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Forecasting Exchange Rate Density using Parametric Models: The Case of Brazil

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  • Marcos M. Abe
  • Eui J. Chang
  • Benjamin M. Tabak

Abstract

This paper employs a recently developed parametric technique to obtain density forecasts for the Brazilian exchange rate, using the exchange rate options market. Empirical results suggest that the option market contains useful information about future exchange rate density. These results suggests that density forecasts using options markets may add value for portfolio and risk management, and may be useful for financial regulators to assess financial stability.

Suggested Citation

  • Marcos M. Abe & Eui J. Chang & Benjamin M. Tabak, 2007. "Forecasting Exchange Rate Density using Parametric Models: The Case of Brazil," Working Papers Series 138, Central Bank of Brazil, Research Department.
  • Handle: RePEc:bcb:wpaper:138
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    File URL: http://www.bcb.gov.br/pec/wps/ingl/wps138.pdf
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    References listed on IDEAS

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    1. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
    2. Melick, William R. & Thomas, Charles P., 1997. "Recovering an Asset's Implied PDF from Option Prices: An Application to Crude Oil during the Gulf Crisis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(01), pages 91-115, March.
    3. Sandro Canesso de Andrade & Benjamin Miranda Tabak, 2001. "Is it Worth Tracking Dollar/Real Implied Volatility?," Working Papers Series 15, Central Bank of Brazil, Research Department.
    4. de Jong, C.M. & Huisman, R., 2000. "From Skews to a Skewed-t," ERIM Report Series Research in Management ERS-2000-12-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Liu, Xiaoquan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2007. "Closed-form transformations from risk-neutral to real-world distributions," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1501-1520, May.
    6. Breeden, Douglas T & Litzenberger, Robert H, 1978. "Prices of State-contingent Claims Implicit in Option Prices," The Journal of Business, University of Chicago Press, vol. 51(4), pages 621-651, October.
    7. Kabir K. Dutta & David F. Babbel, 2005. "Extracting Probabilistic Information from the Prices of Interest Rate Options: Tests of Distributional Assumptions," The Journal of Business, University of Chicago Press, vol. 78(3), pages 841-870, May.
    8. Charles J. Corrado, 2001. "Option pricing based on the generalized lambda distribution," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(3), pages 213-236, March.
    9. Panigirtzoglou, Nikolaos & Skiadopoulos, George, 2004. "A new approach to modeling the dynamics of implied distributions: Theory and evidence from the S&P 500 options," Journal of Banking & Finance, Elsevier, vol. 28(7), pages 1499-1520, July.
    10. Elerain, Ola & Chib, Siddhartha & Shephard, Neil, 2001. "Likelihood Inference for Discretely Observed Nonlinear Diffusions," Econometrica, Econometric Society, vol. 69(4), pages 959-93, July.
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    Cited by:

    1. José Renato Haas Ornelas, 2014. "Assessing the Forecast Ability of Risk-Neutral Densities and Real-World Densities from Emerging Markets Currencies," Working Papers Series 370, Central Bank of Brazil, Research Department.
    2. repec:sbe:breart:v:36:y:2016:i:1:a:45406 is not listed on IDEAS
    3. Ornelas, José Renato Haas & Barbachan, José Santiago Fajardo & Farias, Aquiles Rocha de, 2012. "Estimating relative risk aversion, risk-neutral and real-world densities using brazilian real currency options," EBAPE Working Papers 1, FGV/EBAPE - Escola Brasileira de Administração Pública e de Empresas (Brazil).

    More about this item

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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