A Comparative Study of Likelihood Approximations for Univariate Diffusions*.
Maximum likelihood estimation of the parameters of stochastic differential equations commonly used in finance requires numerical approximation of their transitional probability density functions. This article undertakes a comparative study of the accuracy of Hermite polynomial expansion approximatio...
| Publicado en: | Journal of Financial Econometrics Vol. 21; no. 3; pp. 852 - 880 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Oxford University Press / USA
Summer2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=164351364&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 164351364 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 14798409 T2Y jtl: Journal of Financial Econometrics issn: 14798409 maglogo: N pubinfo: dt: Summer2023 vid: 21 iid: 3 pid: 622 pub: Oxford University Press / USA artinfo: ui: 164351364 10.1093/jjfinec/nbab021 ppf: 852 ppct: 28 formats: tig: atl: A Comparative Study of Likelihood Approximations for Univariate Diffusions*. aug: au: Hurn, Stan Lindsay, Kenneth Xu, Lina affil: School of Economics and Finance, Queensland University of Technology , Brisbane, Australia Department of Mathematics, University of Glasgow, Glasgow , UK su: Stochastic differential equations Maximum likelihood statistics Hermite polynomials Polynomial approximation Probability density function sug: subj: Stochastic differential equations Maximum likelihood statistics Hermite polynomials Polynomial approximation Probability density function keyword: C13 C18 C22 Gaussian quadrature Hermite polynomial expansions maximum likelihood estimation stochastic differential equations C13 C18 C22 Gaussian quadrature Hermite polynomial expansions maximum likelihood estimation stochastic differential equations ab: Maximum likelihood estimation of the parameters of stochastic differential equations commonly used in finance requires numerical approximation of their transitional probability density functions. This article undertakes a comparative study of the accuracy of Hermite polynomial expansion approximations for univariate diffusions and checks how the accuracy of the existing methods responds to increasing the order of the approximation. It is found that one class of expansion dealing with irreducible diffusions is particularly problematic due to the need to evaluate a number of troublesome integrals. A Gaussian quadrature is introduced which resolves the problem and improves the reliability of the expansion. A simulation study demonstrates all the methods in action and provides insight into the practical aspects of using these expansions. An empirical application using data on the VIX indicates that the proposed method based on the Gaussian quadrature performs very well when applied to financial data. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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