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FX volatility forecasts and the informational content of market data for volatility


  • Christian Dunis
  • Jason Laws
  • Stephane Chauvin


The paper examines the medium-term forecasting ability of several alternative models of currency volatility. The data period covers more than eight years of daily observations, January 1991 to March 1999, for the spot exchange rate, 1- and 3-month volatility of the DEM/JPY, GBP/DEM, GBP/USD, USD/CHF, USD/DEM and USD/JPY. Comparing with the results of 'pure' time series models, the reported work investigates whether market implied volatility data can add value in terms of medium-term forecasting accuracy. This is done using data directly available from the marketplace in order to avoid the potential biases arising from 'backing out' volatility from a specific option pricing model. On the basis of the over 34 000 out-of-sample forecasts produced, evidence tends to indicate that, although no single volatility model emerges as an overall winner in terms of forecasting accuracy, the 'mixed' models incorporating market data for currency volatility perform best most of the time.

Suggested Citation

  • Christian Dunis & Jason Laws & Stephane Chauvin, 2003. "FX volatility forecasts and the informational content of market data for volatility," The European Journal of Finance, Taylor & Francis Journals, vol. 9(3), pages 242-272.
  • Handle: RePEc:taf:eurjfi:v:9:y:2003:i:3:p:242-272 DOI: 10.1080/13518470210151100

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    References listed on IDEAS

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    Cited by:

    1. Keith Pilbeam & Kjell Langeland, 2015. "Forecasting exchange rate volatility: GARCH models versus implied volatility forecasts," International Economics and Economic Policy, Springer, vol. 12(1), pages 127-142, March.
    2. Szabolcs Blazsek & Anna Downarowicz, 2013. "Forecasting hedge fund volatility: a Markov regime-switching approach," The European Journal of Finance, Taylor & Francis Journals, vol. 19(4), pages 243-275, April.
    3. Raunig, Burkhard, 2008. "The predictability of exchange rate volatility," Economics Letters, Elsevier, vol. 98(2), pages 220-228, February.


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