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dc.contributor.authorLux, Thomasen
dc.date.accessioned2012-08-03-
dc.date.accessioned2012-08-10T16:54:40Z-
dc.date.available2012-08-10T16:54:40Z-
dc.date.issued2012-
dc.identifier.urihttp://hdl.handle.net/10419/60335-
dc.description.abstractMaximum likelihood estimation of discretely observed diffusion processes is mostly hampered by the lack of a closed form solution of the transient density. It has recently been argued that a most generic remedy to this problem is the numerical solution of the pertinent Fokker-Planck (FP) or forward Kol- mogorov equation. Here we expand extant work on univariate diffusions to higher dimensions. We find that in the bivariate and trivariate cases, a numerical solution of the FP equation via alternating direction finite difference schemes yields results surprisingly close to exact maximum likelihood in a number of test cases. After providing evidence for the effciency of such a numerical approach, we illustrate its application for the estimation of a joint system of short-run and medium run investor sentiment and asset price dynamics using German stock market data.en
dc.language.isoengen
dc.publisher|aKiel Institute for the World Economy (IfW) |cKielen
dc.relation.ispartofseries|aKiel Working Paper |x1781en
dc.subject.jelC58en
dc.subject.jelG12en
dc.subject.jelC13en
dc.subject.ddc330en
dc.subject.keywordstochastic differential equationsen
dc.subject.keywordnumerical maximum likelihooden
dc.subject.keywordFokker-Planck equationen
dc.subject.keywordfinite difference schemesen
dc.subject.keywordasset pricingen
dc.subject.stwMaximum-Likelihood-Methodeen
dc.subject.stwAnalysisen
dc.subject.stwStochastischer Prozessen
dc.subject.stwTheorieen
dc.subject.stwBörsenkursen
dc.subject.stwAnlageverhaltenen
dc.subject.stwSchätzungen
dc.subject.stwDeutschlanden
dc.titleInference for systems of stochastic differential equations from discretely sampled data: A numerical maximum likelihood approach-
dc.typeWorking Paperen
dc.identifier.ppn720581907en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:ifwkwp:1781en

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