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Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations

By Aubrey Hurn, Joseph Jeisman and Kenneth Lindsay


Maximum-likelihood estimates of the parameters of stochastic differential equations are consistent and asymptotically efficient, but unfortunately difficult to obtain if a closed-form expression for the transitional probability density function of the process is not available. As a result, a large number of competing estimation procedures have been proposed. This article provides a critical evaluation of the various estimation techniques. Special attention is given to the ease of implementation and comparative performance of the procedures when estimating the parameters of the Cox–Ingersoll–Ross and Ornstein–Uhlenbeck equations respectively

Topics: 140207 Financial Economics, 140300 ECONOMETRICS, 140303 Economic Models and Forecasting, 140305 Time-Series Analysis, 150200 BANKING FINANCE AND INVESTMENT, Stochastic Differential Equations, Parameter Estimation, Maximum Likelihood, Simulation, Moments
Publisher: Oxford University Press
Year: 2007
DOI identifier: 10.1093/jjfinec/nbm009
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