Textual Sentiment, Option Characteristics, and Stock Return Predictability

IRTG 1792 Discussion Paper 2018-023

54 Pages Posted: 30 Jul 2018

See all articles by Cathy Chen

Cathy Chen

Humboldt University of Berlin

Matthias R. Fengler

University of St. Gallen - School of Economics and Political Science

Wolfgang K. Härdle

Humboldt University of Berlin - Institute for Statistics and Econometrics; Xiamen University - Wang Yanan Institute for Studies in Economics (WISE); Charles University; Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Yanchu Liu

Lingnan (University) College, Sun Yat-sen University, Guangzhou, China.

Date Written: July 18, 2018

Abstract

We distill sentiment from a huge assortment of NASDAQ news articles by means of machine learning methods and examine its predictive power in single-stock option markets and equity markets. We provide evidence that single-stock options react to contemporaneous sentiment. Next, examining return predictability, we discover that while option variables indeed predict stock returns, sentiment variables add further informational content. In fact, both in a regression and a trading context, option variables orthogonalized to public and sentimental news are even more informative predictors of stock returns. Distinguishing further between overnight and trading-time news, we find the first to be more informative. From a statistical topic model, we uncover that this is attributable to the differing thematic coverage of the alternate archives. Finally, we show that sentiment disagreement commands a strong positive risk premium above and beyond market volatility and that lagged returns predict future returns in concentrated sentiment environments.

Keywords: investor disagreement; option markets; overnight information; stock return predictability; textual sentiment; topic model; trading-time information

JEL Classification: C58; G12; G14; G41

Suggested Citation

Chen, Cathy and Fengler, Matthias R. and Härdle, Wolfgang K. and Liu, Yanchu, Textual Sentiment, Option Characteristics, and Stock Return Predictability (July 18, 2018). IRTG 1792 Discussion Paper 2018-023 . Available at SSRN: https://ssrn.com/abstract=3210585

Cathy Chen

Humboldt University of Berlin ( email )

Unter den Linden 6
Berlin, AK Berlin 10099
Germany

Matthias R. Fengler

University of St. Gallen - School of Economics and Political Science ( email )

Bodanstrasse 6
CH-9000 St. Gallen, 9000
Switzerland

HOME PAGE: http://www.mathstat.unisg.ch/fengler

Wolfgang K. Härdle (Contact Author)

Humboldt University of Berlin - Institute for Statistics and Econometrics ( email )

Unter den Linden 6
Berlin, D-10099
Germany

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE) ( email )

A 307, Economics Building
Xiamen, Fujian 10246
China

Charles University ( email )

Celetná 13
Dept Math Physics
Praha 1, 116 36
Czech Republic

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Unter den Linden 6
Berlin, D-10099
Germany

Yanchu Liu

Lingnan (University) College, Sun Yat-sen University, Guangzhou, China. ( email )

Haizhu District,
Guangzhou, China.
Guangzhou, Guangdong 510275
China

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