Subordinated exchange rate models: evidence for heavy tailed distributions and long-range dependence
- Creators
- Marinelli, C.
- Rachev, S. T.
- Roll, R.
Abstract
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 intrinsic 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 Lévy 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 Z(t) subordinated to an α-stable Lévy motion S(t) (possibly fractional stable) by a long-memory intrinsic time process T(t) with Weibull-distributed increments.
Additional Information
© 2001 Published by Elsevier Ltd. Available online 10 December 2001.Additional details
- Eprint ID
- 95188
- DOI
- 10.1016/S0895-7177(01)00113-3
- Resolver ID
- CaltechAUTHORS:20190502-141143200
- Created
-
2019-05-03Created from EPrint's datestamp field
- Updated
-
2021-11-16Created from EPrint's last_modified field