A Bayesian approach to option pricing is presented in which posterior inference about the underlying returns process is conducted implicitly via observed option prices. A range of models allowing for conditional leptokurtosis, skewness and time-varying volatility in returns are considered, with...

The aim of this paper is to examine the application of measures of persistence in a range of time-series models nested in the framework of Cramer (1961). This framework is a generalization of the Wold (1938) decomposition for stationary time-series which, in addition to accommodating the...

A method for estimating the parameters of stochastic differential equations (SDEs) by simulated maximum likelihood is presented. This method is feasible whenever the underlying SDE is a Markov process. Estimates are compared to those generated by indirect inference, discrete and exact maximum...

type="main" xml:id="jtsa12078-abs-0001"The parameters of integer autoregressive models with Poisson, or negative binomial innovations can be estimated by maximum likelihood where the prediction error decomposition, together with convolution methods, is used to write down the likelihood function....