Jump Diffusion and Stochastic Volatility Models in Securities Pricing | Theory and Estimation for Various Asset Classes

Mthuli Ncube (u. a.)

ISBN 10: 3659241199 / ISBN 13: 9783659241192

Published by LAP LAMBERT Academic Publishing, 2012

About this Item

Jump Diffusion and Stochastic Volatility Models in Securities Pricing | Theory and Estimation for Various Asset Classes | Mthuli Ncube (u. a.) | Taschenbuch | 124 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783659241192 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 106213083

Bibliographic Details

• Title: Jump Diffusion and Stochastic Volatility Models in Securities Pricing | Theory and Estimation for Various Asset Classes
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2012
• Language: English
• ISBN 10: 3659241199
• ISBN 13: 9783659241192
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 9D millimeters 220 millimeters width by 150 millimeters height by 9 millimeters depth
• Weight: 203 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

The extreme financial markets volatility that the financial crisis unleashed in 2008, continues to challenge researchers on how best to keep track and model such market movements. This book, entitled "Jump Diffusion and Stochastic Volatility Models in Securities Pricing", seeks to add value to the endeavor of modeling volatility and jumps across various asset classes. The aim is to improve risk management efforts and for more accurate pricing of primary and derivative securities. The book presents jump diffusion and stochastic volatility models for the movements of equities, currencies, interest rates, house prices and temperature. All asset classes demonstrate the presence of jumps and stochastic volatility in the movement of their prices.The jumps conform to the Poisson model while stochastic volatility conforms to a normal and a fat-tailed Garch models. Maximum likelihood methods are used to estimate various parameters in the mixture of distributions.

About the Author

Professor Mthuli Ncube is the Chief Economist and Vice President of the African Development Bank Group & Professor of Finance, Wits Business School, University of the Witwatersrand, South Africa. He holds a PhD in Mathematical Finance from Cambridge University, UK, was also a Lecturer in Finance at the London School of Economics, UK.