TY - JOUR
T1 - Conditional value-at-risk forecasts of an optimal foreign currency portfolio
AU - Kim, Dongwhan
AU - Kang, Kyu Ho
N1 - Funding Information:
We thank two anonymous referees and participants at the Bank of Korea seminar and KEA-APEA 2017 conference for useful feedback. This work is supported by a Korea University Grant ( K2009031 )
Publisher Copyright:
© 2020 International Institute of Forecasters
PY - 2021/4/1
Y1 - 2021/4/1
N2 - 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.
AB - 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.
KW - Bayesian MCMC method
KW - Conditional correlation
KW - Fat tail
KW - Stochastic volatility
KW - Time-varying
UR - http://www.scopus.com/inward/record.url?scp=85094595940&partnerID=8YFLogxK
U2 - 10.1016/j.ijforecast.2020.09.011
DO - 10.1016/j.ijforecast.2020.09.011
M3 - Article
AN - SCOPUS:85094595940
SN - 0169-2070
VL - 37
SP - 838
EP - 861
JO - International Journal of Forecasting
JF - International Journal of Forecasting
IS - 2
ER -