Modelling exchange rate volatility with random level shifts
Files
Accepted manuscript
Date
2017-01-01
Authors
Li, Ye
Perron, Pierre
Xu, Jiawen
Version
OA Version
Citation
Ye Li, Pierre Perron, Jiawen Xu. 2017. "Modelling exchange rate volatility with random level shifts." APPLIED ECONOMICS, Volume 49, Issue 26, pp. 2579 - 2589 (11).
Abstract
Recent literature has shown that the volatility of exchange rate returns displays long memory features. It has also been shown that if a short memory process is contaminated by level shifts, the estimate of the long memory parameter tends to be upward biased. In this article, we directly estimate a random level shift model to the logarithm of the absolute returns of five exchange rates series, in order to assess whether random level shifts (RLSs) can explain this long memory property. Our results show that there are few level shifts for the five series, but once they are taken into account the long memory property of the series disappears. We also provide out-of-sample forecasting comparisons, which show that, in most cases, the RLS model outperforms popular models in forecasting volatility. We further support our results using a variety of robustness checks.