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


Jenny N. Lye

Publication Date:

March 1, 1998

Electronic Access:

Free Download. Use the free Adobe Acrobat Reader to view this PDF file

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


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.


Working Paper No. 1998/029



Publication Date:

March 1, 1998



Stock No:




Please address any questions about this title to