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Modeling and forecasting intraday VaR of an exchange rate portfolio

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  • Omar Abbara
  • Mauricio Zevallos

Abstract

The main task of this work was to predict, for the next 15 minutes, the value‐at‐risk (VaR) of an equally weighted portfolio composed of four exchange rates against the American dollar: Japanese yen, euro, Australian dollar and Swiss franc. The dataset consists of transaction prices of each asset recorded every 15 minutes, from January 7, 2013 to December 31, 2013. For each time series, the multiplicative‐component generalized autoregressive conditional heteroskedasticity model of Engle and Sokalska (Journal of Financial Econometrics, 2012, 10, 54–83) is fitted, and the dependence among the series is modeled by a D‐vine pair‐copula. VaR predictions are estimated based on simulated observations of the fitted model following the proposal of Berg and Aas (European Journal of Finance, 2009, 15, 639–659). The proposed method presents good results in terms of out‐of‐sample intraday VaR forecasting.

Suggested Citation

  • Omar Abbara & Mauricio Zevallos, 2018. "Modeling and forecasting intraday VaR of an exchange rate portfolio," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(7), pages 729-738, November.
    • Handle: RePEc:wly:jforec:v:37:y:2018:i:7:p:729-738
    DOI: 10.1002/for.2540
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    Cited by:

    1. Gong, Yuting & Ma, Chao & Chen, Qiang, 2022. "Exchange rate dependence and economic fundamentals: A Copula-MIDAS approach," Journal of International Money and Finance, Elsevier, vol. 123(C).
    2. Leonard Arvi & Herman Manakyan & Kashi Khazeh, 2023. "Estimated Impact of Covid-19 on Exchange Rate Risk of Multinational Enterprises Operating in Emerging Markets," International Journal of Economics and Financial Issues, Econjournals, vol. 13(4), pages 23-29, July.
    3. William E. Nganje & Linda D. Burbidge & Elisha K. Denkyirah & Elvis M. Ndembe, 2021. "Predicting Food-Safety Risk and Determining Cost-Effective Risk-Reduction Strategies," JRFM, MDPI, vol. 14(9), pages 1-18, September.

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