Stock return autocorrelations and predictability in the Chinese stock market-Evidence from threshold quantile autoregressive models

•We apply the threshold quantile autoregressive model to study the stock return autocorrelations and predictability in the Chinese stock market.•We employ the data from the stock index and individual stocks to study return autocorrelations and find significant return autocorrelations and predictability.•We also use some stock characteristics as exogenous threshold variables to investigate return autocorrelations.•This paper reveals the autocorrelations, dynamic patterns, predictability of stock returns in the Chinese stock market.

This paper applies the threshold quantile autoregressive model to study stock return autocorrelations and predictability in the Chinese stock market from 2005 to 2014. The results show that the Shanghai A-share stock index has significant negative autocorrelations in the lower regime and has significant positive autocorrelations in the higher regime. It attributes that Chinese investors overreact and underreact in two different states. These results are similar when we employ individual stocks. Besides, we investigate stock return autocorrelations by different stock characteristics, including liquidity, volatility, market to book ratio and investor sentiment. The results show autocorrelations are significantly large in the middle and higher regimes of market to book ratio and volatility. Psychological biases can result into return autocorrelations by using investor sentiment proxy since autocorrelations are significantly larger in the middle and higher regime of investor sentiment. The empirical results show that predictability exists in the Chinese stock market.