Stochastic Methods in Asset Pricing

Stochastic Methods in Asset Pricing
Author :
Publisher : MIT Press
Total Pages : 632
Release :
ISBN-13 : 9780262036559
ISBN-10 : 026203655X
Rating : 4/5 (5X Downloads)

Book Synopsis Stochastic Methods in Asset Pricing by : Andrew Lyasoff

Download or read book Stochastic Methods in Asset Pricing written by Andrew Lyasoff and published by MIT Press. This book was released on 2017-08-25 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of the theory of stochastic processes and its connections to asset pricing, accompanied by some concrete applications. This book presents a self-contained, comprehensive, and yet concise and condensed overview of the theory and methods of probability, integration, stochastic processes, optimal control, and their connections to the principles of asset pricing. The book is broader in scope than other introductory-level graduate texts on the subject, requires fewer prerequisites, and covers the relevant material at greater depth, mainly without rigorous technical proofs. The book brings to an introductory level certain concepts and topics that are usually found in advanced research monographs on stochastic processes and asset pricing, and it attempts to establish greater clarity on the connections between these two fields. The book begins with measure-theoretic probability and integration, and then develops the classical tools of stochastic calculus, including stochastic calculus with jumps and Lévy processes. For asset pricing, the book begins with a brief overview of risk preferences and general equilibrium in incomplete finite endowment economies, followed by the classical asset pricing setup in continuous time. The goal is to present a coherent single overview. For example, the text introduces discrete-time martingales as a consequence of market equilibrium considerations and connects them to the stochastic discount factors before offering a general definition. It covers concrete option pricing models (including stochastic volatility, exchange options, and the exercise of American options), Merton's investment–consumption problem, and several other applications. The book includes more than 450 exercises (with detailed hints). Appendixes cover analysis and topology and computer code related to the practical applications discussed in the text.


Stochastic Methods in Asset Pricing Related Books

Stochastic Methods in Asset Pricing
Language: en
Pages: 632
Authors: Andrew Lyasoff
Categories: Business & Economics
Type: BOOK - Published: 2017-08-25 - Publisher: MIT Press

DOWNLOAD EBOOK

A comprehensive overview of the theory of stochastic processes and its connections to asset pricing, accompanied by some concrete applications. This book presen
Stochastic Methods in Neuroscience
Language: en
Pages: 399
Authors: Carlo Laing
Categories: Mathematics
Type: BOOK - Published: 2010 - Publisher: Oxford University Press

DOWNLOAD EBOOK

Great interest is now being shown in computational and mathematical neuroscience, fuelled in part by the rise in computing power, the ability to record large am
Stochastic Methods and their Applications to Communications
Language: en
Pages: 446
Authors: Serguei Primak
Categories: Technology & Engineering
Type: BOOK - Published: 2005-01-28 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Stochastic Methods & their Applications to Communications presents a valuable approach to the modelling, synthesis and numerical simulation of random processes
Stochastic Processes in Physics and Chemistry
Language: en
Pages: 482
Authors: N.G. Van Kampen
Categories: Science
Type: BOOK - Published: 1992-11-20 - Publisher: Elsevier

DOWNLOAD EBOOK

This new edition of Van Kampen's standard work has been completely revised and updated. Three major changes have also been made. The Langevin equation receives
Stochastic Methods
Language: en
Pages: 0
Authors: Crispin Gardiner
Categories: Science
Type: BOOK - Published: 2010-10-19 - Publisher: Springer

DOWNLOAD EBOOK

In the third edition of this classic the chapter on quantum Marcov processes has been replaced by a chapter on numerical treatment of stochastic differential eq