appears to be more volatile and persistent when bad news hits the market than when good news does..},