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dc.contributor.author Gallant, AR
dc.contributor.author Tauchen, GE
dc.date.accessioned 2010-03-09T15:43:08Z
dc.date.issued 1995
dc.identifier.citation 1995
dc.identifier.uri http://hdl.handle.net/10161/2063
dc.description.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.
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.subject G13
dc.title Specification Analysis of Continuous Time Models in Finance
dc.type Scholarly Edition
dc.department Economics
pubs.organisational-group /Duke
pubs.organisational-group /Duke/Trinity College of Arts & Sciences
pubs.organisational-group /Duke/Trinity College of Arts & Sciences/Economics

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