首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Forecasting implied volatility in foreign exchange markets: a functional time series approach
Authors:Fearghal Kearney  Mark Cummins  Finbarr Murphy
Institution:1. Queen's Management School, Queen's University Belfast, Belfast, UK;2. Dublin City University Business School, Dublin City University, Dublin 9, Ireland;3. Kemmy Business School, University of Limerick, Limerick, Ireland
Abstract:We utilise novel functional time series (FTS) techniques to characterise and forecast implied volatility in foreign exchange markets. In particular, we examine the daily implied volatility curves of FX options, namely; Euro/United States Dollar, Euro/British Pound, and Euro/Japanese Yen. The FTS model is shown to produce both realistic and plausible implied volatility shapes that closely match empirical data during the volatile 2006–2013 period. Furthermore, the FTS model significantly outperforms implied volatility forecasts produced by traditionally employed parametric models. The evaluation is performed under both in-sample and out-of-sample testing frameworks with our findings shown to be robust across various currencies, moneyness segments, contract maturities, forecasting horizons, and out-of-sample window lengths. The economic significance of the results is highlighted through the implementation of a simple trading strategy.
Keywords:Exchange rates  implied volatility  forecasting  functional data analysis  functional time series
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号