Fast Relevant Simulation in Finance: Application to Risk Management (Value at Risk) - Couverture souple

Iwasawa, Kazuhiro

 
9783846522615: Fast Relevant Simulation in Finance: Application to Risk Management (Value at Risk)
Couverture souple
ISBN 10 : 3846522619 ISBN 13 : 9783846522615
Editeur : LAP LAMBERT Academic Publishing, 2011

Synopsis

This book introduces new Monte Carlo methods for computing Value-at-Risk(VAR) in finance. 2 major cases (i.i.d. Monte Carlo and Markov Chain Monte Carlo) are treated in this book. New i.i.d Monte Carlo technique is based on the combination of importance sampling, non-linear optimization, and newly proposed exponential twisting density. Its theoretical justification will also be given based on the Large Deviation Theory and the Laplace method. For the Markov Chain Monte Carlo, this book introduces new techniques based on Metropolis-within-Gibbs algorithm combined with Robbins-Monro algorithm from stochastic approximation theory. Its theoretical justification will be given motivated by Ergodic Theory as well. Recently (especially after the financial crisis of 2008), industry practitioners started seeking more general non-Gaussian distribution (historical simulation, etc) and Markov Chain Monte Carlo can be used to deal with such cases. Although this book deals extensively with new techniques for VaR calculation, later chapter of this book contains several examples of its application to pricing various far out of the money options/basket options/Asian options/American options.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

This book introduces new Monte Carlo methods for computing Value-at-Risk(VAR) in finance. 2 major cases (i.i.d. Monte Carlo and Markov Chain Monte Carlo) are treated in this book. New i.i.d Monte Carlo technique is based on the combination of importance sampling, non-linear optimization, and newly proposed exponential twisting density. Its theoretical justification will also be given based on the Large Deviation Theory and the Laplace method. For the Markov Chain Monte Carlo, this book introduces new techniques based on Metropolis-within-Gibbs algorithm combined with Robbins-Monro algorithm from stochastic approximation theory. Its theoretical justification will be given motivated by Ergodic Theory as well. Recently (especially after the financial crisis of 2008), industry practitioners started seeking more general non-Gaussian distribution (historical simulation, etc) and Markov Chain Monte Carlo can be used to deal with such cases. Although this book deals extensively with new techniques for VaR calculation, later chapter of this book contains several examples of its application to pricing various far out of the money options/basket options/Asian options/American options.

Biographie de l'auteur

Kazuhiro Iwasawa currently works as a senior financial engineer at Bloomberg LP. He also held similar positions at Royal Bank of Scotland & Resona Holdings, and has over 15 years of industry experience. He holds PhD in Mathematics from New York University (Courant Institute). His specialty is Monte Carlo Simulation & Stochastic Optimization.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2011
Langue
anglais
ISBN 10 
3846522619
ISBN 13 
9783846522615
Reliure
Broché
Nombre de pages
112
Coordonnées du fabricant
non disponible
Personne responsable
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