Information Demand and Stock Market Volatility

Abstract

We study information demand and supply at the firm and market level using data for 30 of the largest stocks traded on NYSE and NASDAQ. Demand is approximated in a novel manner on the basis of weekly internet search volume time series drawn from the recently released Google Trends database. Supply of information is represented using data from the Reuters NewsScope Archive. Our paper makes contributions in four main directions. First, we shed light on the empirical behavior of demand and supply for idiosyncratic and market information. Demand for information appears to be seasonal and deviates stochastically around a deterministic upward trend. With respect to the information formation and discovery process we find that although information demand and supply tend to be positively correlated, their significant dynamic interactions do not suggest any consistent causal relationship. Second, we show that the demand for information at the market level is significantly positively related to historical and implied measures of volatility and to trading volume, even after controlling for variations in the market return and the supply of information. The effect of idiosyncratic information demand on market activity is less strong and mixed in direction, and, diminishes if implied rather than historical measures of volatility are employed. Third, we show that information demand depends on the state of the market and increases significantly during periods of higher returns. Fourth, analysis of data on the expected variance risk premium for the S&P 500 index confirms for the first time empirically the hypothesis that investors demand more information as their level of risk aversion increases.