2026-04-03T23:26:43Zhttps://recercat.cat/oai/request

oai:recercat.cat:2445/188952025-11-19T20:28:01Zcom_2072_1057col_2072_478822col_2072_478917

00925njm 22002777a 4500 dc Masoliver, Jaume, 1951- author Perelló, Josep, 1974- author 2011-07-07T12:54:51Z 2011-07-07T12:54:51Z 2007 Extreme times techniques, generally applied to nonequilibrium statistical mechanical processes, are also useful for a better understanding of financial markets. We present a detailed study on the mean first-passage time for the volatility of return time series. The empirical results extracted from daily data of major indices seem to follow the same law regardless of the kind of index thus suggesting an universal pattern. The empirical mean first-passage time to a certain level L is fairly different from that of the Wiener process showing a dissimilar behavior depending on whether L is higher or lower than the average volatility. All of this indicates a more complex dynamics in which a reverting force drives volatility toward its mean value. We thus present the mean first-passage time expressions of the most common stochastic volatility models whose approach is comparable to the random diffusion description. We discuss asymptotic approximations of these models and confront them to empirical results with a good agreement with the exponential Ornstein-Uhlenbeck model. Física matemàtica Sistemes no lineals Mathematical physics Nonlinear systems Extreme times for volatility processes