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 …

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 …

We develop and implement a method for maximum likelihood estimation in closed-form of
stochastic volatility models. Using Monte Carlo simulations, we compare a full likelihood …

This paper provides closed-form expansions for the transition density and likelihood function
of arbitrary multivariate diffusions. The expansions are based on a Hermite series, whose …

A beginner's guide to stochastic growth modeling The chief advantage of stochastic growth
models over deterministic models is that they combine both deterministic and stochastic …

Publisher Summary This chapter surveys a set of mathematical and statistical tools that are
valuable in understanding and characterizing nonlinear Markov processes. Such processes …

This paper is a survey of estimation techniques for stationary and ergodic diffusion
processes observed at discrete points in time. The reader is introduced to the following …

We study the term structure of variance swaps, equity and variance risk premia. A model-free
analysis reveals a significant price jump component in variance swap rates. A model-based …

We develop and implement a technique for closed-form maximum likelihood estimation
(MLE) of multifactor affine yield models. We derive closed-form approximations to likelihoods …

This paper proposes a widely applicable method of approximate maximum-likelihood
estimation for multivariate diffusion process from discretely sampled data. A closed-form …