Books in the Chapman & Hall/CRC Financial Mathematics Series series

This book is a comprehensive, self-contained, and unified treatment of the main theory and application of mathematical methods behind modern-day financial mathematics.

Presents techniques that originate from practical problems and that address real requirements. This book introduces the standard lognormal flat BGM and then discusses shifted versions of BGM, including stochastic volatility version. It covers topics such as simulation, time slicing, pricing, delta hedging, vega hedging, and callable exotics.

Offers a hands-on introduction to mathematical finance. This title includes the relevant mathematical background as well as many exercises with solutions. It presents the classical topics of utility and the mean-variance approach to portfolio choice.

This textbook is designed to enable students with little knowledge of mathematical analysis to engage with modern quantitative finance. The exposition of the topics is concise as chapters are intended to represent a preliminary contact with the mathematical concepts used in QF.

Written from the perspective of practitioners who apply mathematical concepts to structured credit products, Structured Credit Portfolio Analysis starts with a brief wrap-up on basic concepts of credit risk modeling and then quickly moves on to more advanced topics such as the modeling and evaluation of basket products, credit-linked notes referenced to credit portfolios, collateralized debt obligations, and index tranches. This unique critically acclaimed volume is written in a self-contained style so readers with a basic understanding of probability will have no difficulty following it. In addition, many examples and calculations have been included to keep the discussion close to business applications.

Containing many results that are new or exist only in recent research articles, Interest Rate Modeling: Theory and Practice portrays the theory of interest rate modeling as a three-dimensional object of finance, mathematics, and computation.

This book covers statistical inference for copula and tail copula models with applications in finance, insurance and risk management.

The book will be devoted to quantitative models and computational techniques for risk management of equity-linked insurance. Although there have been research papers on the valuation of a great variety of investment guarantee products, they were primarily based on financial option pricing theory from the policyholders¿ perspective. This book is aimed at addressing the risk management issues from the insurer and regulator¿s viewpoints.

This book provides analysis of the effects of portfolio rebalancing on portfolio returns and risks, examining when and why fixed-weight portfolios might outperform buy-and-hold portfolios, and the effects of portfolio rebalancing in capital markets and understand why many capitalization-weighted indices underperform fixed-weight portfolios.

Written by a leading contributor to volatility modeling and Risk?s 2009 Quant of the Year, this book explains how stochastic volatility is used to tackle practical issues arising in the modeling of derivatives. With many unpublished results and insights, the book addresses the practicalities of modeling local volatility, local-stochastic volatility, and multi-asset stochastic volatility. It covers forward-start options, variance swaps, options on realized variance, timer options, VIX futures and options, and daily cliquets.

If you know a little bit about financial mathematics but don¿t yet know a lot about programming, then C++ for Financial Mathematics is for you.C++ is an essential skill for many jobs in quantitative finance, but learning it can be a daunting prospect. This book gathers together everything you need to know to price derivatives in C++ without unnecessary complexities or technicalities. It leads the reader step-by-step from programming novice to writing a sophisticated and flexible financial mathematics library. At every step, each new idea is motivated and illustrated with concrete financial examples.

This book focuses on the application of the partial hedging approach from modern math finance to equity-linked life insurance contracts. It provides an accessible, up-to-date introduction to quantifying financial and insurance risks. The book also explains how to price innovative financial and insurance products from partial hedging perspectives.

This classroom-tested text provides a deep understanding of derivative contracts. Unlike much of the existing literature, the book treats price as a number of units of one asset needed for an acquisition of a unit of another asset instead of expressing prices in dollar terms exclusively. This numeraire approach leads to simpler pricing options for complex products, such as barrier, lookback, quanto, and Asian options. With many examples and exercises, the text relies on intuition and basic principles, rather than technical computations.

Intended for practitioners, researchers and graduate students in quantitative finance, computer science and related fields, this book serves as a handbook for design and implementation of financial models with relevant numerical methods on different HPC platforms in banks, insurance companies, pensions, asset-management companies and trading firms.

This book is among the first to present the mathematical models most commonly used to solve optimal execution problems and market making problems in finance. The Financial Mathematics of Market Liquidity: From Optimal Execution to Market Making presents a general modeling framework for optimal execution problemsΓÇôinspired from the Almgren-Chriss approachΓÇôand then demonstrates the use of that framework across a wide range of areas.The book introduces the classical tools of optimal execution and market making, along with their practical use. It also demonstrates how the tools used in the optimal execution literature can be used to solve classical and new issues where accounting for liquidity is important. In particular, it presents cutting-edge research on the pricing of block trades, the pricing and hedging of options when liquidity matters, and the management of complex share buy-back contracts.What sets this book apart from others is that it focuses on specific topics that are rarely, or only briefly, tackled in books dealing with market microstructure. It goes far beyond existing books in terms of mathematical modelingΓÇôbridging the gap between optimal execution and other fields of Quantitative Finance.The book includes two appendices dedicated to the mathematical notions used throughout the book. Appendix A recalls classical concepts of mathematical economics. Appendix B recalls classical tools of convex analysis and optimization, along with central ideas and results of the calculus of variations.This self-contained book is accessible to anyone with a minimal background in mathematical analysis, dynamic optimization, and stochastic calculus. Covering post-electronification financial markets and liquidity issues for pricing, this book is an ideal resource to help investment banks and asset managers optimize trading strategies and improve overall risk management.

Written by a well-known expert of asset management and risk parity, this book provides an up-to-date treatment of the risk parity approach, an alternative method to Markowitz optimization. It builds financial exposure to equities and commodities, considers credit risk in the management of bond portfolios, and designs long-term investment policy. The first part of the book gives a theoretical account of portfolio optimization and risk parity. Each chapter in the second part presents an application of risk parity to a specific asset class.

This text addresses a variety of numerical methods for pricing derivative contracts, including Fourier techniques, finite differences, numerical simulation, and Monte Carlo simulation methods one of the first books to cover all of these techniques. After presenting the basics of pricing techniques, it covers key concepts of calibration and parameter estimation. Written by a popular professor at Columbia University and NYU 's Courant Institute, the book is suitable for any graduate course on computational finance in financial engineering and financial mathematics programs as well as for practitioners interested in computational methods in finance.

Written by two leaders in quantitative research, this book compares various numerical methods for solving high-dimensional nonlinear problems arising in option pricing. Designed for practitioners, it is the first authored book to discuss nonlinear Black-Scholes PDEs and compare the efficiency of many different methods, including novel techniques for pricing options, calibrating models, and more. The book helps quants develop both their analytical and numerical expertise, building intuition through numerous real-world examples of numerical implementation.

Incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. This book presents the methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as financial and actuarial models.

Shows how the mathematical tools of linear algebra and optimization can quickly and clearly formulate important ideas on the subject. This book covers the concepts of the Markowitz 'budget constraint only' model to a linearly constrained model. It explains how the basic portfolio optimization problem can help determine the optimal investment.

Illustrating mathematical models for structured credit with practical examples, this book presents an introduction to the foundations of structured credit portfolio modeling. It features material on estimation of asset correlations, and benchmark correlations based on securitizations of benchmark portfolios in the market.