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The forecast ability of risk-neutral densities of foreign exchange

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  • Craig, Ben R.
  • Keller, Joachim

Abstract

We estimate the process underlying the pricing of American options by using higher-order lattices combined with a multigrid method. This paper also tests whether the risk-neutral densities given from American options provide a good forecasting tool. We use a nonparametric test of the densities that is based on the inverse probability functions and is modified to account for correlation across time between our random variables, which are uniform under the null hypothesis. We find that the densities based on the Americanoption markets for foreign exchange do quite well for the forecasting period over which the options are thickly traded. Further, simple models that fit the densities do about as well as more sophisticated models.

Suggested Citation

  • Craig, Ben R. & Keller, Joachim, 2005. "The forecast ability of risk-neutral densities of foreign exchange," Discussion Paper Series 2: Banking and Financial Studies 2005,05, Deutsche Bundesbank.
    • Handle: RePEc:zbw:bubdp2:4260
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    References listed on IDEAS

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    1. Falko Fecht & Kevin X. D. Huang & Antoine Martin, 2008. "Financial Intermediaries, Markets, and Growth," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(4), pages 701-720, June.
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    5. Bates, David S, 1991. "The Crash of '87: Was It Expected? The Evidence from Options Markets," Journal of Finance, American Finance Association, vol. 46(3), pages 1009-1044, July.
    6. Valentina Corradi & Norman R. Swanson, 2001. "Bootstrap Specification Tests with Dependent Observations and Parameter Estimation Error," Discussion Papers 0101, University of Exeter, Department of Economics.
    7. 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.
    8. Clements, Michael P. & Smith, Jeremy, 2001. "Evaluating forecasts from SETAR models of exchange rates," Journal of International Money and Finance, Elsevier, vol. 20(1), pages 133-148, February.
    9. Hamerle, Alfred & Liebig, Thilo & Scheule, Harald, 2004. "Forecasting Credit Portfolio Risk," Discussion Paper Series 2: Banking and Financial Studies 2004,01, Deutsche Bundesbank.
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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. 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.
    3. Frederico Pechir Gomes & Marcelo Yoshio Takami & Vinicius Ratton Brandi, 2008. "Foreign Exchange Market Volatility Information: An Investigation of Real-Dollar Exchange Rate," Working Papers Series 174, Central Bank of Brazil, Research Department.
    4. Gabriele Galati & Patrick Higgins & Owen Humpage & William Melick, 2007. "Option prices, exchange market intervention, and the higher moment expectations channel: a user's guide," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(2), pages 225-247.
    5. Gomes, Frederico Pechir & Takami, Marcelo Yoshio & Brandi, Vinicius Ratton, 2008. "Investigating Unusual Changes in Real-Dollar Exchange Rate," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 62(2), October.

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    More about this item

    Keywords

    Risk-neutral densities from option prices; American exchange rate options; Evaluating Density Forecasts; Pentionominal tree; Density evaluation;
    All these keywords.

    JEL classification:

    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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