@techreport{NBERt0059,
 title = "Maximum Likelihood Estimation of Generalized Ito Processes with Discretely Sampled Data",
 author = "Andrew W. Lo",
 institution = "National Bureau of Economic Research",
 type = "Working Paper",
 series = "Technical Working Paper Series",
 number = "59",
 year = "1986",
 month = "August",
 URL = "http://www.nber.org/papers/t0059",
 abstract = {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.},
}