Subordinated Exchange Rate Models: Evidence for Heavy Tailed Distributions and Long-Range Dependence
Mathematical and Computer Modelling, Vol. 34, No. 9-11, pp. 955-1001, 2001
70 Pages Posted: 15 Oct 2004
We investigate the main properties of high-frequency exchange rate data in the setting of stochastic subordination and stable modeling, focusing on heavy-tailedness and long memory, together with their dependence on the sampling period. We show that the the instrinsic time process exhibits strong long-range dependence and has increments well described by a Weibull law, while the return series in intrinsic time has weak long memory and is well approximated by a stable Levy motion. We also show that the stable domain of attraction offers a good fit to the returns in physical time, which leads us to consider as a realistic model for exchange rate data a process subordinated to an alpha-stable Levy motion (possibly fractional stable) by a long-memory intrinsic time process with Weibull distributed increments.
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