Stock Return Predictability and Investor Sentiment: A High-Frequency Perspective

58 Pages Posted: 20 Nov 2015 Last revised: 13 Apr 2016

Licheng Sun

Old Dominion University

Mohammad Najand

Old Dominion University - Finance

Jiancheng Shen

Old Dominion University - Finance

Date Written: April 1, 2016

Abstract

We explore the predictive relation between high-frequency investor sentiment and stock market returns. Our results are based on a proprietary dataset of high-frequency investor sentiment, which is computed based on a comprehensive textual analysis of sources from news wires, internet news sources, and social media. We find substantial evidence that intraday S&P 500 index returns are predictable using lagged half-hour investor sentiment. The predictability is evident based on both in-sample and out-of-sample statistical metrics. We document that this sentiment effect is independent of the intraday momentum effect, which is based on lagged half-hour returns. While the intraday momentum effect only exists in the last half hour, the sentiment effect persists in at least the last two hours of a trading day. From an investment perspective, high-frequency investor sentiment also appears to have significant economic value when evaluated with market timing trading strategies.

Keywords: Intraday, Investor Sentiment, High Frequency, Stock Return Predictability

JEL Classification: G11, G14

Suggested Citation

Sun, Licheng and Najand, Mohammad and Shen, Jiancheng, Stock Return Predictability and Investor Sentiment: A High-Frequency Perspective (April 1, 2016). Available at SSRN: https://ssrn.com/abstract=2692328 or http://dx.doi.org/10.2139/ssrn.2692328

Licheng Sun (Contact Author)

Old Dominion University ( email )

Strome College of Business
Department of Finance
Norfolk, VA 23529-0222
United States

Mohammad Najand

Old Dominion University - Finance ( email )

School of Business and Public Administration
Norfolk, VA 23529-0222
United States
757-683-3509 (Phone)
757-683-5639 (Fax)

Jiancheng Shen

Old Dominion University - Finance ( email )

Norfolk, VA 23529-0222
United States

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