IMF Working Papers

Parametric Distributional Flexibility and Conditional Variance Models with an Application to Hourly Exchange Rates

By Jenny N. Lye

March 1, 1998

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Jenny N. Lye Parametric Distributional Flexibility and Conditional Variance Models with an Application to Hourly Exchange Rates, (USA: International Monetary Fund, 1998) accessed September 18, 2024
Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate

Summary

This paper builds on the ARCH approach for modeling distributions with time-varying conditional variance by using the generalized Student t distribution. The distribution offers flexibility in modeling both leptokurtosis and asymmetry (characteristics seen in high-frequency financial time series data), nests the standard normal and Student t distributions, and is related to the Gram Charlier and mixture distributions. An empirical ARCH model based on this distribution is formulated and estimated using hourly exchange rate returns for four currencies. The generalized Student t is found to better model the empirical conditional and unconditional distributions than other distributional specifications.

Subject: Currencies, Exchange rate modelling, Exchange rates, Foreign exchange, Monetary policy, Money, Standing facilities

Keywords: ARCH, Conditional distribution, Currencies, Distribution parameter, Exchange rate modelling, Exchange Rates, Generalized Student t Distributions, Gram Charlier distribution, Mixture distribution, Modeling Variance, Standing facilities, Stud. t, WP

Publication Details

  • Pages:

    39

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Working Paper No. 1998/029

  • Stock No:

    WPIEA0291998

  • ISBN:

    9781451844771

  • ISSN:

    1018-5941