Forecasting EUR–USD implied volatility: The case of intraday data

Christian Dunis, Neil Kellard () and Stuart Snaith

Journal of Banking & Finance, 2013, vol. 37, issue 12, 4943-4957

Abstract: This study models and forecasts the evolution of intraday implied volatility on an underlying EUR–USD exchange rate for a number of maturities. To our knowledge we are the first to employ high frequency data in this context. This allows the construction of forecasting models that can attempt to exploit intraday seasonalities such as overnight effects. Results show that implied volatility is predictable at shorter horizons, within a given day and across the term structure. Moreover, at the conventional daily frequency, intraday seasonality effects can be used to augment the forecasting power of models. The type of inefficiency revealed suggests potentially profitable trading models.

Keywords: Exchange rates; Implied volatility; Intraday data; Out-of-sample prediction (search for similar items in EconPapers)
JEL-codes: C22 C32 C53 C58 G17 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:37:y:2013:i:12:p:4943-4957

DOI: 10.1016/j.jbankfin.2013.08.028

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