Conditional value-at-risk forecasts of an optimal foreign currency portfolio

Dongwhan Kim and Kyu Ho Kang

International Journal of Forecasting, 2021, vol. 37, issue 2, 838-861

Abstract: This study provides daily conditional value-at-risk (C-VaR) forecasts for a foreign currency portfolio comprising the USD/EUR, USD/JPY, and USD/BRL currencies. To do so, we estimate multivariate stochastic volatility models with time-varying conditional correlations using a Bayesian Markov chain Monte Carlo algorithm. Then, given the model-specific currency return density forecasts, we make the optimal portfolio choice by minimizing the C-VaR through numerical optimization. According to out-of-sample experiment, including emerging markets into the currency basket is essential for downside risk management, and considering model uncertainty as well as the parameter uncertainty can improve the portfolio performance.

Keywords: Fat tail; Stochastic volatility; Time-varying; Conditional correlation; Bayesian MCMC method (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:37:y:2021:i:2:p:838-861

DOI: 10.1016/j.ijforecast.2020.09.011

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