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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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    References listed on IDEAS

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    1. 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.
    2. West, Kenneth D. & Cho, Dongchul, 1995. "The predictive ability of several models of exchange rate volatility," Journal of Econometrics, Elsevier, vol. 69(2), pages 367-391, October.
    3. 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.
    4. Sheri Markose & Amadeo Alentorn, 2005. "Option Pricing and the Implied Tail Index with the Generalized Extreme Value (GEV) Distribution," Computing in Economics and Finance 2005 397, Society for Computational Economics.
    5. Bookstaber, Richard M & McDonald, James B, 1987. "A General Distribution for Describing Security Price Returns," The Journal of Business, University of Chicago Press, vol. 60(3), pages 401-424, July.
    6. Elerain, Ola & Chib, Siddhartha & Shephard, Neil, 2001. "Likelihood Inference for Discretely Observed Nonlinear Diffusions," Econometrica, Econometric Society, vol. 69(4), pages 959-993, July.
    7. Markose, Sheri M & Alentorn, Amadeo, 2005. "The Generalized Extreme Value (GEV) Distribution, Implied Tail Index and Option Pricing," Economics Discussion Papers 3726, University of Essex, Department of Economics.
    8. 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.
    9. 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(1), pages 91-115, March.
    10. 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.
    11. repec:bla:jfinan:v:59:y:2004:i:1:p:407-446 is not listed on IDEAS
    12. Robert J. Ritchey, 1990. "Call Option Valuation For Discrete Normal Mixtures," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 13(4), pages 285-296, December.
    13. 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. 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).
    2. 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.
    3. Ornelas, José Renato Haas, 2016. "The Forecast Ability of Option-implied Densities from Emerging Markets Currencies," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 36(1), March.

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    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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