Forecasting Implied Volatility in Foreign Exchange Markets: A Functional Time Series Approach

Fearghal Kearney, Mark Cummins, Finbarr Murphy

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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.
Original languageEnglish
Pages (from-to)1-18
JournalEuropean Journal of Finance
Early online date26 Jan 2017
DOIs
Publication statusEarly online date - 26 Jan 2017

Bibliographical note

Fearghal Kearney, Mark Cummins & Finbarr Murphy (2018) Forecasting implied volatility in foreign exchange markets: a functional time series approach, The European Journal of Finance, 24:1, 1-18, DOI: 10.1080/1351847X.2016.1271441

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