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Hedging the exchange rate risk for international portfolios

Xing Yu, Wei Guo Zhang, Yong Jun Liu, Xinxin Wang and Chao Wang

Mathematics and Computers in Simulation (MATCOM), 2020, vol. 173, issue C, 85-104

Abstract: This paper studies exchange rate risk hedging with currency options in international portfolios. We propose a new iterative method to estimate the bandwidth of the kernel density estimator (KDE). Based on KDE, we further estimate the density function of the hedging portfolio’s return and calculate the risk of lower partial moments (LPM). Some in-depth analysis is conducted for currency of USD/CAD in two sample spaces (i.e. testing the hedging efficiency with in-sample data and out-of-sample simulation). Specifically, we test whether currency options hedging can improve the performance of international assets portfolios and find that, for the investors whose domestic currency is CAD, currency options hedging is more significant and outperforms other instruments in the investment period of in-sample. To examine the robustness, we also investigate the hedging effectiveness of the proposed model in view of the out-of-sample simulation. Simulation results demonstrate the superiority of currency options hedging in terms of reducing the downside risk exposure. We find that higher risk aversion or target return means an increase in downside risk, but efficient frontier measured by mean/LPM becomes smaller. The efficient frontier markedly increases when the investor hedges the exchange rate risk with currency options. We also apply the proposed model to the currency of USD/CHN and obtain similar results. Therefore, we suggest investors to buy put options with larger strike price for hedging exchange rate risk.

Keywords: Exchange rate risk; Hedging with currency options; Kernel density estimation; Differential evolution algorithm; International portfolios (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:173:y:2020:i:c:p:85-104

DOI: 10.1016/j.matcom.2020.02.014

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