Time to Digest and Volatility Dynamics∗

This paper proposes a new mechanism to explain the dynamics of asset return volatility. Random shocks to asset fundamentals arrive according to a Poisson process. Financial analysts gradually reduce the uncertainty created by a shock subject to capacity constraints or cost of effort associated with processing information. In the short-run, analysts work at their maximum capacity to digest the shock, resulting in an exponential decay pattern in the serial correlation of asset return volatility similar to an ARCH/GARCH type volatility model. In the long run, analysts gradually reduce effort as uncertainty decreases, causing a hyperbolic decay pattern in the serial correlation of the stock return volatility process. This decay rate can be slow enough to explain the long memory property of the return volatility process documented in the literature. We analyze cross-sectionally the long-run persistence of volatility of individual stocks on NYSE/AMEX. We found evidence that supports the link between the degree of volatility persistence and the cost of analysts’ effort. Comments Welcome ∗Lin Peng is with Baruch College, City University of New York. Email: lin [email protected], Phone: (646) 312-3491, Fax: (425)962-6137. Wei Xiong is with the Department of Economics and Bendheim Center for Finance, Princeton University. Email: [email protected], Phone: (609) 258-0282, Fax: (609) 2580771. The authors wish to thank Tim Bollerslev, Markus Brunnermeier, Gregory Chow, Jennifer Francis, Campbell Harvey, David Hsieh, Pete Kyle, Hui Ou-Yang, Katherine Schipper, Chris Sims, George Tauchen, S. Viswanathan, and seminar participants at Duke University financial econometrics workshop and finance seminar, Princeton University, Rutgers University, UNC-Chapel Hill macro workshop, and the 12th annual conference on financial economics and accounting for helpful discussions. All errors remain our responsibility. Time to Digest and Volatility Dynamics