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- W2890196216 abstract "We consider the tail probabilities of stock returns for a general class of stochastic volatility models. In these models, the stochastic differential equation for volatility is autonomous, time-homogeneous and dependent on only a finite number of dimensional parameters. Three bounds on the high-volatility limits of the drift and diffusion coefficients of volatility ensure that volatility is mean-reverting, has long memory and is as volatile as the stock price. Dimensional analysis then provides leading-order approximations to the drift and diffusion coefficients of volatility for the high-volatility limit. Thereby, using the Kolmogorov forward equation for the transition probability of volatility, we find that the tail probability for short-term returns falls off like an inverse cubic. Our analysis then provides a possible explanation for the inverse cubic fall off that Gopikrishnan et al. (1998) report for returns over 5-120 minutes intervals. We find, moreover, that the tail probability scales like the length of the interval, over which the return is measured, to the power 3/2. There do not seem to be any empirical results in the literature with which to compare this last prediction." @default.
- W2890196216 created "2018-09-27" @default.
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- W2890196216 date "2018-09-22" @default.
- W2890196216 modified "2023-09-26" @default.
- W2890196216 title "Tail probabilities for short-term returns on stocks" @default.
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- W2890196216 doi "https://doi.org/10.13140/rg.2.2.18816.28165" @default.
- W2890196216 hasPublicationYear "2018" @default.
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