Inference for Diffusion Processes and Stochastic Volatility Models Ph.D. thesis
نویسندگان
چکیده
We discuss parameter estimation for discretely observed, ergodic diffusion processes where the diffusion coefficient does not depend on the parameter. We propose using an approximation of the continuous-time score function as an estimating function. The estimating function can be expressed in simple terms through the drift and the diffusion coefficient and is thus easy to calculate. Simulation studies show that the method performs well.
منابع مشابه
DYNSTOCH 2013 University of Copenhagen April 17 - 19
s (Talks) 5 Adeline Samson. PARAMETER ESTIMATION IN THE STOCHASTIC MORRIS-LECAR NEURONAL MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Alexander Schnurr. AN ORDINAL PATTERN APPROACH TO DETECT AND TO MODEL DEPENDENCE STRUCTURES BETWEEN FINANCIAL TIME SERIES . . . . . . . . . . . . 7 Benedikt Funke. ADAPTIVE NADARAYA-WATSON LIKE ESTIMATORS FOR THE ESTIMATION ...
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