Stochastic Finance: An Introduction In Discrete Time, 4 Edition

Stochastic Finance: An Introduction In Discrete Time, 4 Edition
by Hans Follmer / / / PDF, EPUB


Read Online 41.6 MB Download


This book is an introduction to financial mathematics. It is intended for graduate students in mathematics and for researchers working in academia and industry.

The focus on stochastic models in discrete time has two immediate benefits. First, the probabilistic machinery is simpler, and one can discuss right away some of the key problems in the theory of pricing and hedging of financial derivatives. Second, the paradigm of a complete financial market, where all derivatives admit a perfect hedge, becomes the exception rather than the rule. Thus, the need to confront the intrinsic risks arising from market incomleteness appears at a very early stage.

The first part of the book contains a study of a simple one-period model, which also serves as a building block for later developments. Topics include the characterization of arbitrage-free markets, preferences on asset profiles, an introduction to equilibrium analysis, and monetary measures of financial risk.

In the second part, the idea of dynamic hedging of contingent claims is developed in a multiperiod framework. Topics include martingale measures, pricing formulas for derivatives, American options, superhedging, and hedging strategies with minimal shortfall risk.

This fourth, newly revised edition contains more than one hundred exercises. It also includes material on risk measures and the related issue of model uncertainty, in particular a chapter on dynamic risk measures and sections on robust utility maximization and on efficient hedging with convex risk measures.

Contents:

Part I: Mathematical finance in one period

Arbitrage theory

Preferences

Optimality and equilibrium

Monetary measures of risk

Part II: Dynamic hedging

Dynamic arbitrage theory

American contingent claims

Superhedging

Efficient hedging

Hedging under constraints

Minimizing the hedging error

Dynamic risk measures

views: 633