Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces

Han Lin Shang and Fearghal Kearney

Papers from arXiv.org

Abstract: This paper presents static and dynamic versions of univariate, multivariate, and multilevel functional time-series methods to forecast implied volatility surfaces in foreign exchange markets. We find that dynamic functional principal component analysis generally improves out-of-sample forecast accuracy. More specifically, the dynamic univariate functional time-series method shows the greatest improvement. Our models lead to multiple instances of statistically significant improvements in forecast accuracy for daily EUR-USD, EUR-GBP, and EUR-JPY implied volatility surfaces across various maturities, when benchmarked against established methods. A stylised trading strategy is also employed to demonstrate the potential economic benefits of our proposed approach.

Date: 2021-07
New Economics Papers: this item is included in nep-ets, nep-for, nep-isf and nep-rmg
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http://arxiv.org/pdf/2107.14026 Latest version (application/pdf)

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Journal Article: Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2107.14026

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