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Stochastic Methods in Asset Pricing

(Hardback)


Publishing Details

Full Title:

Stochastic Methods in Asset Pricing

Contributors:

By (Author) Andrew Lyasoff

ISBN:

9780262036559

Publisher:

MIT Press Ltd

Imprint:

MIT Press

Publication Date:

25th August 2017

Country:

United States

Classifications

Readership:

Tertiary Education

Fiction/Non-fiction:

Non Fiction

Other Subjects:

Business mathematics and systems
Stochastics

Dewey:

332.632

Physical Properties

Physical Format:

Hardback

Number of Pages:

632

Dimensions:

Width 152mm, Height 229mm, Spine 29mm

Description

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 Levy 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.

Author Bio

Andrew Lyasoff is affiliated with the Mathematical Finance Program at Boston University's Questrom School of Business.

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