Bøger i Chapman & Hall/CRC Financial Mathematics Series serien

Presents an overview of the theoretical, numerical, and empirical aspects of using jump processes in financial modeling. This book demonstrates that the concepts and tools necessary for understanding and implementing models with jumps can be more intuitive that those involved in the Black Scholes and diffusion models.

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.

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 With many unpublished results and insights, the book addresses the practicalities of modeling local volatility, local-stochastic volatility, and multi-asset stochastic volatility.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.

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.

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.

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.

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.

Applies advanced analytical and geometrical methods used in physics and mathematics to the financial field. This work introduces tools and methods, including differential geometry, spectral decomposition, and supersymmetry, and applies these methods to practical problems in finance. It focuses on the calibration and dynamics of implied volatility.

Presents both standard and novel results on the axiomatics of the individual choice in an uncertain framework. This work offers an overview of standard portfolio optimization. It provides a review of the main results for static and dynamic cases. It shows how theoretical results can be applied to practical and operational portfolio optimization.

Offers a treatment of option pricing with an emphasis on the valuation of American options on dividend-paying assets. This book reviews valuation principles for European contingent claims and analyses the American contingent claims. It presents basic valuation principles for American options including barrier, capped, and multi-asset options.

Suitable for professionals, this title covers the key methods and models of quantitative finance from the perspective of their implementation in C++. It introduces computational finance in a pragmatic manner, focusing on practical implementation.

Risk management combines considerable quantitative skills with practical and intuitive competencies. Presenting both mathematical aspects and practical skills, this book introduces the foundations of risk management and shows how these concepts are used to create practical risk management systems.

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.

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

Emphasizing the need for knowledge of modern finance theory in portfolio management, this text explains why theory should precede mathematics when it comes to money management. It presents key concepts underlying portfolio management theory, followed by examples and applied exercises to enforce understanding of concepts and principles.

Suitable for students of mathematical finance, or a quick introduction to researchers and finance practitioners. This book covers the stochastic calculus theory required, as well as many key finance topics, including a chapter dedicated to credit risk modeling.

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.

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.

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.

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.

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.

Offering insight into how the financial system works and how the credit crisis arose, this book provides a comprehensive account of the credit crunch that is easily understandable to non-specialists. It explains how the financial system was drawn into the crunch and the issues that need to be addressed to prevent further disasters.

Reviews quantitative investment strategies and factors that are commonly used in practice, including value, momentum, and quality, accompanied by their academic origins. This work presents advanced techniques and applications in return forecasting models, risk management, portfolio construction, and portfolio implementation.