Can Internet Search Queries Help to Predict Stock Market Volatility?

Paris December 2012 Finance Meeting EUROFIDAI-AFFI Paper

European Financial Management, Forthcoming

34 Pages Posted: 10 Oct 2011 Last revised: 7 Jan 2016

Thomas Dimpfl

University of Tuebingen - Department of Statistics and Econometrics

Stephan Jank

Deutsche Bundesbank; University of Cologne - Centre for Financial Research (CFR)

Multiple version iconThere are 2 versions of this paper

Date Written: June 6, 2012

Abstract

This paper studies the dynamics of stock market volatility and retail investors' attention to the stock market, where attention to the stock market is measured by internet search queries related to the leading stock market index. We find a strong co-movement of the Dow Jones' realized volatility and the volume of search queries for its name. Furthermore, search queries Granger cause volatility: a heightened number of searches today is followed by an increase in volatility tomorrow. We utilize this finding to improve several models of realized volatility. Including search queries in autoregressive models of realized volatility helps to improve volatility forecasts in-sample and out-of-sample as well as for different forecasting horizons. Search queries are particularly useful in high-volatility phases when a precise prediction is vital.

Keywords: realized volatility, forecasting, investor behavior, limited attention, noise trader, search engine data

JEL Classification: G10, G14, G17

Suggested Citation

Dimpfl, Thomas and Jank, Stephan, Can Internet Search Queries Help to Predict Stock Market Volatility? (June 6, 2012). Paris December 2012 Finance Meeting EUROFIDAI-AFFI Paper. Available at SSRN: https://ssrn.com/abstract=1941680 or http://dx.doi.org/10.2139/ssrn.1941680

Thomas Dimpfl

University of Tuebingen - Department of Statistics and Econometrics ( email )

Germany

Stephan Jank (Contact Author)

Deutsche Bundesbank ( email )

Wilhelm-Epstein-Str. 14
D-60431 Frankfurt/Main
Germany

University of Cologne - Centre for Financial Research (CFR) ( email )

Albertus-Magnus Platz
Cologne, 50923
Germany

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