Non-linearity in stock index returns: the volatility and serial correlation relationship

Abstract

It appears that stock market index returns exhibit (weak) autocorrelation and there is evidence that volatility in equity markets is inversely related to first order autocorrelation. A prominent theory that can address both the aforementioned stylized facts is the feedback trading theory that relates autocorrelation to individual investor trading patterns. We provide a unified framework to simultaneously investigate market wide feedback trading strategies effects and the presence of volatility-correlation relationships. Our empirical application uses market portfolios from six international markets and employs conditional non-linear in mean and in variance models. Parametric specifications for conditional dependence beyond the mean and variance are also modelled following Hansen's (1994) (Hansen, B.E., 1994. Int. Econ. Rev. 35 (a), 705–730) autoregressive conditional density estimation. For the sample period under investigation (post 1990), our results support the presence of feedback traders and an inverse volatility–correlation relationship in three out of six markets while only two of the series under investigation do not provide evidence of autocorrelation. Our empirical work supports volatility induced sign switches in correlation. We document positive and significant risk premium parameters in three markets while we find that volatility at the market level is enhanced by past movements of the daily range (daily high–low price difference) series.