|
Showing 1 - 4 of
4 matches in All Departments
This book presents a concise treatment of stochastic calculus and
its applications. It gives a simple but rigorous treatment of the
subject including a range of advanced topics, it is useful for
practitioners who use advanced theoretical results. It covers
advanced applications, such as models in mathematical finance,
biology and engineering.Self-contained and unified in presentation,
the book contains many solved examples and exercises. It may be
used as a textbook by advanced undergraduates and graduate students
in stochastic calculus and financial mathematics. It is also
suitable for practitioners who wish to gain an understanding or
working knowledge of the subject. For mathematicians, this book
could be a first text on stochastic calculus; it is good companion
to more advanced texts by a way of examples and exercises. For
people from other fields, it provides a way to gain a working
knowledge of stochastic calculus. It shows all readers the
applications of stochastic calculus methods and takes readers to
the technical level required in research and sophisticated
modelling.This second edition contains a new chapter on bonds,
interest rates and their options. New materials include more worked
out examples in all chapters, best estimators, more results on
change of time, change of measure, random measures, new results on
exotic options, FX options, stochastic and implied volatility,
models of the age-dependent branching process and the stochastic
Lotka-Volterra model in biology, non-linear filtering in
engineering and five new figures.Instructors can obtain slides of
the text from the author.
This book presents a concise and rigorous treatment of stochastic
calculus. It also gives its main applications in finance, biology
and engineering. In finance, the stochastic calculus is applied to
pricing options by no arbitrage. In biology, it is applied to
populations' models, and in engineering it is applied to filter
signal from noise. Not everything is proved, but enough proofs are
given to make it a mathematically rigorous exposition. This book
aims to present the theory of stochastic calculus and its
applications to an audience which possesses only a basic knowledge
of calculus and probability. It may be used as a textbook by
graduate and advanced undergraduate students in stochastic
processes, financial mathematics and engineering. It is also
suitable for researchers to gain working knowledge of the subject.
It contains many solved examples and exercises making it suitable
for self study. In the book many of the concepts are introduced
through worked-out examples, eventually leading to a complete,
rigorous statement of the general result, and either a complete
proof, a partial proof or a reference. Using such structure, the
text will provide a mathematically literate reader with rapid
introduction to the subject and its advanced applications. This
book covers models in mathematical finance, biology and
engineering. For mathematicians, this book can be used as a first
text on stochastic calculus or as a companion to more rigorous
texts by a way of examples and exercises.
This book presents a concise and rigorous treatment of stochastic
calculus. It also gives its main applications in finance, biology
and engineering. In finance, the stochastic calculus is applied to
pricing options by no arbitrage. In biology, it is applied to
populations' models, and in engineering it is applied to filter
signal from noise. Not everything is proved, but enough proofs are
given to make it a mathematically rigorous exposition. This book
aims to present the theory of stochastic calculus and its
applications to an audience which possesses only a basic knowledge
of calculus and probability. It may be used as a textbook by
graduate and advanced undergraduate students in stochastic
processes, financial mathematics and engineering. It is also
suitable for researchers to gain working knowledge of the subject.
It contains many solved examples and exercises making it suitable
for self study. In the book many of the concepts are introduced
through worked-out examples, eventually leading to a complete,
rigorous statement of the general result, and either a complete
proof, a partial proof or a reference. Using such structure, the
text will provide a mathematically literate reader with rapid
introduction to the subject and its advanced applications. This
book covers models in mathematical finance, biology and
engineering. For mathematicians, this book can be used as a first
text on stochastic calculus or as a companion to more rigorous
texts by a way of examples and exercises.
This book presents a concise treatment of stochastic calculus and
its applications. It gives a simple but rigorous treatment of the
subject including a range of advanced topics, it is useful for
practitioners who use advanced theoretical results. It covers
advanced applications, such as models in mathematical finance,
biology and engineering.Self-contained and unified in presentation,
the book contains many solved examples and exercises. It may be
used as a textbook by advanced undergraduates and graduate students
in stochastic calculus and financial mathematics. It is also
suitable for practitioners who wish to gain an understanding or
working knowledge of the subject. For mathematicians, this book
could be a first text on stochastic calculus; it is good companion
to more advanced texts by a way of examples and exercises. For
people from other fields, it provides a way to gain a working
knowledge of stochastic calculus. It shows all readers the
applications of stochastic calculus methods and takes readers to
the technical level required in research and sophisticated
modelling.This second edition contains a new chapter on bonds,
interest rates and their options. New materials include more worked
out examples in all chapters, best estimators, more results on
change of time, change of measure, random measures, new results on
exotic options, FX options, stochastic and implied volatility,
models of the age-dependent branching process and the stochastic
Lotka-Volterra model in biology, non-linear filtering in
engineering and five new figures.Instructors can obtain slides of
the text from the author.
|
|