Monte Carlo Methods in Financial Engineering (Stochastic Modelling and Applied Probability) (v. 53)

✍ Scribed by Paul Glasserman

Publisher: Springer
Year: 2003
Tongue: English
Leaves: 599
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not." --Glyn Holton, Contingency Analysis

📜 SIMILAR VOLUMES

Monte Carlo Methods in Financial Enginee

📁 Monte Carlo Methods in Financial Engineering: v. 53

✍ Paul Glasserman 📂 Library 📅 2003 🏛 Springer 🌐 English

Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques. <P>This book develops the use of Monte Carlo method

Martingale Methods in Financial Modellin

📁 Martingale Methods in Financial Modelling (Stochastic Modelling and Applied Probability)

✍ Marek Musiela, Marek Rutkowski 📂 Library 📅 2009 🏛 Springer 🌐 English

A new edition of a successful, well-established book that provides the reader with a text focused on practical rather than theoretical aspects of financial modelling Includes a new chapter devoted to volatility risk The theme of stochastic volatility reappears systematically and has been revised f

Stochastic Calculus and Financial Applic

📁 Stochastic Calculus and Financial Applications (Stochastic Modelling and Applied Probability 45)

✍ J. Michael Steele 📂 Library 📅 2000 🏛 Springer 🌐 English

Stochastic calculus has important applications to mathematical finance. This book will appeal to practitioners and students who want an elementary introduction to these areas. From the reviews: "As the preface says, ‘This is a text with an attitude, and it is designed to reflect, wherever possible a

Image Analysis, Random Fields and Markov

📁 Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability)

✍ Gerhard Winkler 📂 Library 📅 2012 🏛 Springer 🌐 English

<span>This second edition of G. Winkler's successful book on random field approaches to image analysis, related Markov Chain Monte Carlo methods, and statistical inference with emphasis on Bayesian image analysis concentrates more on general principles and models and less on details of concrete appl

MONTE CARLO METHODS IN FINANCIAL ENGINEE

📁 MONTE CARLO METHODS IN FINANCIAL ENGINEERING

✍ GLASSERMAN 📂 Library 📅 2004 🏛 Springer 🌐 English

Monte Carlo methods in financial enginee

📁 Monte Carlo methods in financial engineering

✍ Paul Glasserman 📂 Library 📅 2004 🏛 Springer 🌐 English

Applied financial econometrics subjects are featured in this second volume, with papers that survey important research even as they make unique empirical contributions to the literature. These subjects are familiar: portfolio choice, trading volume, the risk-return tradeoff, option pricing, bond yie