Modeling and forecasting intraday VaR of an exchange rate portfolio

Omar Abbara and Mauricio Zevallos

Journal of Forecasting, 2018, vol. 37, issue 7, 729-738

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.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:wly:jforec:v:37:y:2018:i:7:p:729-738

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