NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

Maximum Likelihood Estimation of Generalized Ito Processes with Discretely Sampled Data

Andrew W. Lo

NBER Technical Working Paper No. 59
Issued in August 1986
NBER Program(s):   ME

In this paper, we consider the parametric estimation problem for continuous time stochastic processes described by general first-order nonlinear stochastic differential equations of the Ito type. We characterize the likelihood function of a discretely-sampled set of observations as the solution to a functional partial differential equation. The consistency and asymptotic normality of the maximum likelihood estimators are explored, and several illustrative examples are provided.

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Document Object Identifier (DOI): 10.3386/t0059

Published: Econometric Theory, vol. 4, 1988, pp. 231-247

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