Sentiment-Driven Stochastic Volatility Model: A High-Frequency Textual Tool for Economists

29 Pages Posted: 13 Jun 2019

See all articles by Jozef Baruník

Jozef Baruník

Charles University in Prague - Department of Economics; Institute of Information Theory and Automation, Prague

Cathy Yi‐Hsuan Chen

University of Glasgow, Adam Smith Business School; Humboldt Universität zu Berlin

Jan Vecer

Charles University in Prague - Faculty of Mathematics and Physics

Date Written: May 31, 2019

Abstract

We propose how to quantify high-frequency market sentiment using high-frequency news from NASDAQ news platform and support vector machine classifiers. News arrive at markets randomly and the resulting news sentiment behaves like a stochastic process. To characterize the joint evolution of sentiment, price, and volatility, we introduce a unified continuous-time sentiment-driven stochastic volatility model. We provide closed-form formulas for moments of the volatility and news sentiment processes and study the news impact. Further, we implement a simulation-based method to calibrate the parameters. Empirically, we document that news sentiment raises the threshold of volatility reversion, sustaining high market volatility.

Keywords: High frequency text, Sentiment, Stochastic volatility, Continuous time models

JEL Classification: G12, C14, C51, C58, G4

Suggested Citation

Barunik, Jozef and Chen, Cathy Yi‐Hsuan and Vecer, Jan, Sentiment-Driven Stochastic Volatility Model: A High-Frequency Textual Tool for Economists (May 31, 2019). Available at SSRN: https://ssrn.com/abstract=3397314 or http://dx.doi.org/10.2139/ssrn.3397314

Jozef Barunik (Contact Author)

Charles University in Prague - Department of Economics ( email )

Opletalova 26
Prague 1, 110 00
Czech Republic

HOME PAGE: http://ies.fsv.cuni.cz/en/staff/barunik

Institute of Information Theory and Automation, Prague ( email )

Pod vodarenskou vezi 4
CZ-18208 Praha 8
Czech Republic

HOME PAGE: http://staff.utia.cas.cz/barunik/home.htm

Cathy Yi‐Hsuan Chen

University of Glasgow, Adam Smith Business School ( email )

University Avenue
Glasgow, G12 8QQ
United Kingdom
01413305065 (Phone)

HOME PAGE: http://https://gla.cathychen.info

Humboldt Universität zu Berlin ( email )

Unter den Linden 6,
Berlin, 10117
Germany
03020935631 (Phone)
10099 (Fax)

Jan Vecer

Charles University in Prague - Faculty of Mathematics and Physics ( email )

Sokolovska 83
Prague, 186 75
Czech Republic

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