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Saddlepoint Approximation Methods in Financial Engineering

  • Yue Kuen Kwok
  • Wendong Zheng

Part of the SpringerBriefs in Quantitative Finance book series (BRIEFFINANCE)

Table of contents

  1. Front Matter
    Pages i-x
  2. Yue Kuen Kwok, Wendong Zheng
    Pages 1-9
  3. Yue Kuen Kwok, Wendong Zheng
    Pages 57-71
  4. Yue Kuen Kwok, Wendong Zheng
    Pages 73-95
  5. Yue Kuen Kwok, Wendong Zheng
    Pages 97-122
  6. Back Matter
    Pages 123-128

About this book

Introduction

This book summarizes recent advances in applying saddlepoint approximation methods to financial engineering. It addresses pricing exotic financial derivatives and calculating risk contributions to Value-at-Risk and Expected Shortfall in credit portfolios under various default correlation models. These standard problems involve the computation of tail probabilities and tail expectations of the corresponding underlying state variables. 

The text offers in a single source most of the saddlepoint approximation results in financial engineering, with different sets of ready-to-use approximation formulas. Much of this material may otherwise only be found in original research publications. The exposition and style are made rigorous by providing formal proofs of most of the results.

Starting with a presentation of the derivation of a variety of saddlepoint approximation formulas in different contexts, this book will help new researchers to learn the fine technicalities of the topic. It will also be valuable to quantitative analysts in financial institutions who strive for effective valuation of prices of exotic financial derivatives and risk positions of portfolios of risky instruments.

 

Keywords

62P05;62E17;44A10 Saddlepoint approximation derivatives pricing risk measures financial engineering credit portfolios

Authors and affiliations

  • Yue Kuen Kwok
    • 1
  • Wendong Zheng
    • 2
  1. 1.Department of MathematicsHong Kong University of Science and TechnologyHong KongChina
  2. 2.Department of MathematicsHong Kong University of Science and TechnologyHong KongChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-74101-7
  • Copyright Information The Author(s) 2018
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-74100-0
  • Online ISBN 978-3-319-74101-7
  • Series Print ISSN 2192-7006
  • Series Online ISSN 2192-7014
  • Buy this book on publisher's site