A highly readable introduction to stochastic integration and
stochastic differential equations, this book combines developments
of the basic theory with applications. It is written in a style
suitable for the text of a graduate course in stochastic calculus,
following a course in probability.
Using the modern approach, the stochastic integral is defined
for predictable integrands and local martingales; then It s change
of variable formula is developed for continuous martingales.
Applications include a characterization of Brownian motion, Hermite
polynomials of martingales, the Feynman Kac functional and
theSchrodinger equation. For Brownian motion, the topics of local
time, reflected Brownian motion, and time change are discussed.
New to the second edition are a discussion of the Cameron Martin
Girsanov transformation and a final chapter which provides an
introduction to stochastic differential equations, as well as many
exercises for classroom use.
This book will be a valuable resource to all mathematicians,
statisticians, economists, and engineers employing the modern tools
of stochastic analysis.
"The text also proves that stochastic integration has made an
important impact on mathematical progress over the last decades and
that stochastic calculus has become one of the most powerful tools
in modern probability theory. "
Journal of the American Statistical Association
"An attractive text written in a] lean and precise style
eminently readable. Especially pleasant are the care and attention
devoted to details A very fine book."
Mathematical Reviews"
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