This paper gives a brief overview of the nonparametric techniques that are useful for
financial econometric problems. The problems include estimation and inference for …

The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

In financial and actuarial modeling and other areas of application, stochastic differential
equations with jumps have been employed to describe the dynamics of various state …

During the seven years that elapsed between the first and second editions of the present
book, considerable progress was achieved in the area of financial modelling and pricing of …

When a continuous‐time diffusion is observed only at discrete dates, in most cases the
transition distribution and hence the likelihood function of the observations is not explicitly …

Stochastic di? erential equations model stochastic evolution as time evolves. These models
have a variety of applications in many disciplines and emerge naturally in the study of many …

Let X t, t≤ T be a sample of discrete or continuous data that is randomly generated and
takes values in r-dimensional Euclidean space. The distribution of X t depends on a …

This article proposes a new method for estimation of parameters in diffusion processes from
discrete observations. The method is based on Markov-chain Monte Carlo methodology and …

This paper is concerned with the Bayesian estimation of nonlinear stochastic differential
equations when observations are discretely sampled. The estimation framework relies on …

Parameter estimation in stochastic differential equations and stochastic partial differential
equations is the science, art and technology of modelling complex phenomena and making …