Specification Analysis of Continuous Time Models in Finance

A. Gallant and George Tauchen ()

No 95-49, Working Papers from Duke University, Department of Economics

Abstract: The paper describes the use of the Gallant-Tauchen efficient method of moments (EMM) technique for diagnostic checking of stochastic differential equations (SDEs) estimated from financial market data. The EMM technique is a simulation-based method that uses the score function of an auxiliary model as the criterion to define a generalized method of moments (GMM) objective function. The technique can handle multivariate SDEs where the state vector is not completely observed. The optimized GMM objective function is distributed as chi-square and may be used to test model adequacy. Elements of the score function correspond to specific parameters and large values reflect features of data that a rejected SDE specification does not describe well. The diagnostics are illustrated by estimating a three-factor model to weekly, 1962-1995, term structure data comprised of short (3 month), medium (12 month), and long (10 year) Treasury rates. The Yield-Factor Model is sharply rejected, although an extension that permits the local variance function to be a convex function of the interest rates comes much closer to describing the data.

JEL-codes: G13 (search for similar items in EconPapers)
Date: 1995
References: Add references at CitEc
Citations:

Published in MODELLING STOCK MARKET VOLATILITY: BRIDGING THE GAP TO CONTINUOUS TIME, Peter E. Rossi (ed.), Academic Press, 1996, pages 357-383

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:duk:dukeec:95-49

Access Statistics for this paper

More papers in Working Papers from Duke University, Department of Economics Department of Economics Duke University 213 Social Sciences Building Box 90097 Durham, NC 27708-0097.
Bibliographic data for series maintained by Department of Economics Webmaster ().