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Estimation and arbitrage opportunities for exchange rate baskets

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  • Mercurio, Danilo
  • Torricelli, Costanza

Abstract

This paper analyzes short term portfolio investment opportunities in a capital market where a currency is defined as a currency basket, i.e. a linear combination of foreign currencies. In line with the mean-variance hedging approach, we determine a self-financed optimal investment strategy which minimizes an expected quadratic cost function. In order to implement such a strategy an estimate of the basket weights is required. To this end we suggest an adaptive nonparametric procedure, which, if compared with standard procedures, provides very satisfactory results both on simulated and real data. We apply the optimal investment strategy to the case of the Thai Bath basket. The basket weights are computed with the adaptive estimator. We also implement a recursive estimator, a rolling estimator and the Ka1man filter which serve as benchmark models. The different estimators are compared with profit based criteria.

Suggested Citation

  • Mercurio, Danilo & Torricelli, Costanza, 2001. "Estimation and arbitrage opportunities for exchange rate baskets," SFB 373 Discussion Papers 2001,37, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    • Handle: RePEc:zbw:sfb373:200137
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    Cited by:

    1. Danilo Mercurio & Costanza Torricelli, 2003. "Estimation and arbitrage opportunities for exchange rate baskets," Applied Economics, Taylor & Francis Journals, vol. 35(15), pages 1689-1698.
    2. Hsin-Hung Chen & Hsien-Tang Tsai & Dennis Lin, 2011. "Optimal mean-variance portfolio selection using Cauchy-Schwarz maximization," Applied Economics, Taylor & Francis Journals, vol. 43(21), pages 2795-2801.

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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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