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Estimation and arbitrage opportunities for exchange rate baskets

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  • Danilo Mercurio
  • Costanza Torricelli

Abstract

This paper analyses short-term portfolio investment opportunities in a capital market where a currency is defined as a currency basket. In line with the mean-variance hedging approach, a self-financed optimal investment strategy is determined which minimizes the expected quadratic cost function. The successful implementation of the speculative strategy requires a precise estimate of the basket weights, which are possibly non-constant over time. To this end, an adaptive non-parametric procedure is suggested which provides satisfactory results both on simulated and real data. The optimal investment strategy is applied to the case of the Thai Baht basket whereby the weights are computed by means of the adaptive estimator. A recursive estimator, a rolling estimator and the Kalman filter, are implemented and serve as benchmark models. Results are compared with the literature. The different estimators are evaluated with profit-based criteria and the performance of the adaptive estimator turns out to be the best one.

Suggested Citation

  • Danilo Mercurio & Costanza Torricelli, 2003. "Estimation and arbitrage opportunities for exchange rate baskets," Applied Economics, Taylor & Francis Journals, vol. 35(15), pages 1689-1698.
    • Handle: RePEc:taf:applec:v:35:y:2003:i:15:p:1689-1698
    DOI: 10.1080/0003684032000095938
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    References listed on IDEAS

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    1. Christoffersen, Peter F & Giorgianni, Lorenzo, 2000. "Interest-Rate Arbitrage in Currency Baskets: Forecasting Weights and Measuring Risk," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(2), pages 242-253, April.
    2. Cooley, Thomas F & Prescott, Edward C, 1973. "An Adaptive Regression Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(2), pages 364-371, June.
    3. Danilo Mercurio & Costanza Torricelli, 2003. "Estimation and arbitrage opportunities for exchange rate baskets," Applied Economics, Taylor & Francis Journals, vol. 35(15), pages 1689-1698.
    4. Canarellsal, Giorgio & Pollard, Stephen K. & Lai, Kon S., 1990. "Cointegration between exchange rates and relative prices: another view," European Economic Review, Elsevier, vol. 34(7), pages 1303-1322, November.
    5. Liptser, R. & Spokoiny, Vladimir G., 1999. "Deviation probability bound for martingales with applications to statistical estimation," SFB 373 Discussion Papers 1999,85, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    6. Hansen, Bruce E, 2002. "Tests for Parameter Instability in Regressions with I(1) Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 45-59, January.
    7. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    8. Granger, Clive W J, 1986. "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 213-228, August.
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    Cited by:

    1. 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.
    2. Danilo Mercurio & Costanza Torricelli, 2003. "Estimation and arbitrage opportunities for exchange rate baskets," Applied Economics, Taylor & Francis Journals, vol. 35(15), pages 1689-1698.

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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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