Stock Return Autocorrelations and Predictability in the Chinese Stock Market: Evidence from Threshold Quantile Autoregressive Models

Wen-Jun Xue () and Li-Wen Zhang
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Wen-Jun Xue: Department of Economics, Florida International University
Li-Wen Zhang: School of Economics, Shanghai University, China

No 1605, Working Papers from Florida International University, Department of Economics

Abstract: 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.

Keywords: Stock return autocorrelations; Predictability; Chinese stock market; Threshold quantile autoregressive model (search for similar items in EconPapers)
JEL-codes: C23 G12 G14 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2016-10
New Economics Papers: this item is included in nep-tra
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https://economics.fiu.edu/research/pdfs/2016_working_papers/1605.pdf First version, 2016 (application/pdf)

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