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Daily Exchange Rate Behaviour and Hedging of Currency Risk

Author

Listed:
  • Charles S. Bos

    (Erasmus University Rotterdam)

  • Ronald J. Mahieu

    (Rotterdam School of Management)

  • Herman K. van Dijk

    (Econometric Institute, Erasmus University Rotterdam)

Abstract

This discussion paper led to a publication in the 'Journal of Applied Econometrics', 2000, 15(6), pages 671-696. Exchange rates typically exhibit time-varying patterns in both means andvariances. The histograms of such series indicate heavy tails. In thispaper we construct models which enable a decision-maker to analyze theimplications of such time series patterns for currency risk management.Our approach is Bayesian where extensive use is made of Markov chainMonte Carlo methods. The effects of several model characteristics(unit roots, GARCH, stochastic volatility, heavy tailed disturbancedensities) are investigated in relation to the hedging decision strategies.Consequently, we can make a distinction between statistical relevanceof model specifications, and the economic consequences from a riskmanagement point of view. The empirical results suggest thateconometric modelling of heavy tails and time-varying means and variances paysoff compared to a efficient markets model. The different ways to measurepersistence and changing volatilities appear to strongly influence thehedging decision the investor faces.

Suggested Citation

  • Charles S. Bos & Ronald J. Mahieu & Herman K. van Dijk, 1999. "Daily Exchange Rate Behaviour and Hedging of Currency Risk," Tinbergen Institute Discussion Papers 99-078/4, Tinbergen Institute.
  • Handle: RePEc:tin:wpaper:19990078
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    Citations

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    Cited by:

    1. Thomas M. Trimbur, 2006. "Detrending economic time series: a Bayesian generalization of the Hodrick-Prescott filter," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(4), pages 247-273.
    2. Vasco Cúrdia & Marco Del Negro & Daniel L. Greenwald, 2014. "Rare Shocks, Great Recessions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1031-1052, November.
    3. Charles Bos & Neil Shephard, 2006. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 219-244.
    4. Hoogerheide, Lennart F. & Kaashoek, Johan F. & van Dijk, Herman K., 2007. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural networks," Journal of Econometrics, Elsevier, vol. 139(1), pages 154-180, July.
    5. Jacek Osiewalski & Mateusz Pipien, 2004. "Bayesian Comparison of Bivariate GARCH Processes in the Presence of an Exogenous Variable," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 6, pages 25-36.
    6. Siem Jan Koopman & Charles S. Bos, 2002. "Time Series Models with a Common Stochastic Variance for Analysing Economic Time Series," Tinbergen Institute Discussion Papers 02-113/4, Tinbergen Institute.
    7. Charles Bos & Neil Shephard, 2006. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 219-244.

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    More about this item

    Keywords

    Bayesian decision making; econometric modelling; exchange rates; risk management; forward contracts; stochastic volatility; GARCH;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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