1.

Record Nr.

UNINA9910254099303321

Autore

Bouchard Bruno

Titolo

Fundamentals and Advanced Techniques in Derivatives Hedging [[electronic resource] /] / by Bruno Bouchard, Jean-François Chassagneux

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016

ISBN

3-319-38990-4

Edizione

[1st ed. 2016.]

Descrizione fisica

1 online resource (XII, 280 p.)

Collana

Universitext, , 0172-5939

Disciplina

650.01513

Soggetti

Economics, Mathematical 

Probabilities

Partial differential equations

Calculus of variations

Quantitative Finance

Probability Theory and Stochastic Processes

Partial Differential Equations

Calculus of Variations and Optimal Control; Optimization

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Part A. Fundamental theorems -- Discrete time models -- Continuous time models -- Optimal management and price selection.- Part B. Markovian models and PDE approach -- Delta hedging in complete market -- Super-replication and its practical limits -- Hedging under loss contraints.- Part C. Practical implementation in local and stochastic volatility models -- Local volatility models -- Stochastic volatility models -- References.

Sommario/riassunto

This book covers the theory of derivatives pricing and hedging as well as techniques used in mathematical finance. The authors use a top-down approach, starting with fundamentals before moving to applications, and present theoretical developments alongside various exercises, providing many examples of practical interest. A large spectrum of concepts and mathematical tools that are usually found in separate monographs are presented here. In addition to the no-



arbitrage theory in full generality, this book also explores models and practical hedging and pricing issues. Fundamentals and Advanced Techniques in Derivatives Hedging further introduces advanced methods in probability and analysis, including Malliavin calculus and the theory of viscosity solutions, as well as the recent theory of stochastic targets and its use in risk management, making it the first textbook covering this topic. Graduate students in applied mathematics with an understanding of probability theory and stochastic calculus will find this book useful to gain a deeper understanding of fundamental concepts and methods in mathematical finance.