Maximum Likelihood Estimation of Hidden Markov Processes

We consider the process dYt=ut dt+dWt, where u is a process not necessarily adapted to FY (the filtration generated by the process Y) and W is a Brownian motion. We obtain a general representation for the likelihood ratio of the law of the Y process relative to Brownian measure. This representation...

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Veröffentlicht in:	The Annals of applied probability 2003-11, Vol.13 (4), p.1296-1312
Hauptverfasser:	Frydman, Halina, Lakner, Peter
Format:	Artikel
Sprache:	eng
Schlagworte:	60J25 60J60 62M05 Brownian motion E-M algorithm filtered integrals Financial modeling Hidden diffusion financial models likelihood ratio Markov chains Markov processes Mathematical independent variables Maximum likelihood estimation Maximum likelihood estimators Random variables Security prices Stochastic processes
Online-Zugang:	Volltext
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