Information Demand and Stock Return Predictability

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