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Foster-Hart optimization for currency portfolios

Author

Listed:
  • Kurosaki Tetsuo

    (Bank of Japan, 2-1-1 Nihonbashi-Hongokucho, Chuo-ku, Tokyo 103-8660, Japan)

  • Kim Young Shin

    (Stony Brook University, College of Business, Stony Brook, NY 11794-3775, United States of America)

Abstract

We examine the effectiveness of Foster-Hart optimization for currency portfolios. Compared to stock trading, short selling is quite common in currency trading. Combining long and short positions leads to maintaining positive expected portfolio returns. Foster-Hart optimization is more applicable to currency portfolios than to stock portfolios because the Foster-Hart risk measure is not defined for the gamble whose expected returns are negative. Our sample portfolio consists of ten European currencies. For time series analysis, we employ a generalized autoregressive conditional heteroscedasticity (GARCH) model with multivariate normal tempered stable (MNTS) distributed residuals in order to capture fat-tailedness, skewness, and asymmetric interdependence of exchange rate dynamics. Statistical tests indicate that the model is recommendable among the candidate models. We establish that Foster-Hart optimization is more profitable than standard techniques in this context.

Suggested Citation

  • Kurosaki Tetsuo & Kim Young Shin, 2019. "Foster-Hart optimization for currency portfolios," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(2), pages 1-15, April.
    • Handle: RePEc:bpj:sndecm:v:23:y:2019:i:2:p:15:n:6
    DOI: 10.1515/snde-2017-0119
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    References listed on IDEAS

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    More about this item

    Keywords

    average value at risk; Foster-Hart risk; multivariate normal tempered stable distribution; portfolio optimization; value at risk;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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