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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 explains how to study risk embedded in financial transactions between the bank and its counterparty. The authors provide an analytical basis for the quantitative methodology of dynamic valuation, mitigation, and hedging of bilateral counterparty risk on over-the-counter (OTC) derivative contracts under funding constraints. They explore

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

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 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.

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.

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.

This book seeks to replace existing books with a more rigorous stand-alone text that covers fewer examples but with more proofs, and also provides example computer programs, mainly in Octave/MATLAB but also as spreadsheets and Macsyma scripts, with which students may experiment on real data.

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.

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.

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.

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.

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.

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 deriv

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.

This textbook is ideal for an undergraduate course on derivatives in a finance, economics, or financial mathematics programme. As well as covering all of the essential topics, the book also includes the basis of the numerical techniques most used in the financial industry, and their implementation in Python.

This book is a study of the mathematical ideas and techniques that are important to the two main arms of the area of Financial Mathematics: portfolio optimization and derivative valuation. The text is authored for courses taken by advanced undergraduates, MBA, or other students in quantitative finance programs.

This book provides a rigorous overview and exploration of stochastic modelling of big data in finance (BDF). The book describes various stochastic models, including multivariate models, to deal with big data in finance. This includes data in high-frequency and algorithmic trading, specifically in limit order books (LOB).

This book presents an introduction to pricing and hedging in discrete and continuous time financial models, emphasizing both analytical and probabilistic methods. It demonstrates both the power and limitations of mathematical models in finance, covering the basics of stochastic calculus for finance.