Statistical Methods for Stochastic Differential Equations

Mathieu Kessler, Alexander Lindner, Michael Sorensen

Hardback
$83.96

eBook
from $47.00

May 17, 2012 by Chapman and Hall/CRC
Monograph - 507 Pages - 17 B/W Illustrations
ISBN 9781439849408 - CAT# K12236
Series: Chapman & Hall/CRC Monographs on Statistics & Applied Probability

FREE Standard Shipping!

was $104.95

$83.96

SAVE $20.99

Add to Cart
Add to Wish List

Features

  • Provides an overview of recent developments in statistical methods for stochastic differential equations
  • Includes sufficient background material for each topic discussed, including high-frequency data, estimation based on simulation techniques, and diffusions with jumps
  • Presents applications to finance and econometrics
  • Contains mathematically rigorous contributions from leading researchers in the field

Summary

The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to the topic at hand and builds gradually towards discussing recent research.

The book covers Wiener-driven equations as well as stochastic differential equations with jumps, including continuous-time ARMA processes and COGARCH processes. It presents a spectrum of estimation methods, including nonparametric estimation as well as parametric estimation based on likelihood methods, estimating functions, and simulation techniques. Two chapters are devoted to high-frequency data. Multivariate models are also considered, including partially observed systems, asynchronous sampling, tests for simultaneous jumps, and multiscale diffusions.

Statistical Methods for Stochastic Differential Equations is useful to the theoretical statistician and the probabilist who works in or intends to work in the field, as well as to the applied statistician or financial econometrician who needs the methods to analyze biological or financial time series.