Information Demand and Stock Return Predictability

Forthcoming, Journal of International Money and Finance

33 Pages Posted: 29 Jan 2015 Last revised: 4 Nov 2017

See all articles by Dimitris K. Chronopoulos

Dimitris K. Chronopoulos

University of St. Andrews - School of Management

Fotios I. Papadimitriou

Business School, University of Aberdeen

Nikolaos Vlastakis

Essex Business School, University of Essex

Date Written: January 27, 2015

Abstract

Recent theoretical work suggests that signs of asset returns are predictable given that their volatilities are. This is the first paper to investigate whether the demand for information, approximated by the daily internet search volume index (SVI) from Google, can enhance volatility forecasts out-of-sample and subsequently induce better sign predictability of the S&P 500 daily returns. Our results reveal that the inclusion of the SVI variable in a number of GARCH family models leads to significantly better volatility forecasts in all cases. Moreover, we demonstrate that the sign of stock returns is predictable in contrast to return predictability in the levels which has previously proven difficult to detect in the US context. Finally, we provide novel evidence on the economic value of sign predictability and show that the SVI can help investors to form profitable investment strategies.

Keywords: Return sign predictability, Information demand, Volatility, Economic value

JEL Classification: G11, G14, G17

Suggested Citation

Chronopoulos, Dimitris K. and Papadimitriou, Fotios I. and Vlastakis, Nikolaos, Information Demand and Stock Return Predictability (January 27, 2015). Forthcoming, Journal of International Money and Finance. Available at SSRN: https://ssrn.com/abstract=2556179 or http://dx.doi.org/10.2139/ssrn.2556179

Dimitris K. Chronopoulos

University of St. Andrews - School of Management ( email )

The Gateway
North Haugh
St. Andrews, Fife, Scotland KY16 9SS
United Kingdom

Fotios I. Papadimitriou (Contact Author)

Business School, University of Aberdeen ( email )

Dunbar Street
Aberdeen, Scotland AB24 3QY
United Kingdom

Nikolaos Vlastakis

Essex Business School, University of Essex ( email )

Wivenhoe Park
Colchester, CO4 3SQ
United Kingdom

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