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Predicting stock market crises using daily stock market valuation and investor sentiment indicators

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  • Fu, Junhui
  • Zhou, Qingling
  • Liu, Yufang
  • Wu, Xiang

Abstract

The purpose of this paper is to develop a daily early warning system for stock market crises using daily stock market valuation and investor sentiment indicators. To achieve this goal, we use principal components analysis to propose a comprehensive index of daily market indicators that reflects stock market valuation and investor sentiment. Based on the comprehensive index, we employ a logit model with Ensemble Empirical Mode Decomposition to develop a daily early warning system for stock market crises. Finally, we apply the proposed system to the early warning for stock market crises in China. The in-sample forecasting results show that investor sentiment and the forecast horizon by Ensemble Empirical Mode Decomposition improve the forecasting performance of conventional early warning systems. The out-of-sample forecasting results indicate that the proposed warning system still has a good performance.

Suggested Citation

  • Fu, Junhui & Zhou, Qingling & Liu, Yufang & Wu, Xiang, 2020. "Predicting stock market crises using daily stock market valuation and investor sentiment indicators," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    • Handle: RePEc:eee:ecofin:v:51:y:2020:i:c:s1062940818304108
    DOI: 10.1016/j.najef.2019.01.002
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    2. Adnan Abo Al Haija & Rahma Lahyani, 2023. "Dynamic interactions of actual stock returns with forecasted stock returns and investors’ risk aversion: empirical evidence interplaying the impact of Covid-19 pandemic," Review of Quantitative Finance and Accounting, Springer, vol. 61(3), pages 1129-1149, October.
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