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Filtering and Forecasting with Misspecified Arch Models II : Making the Right Forecast with the Wrong Model

Author: Daniel B Nelson; Dean P Foster
Publisher: Cambridge, Mass. National Bureau of Economic Research 1992.
Series: Technical Working Paper Series (National Bureau of Economic Research), no. t0132.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
A companion paper (Nelson (1992)) showed that in data observed at high frequencies, an ARCH model may do a good job at estimating conditional variances, even when the ARCH model is severely misspecified. While such models may perform reasonably well at filtering (i.e., at estimating unobserved instantaneous conditional variances) they may perform disastrously at medium and long term forecasting. In this paper, we  Read more...
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Details

Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Daniel B Nelson; Dean P Foster
OCLC Number: 1027337720
Notes: December 1992.
Description: 1 online resource.
Details: Mode of access: World Wide Web.
Series Title: Technical Working Paper Series (National Bureau of Economic Research), no. t0132.
Responsibility: Daniel B. Nelson, Dean P. Foster.

Abstract:

A companion paper (Nelson (1992)) showed that in data observed at high frequencies, an ARCH model may do a good job at estimating conditional variances, even when the ARCH model is severely misspecified. While such models may perform reasonably well at filtering (i.e., at estimating unobserved instantaneous conditional variances) they may perform disastrously at medium and long term forecasting. In this paper, we develop conditions under which a misspecified ARCH model successfully performs both tasks, filtering and forecasting. The key requirement (in addition to the conditions for consistent filtering) is that the ARCH model correctly specifies the functional form of the first two conditional moments of all state variables. We apply these results to a diffusion model employed in the options pricing literature, the stochastic volatility model of Hull and White (1987), Scott (1987), and Wiggins (1987).

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