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Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange

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Listed:
  • Francis X. Diebold
  • Jinyong Hahn
  • Anthony S. Tay
Abstract
We provide a framework for evaluating and improving multivariate density forecasts. Among other things, the multivariate framework lets us evaluate the adequacy of density forecasts involving cross-variable interactions, such as time-varying conditional correlations. We also provide conditions under which a technique of density forecast "calibration" can be used to improve deficient density forecasts. Finally, motivated by recent advances in financial risk management, we provide a detailed application to multivariate high-frequency exchange rate density forecasts.

Suggested Citation

  • Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1998. "Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-079, New York University, Leonard N. Stern School of Business-.
    • Handle: RePEc:fth:nystfi:98-079
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    Cited by:

    1. Lopez, Jose A. & Saidenberg, Marc R., 2000. "Evaluating credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 151-165, January.
    2. Stefan Jaschke & Gerhard Stahl & Richard Stehle, 2007. "Value-at-risk forecasts under scrutiny—the German experience," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 621-636.

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    More about this item

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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