Recommending Books for Purchase (Bulletin 102 - Aug 2020): Quantitative Finance

Employee stock options (ESOs) are an integral component of compensation in the US. In fact, almost all S&P 500 companies grant options to their top executives, and the total value accounts for almost half of the total pay for their CEOs. In view of the extensive use and significant cost of ESOs to firms, the Financial Accounting Standards Board (FASB) has mandated expensing ESOs since 2004. This gives rise to the need to create a reasonable valuation method for these options for most firms that grant ESOs to their employees. The valuation of ESOs involves a number of challenging issues, and is thus an important active research area in Accounting, Corporate Finance, and Financial Mathematics.In this exciting book, the author discusses the practical and challenging problems surrounding ESOs from a financial mathematician's perspective. This book provides a systematic overview of the contractual features of ESOs and thoughtful discussions of different valuation approaches, with emphasis on three major aspects: (i) hedging strategies; (ii) exercise timing; and (iii) valuation methodologies. In addition to addressing each of these categories, this book also highlights their connections and combined effects of the cost of ESOs to firms, as well as examines the implications to modeling and valuation approaches. The book features a unique approach that combines stochastic modeling and control techniques with option pricing theory, and provides formulas and numerical schemes for fast implementation and clear illustration.

eBook Price : $88

In the field of financial risk management, the 'sell side' is the set of financial institutions who offer risk management products to corporations, governments, and institutional investors, who comprise the 'buy side'. The sell side is often at a significant advantage as it employs quantitative experts who provide specialized knowledge. Further, the existing body of knowledge on risk management, while extensive, is highly technical and mathematical and is directed to the sell side.This book levels the playing field by approaching risk management from the buy side instead, focusing on educating corporate and institutional users of risk management products on the essential knowledge they need to be an intelligent buyer. Rather than teach financial engineering, this volume covers the principles that the buy side should know to enable it to ask the right questions and avoid being misled by the complexity often presented by the sell side.Written in a user-friendly manner, this textbook is ideal for graduate and advanced undergraduate classes in finance and risk management, MBA students specializing in finance, and corporate and institutional investors. The text is accompanied by extensive supporting material including exhibits, end-of-chapter questions and problems, solutions, and PowerPoint slides for lecturers.

eBook Price : $148

The concept of local volatility as well as the local volatility model are one of the classical topics of mathematical finance. Although the existing literature is wide, there still exist various problems that have not drawn sufficient attention so far, for example: a) construction of analytical solutions of the Dupire equation for an arbitrary shape of the local volatility function; b) construction of parametric or non-parametric regression of the local volatility surface suitable for fast calibration; c) no-arbitrage interpolation and extrapolation of the local and implied volatility surfaces; d) extension of the local volatility concept beyond the Black-Scholes model, etc. Also, recent progresses in deep learning and artificial neural networks as applied to financial engineering have made it reasonable to look again at various classical problems of mathematical finance including that of building a no-arbitrage local/implied volatility surface and calibrating it to the option market data.This book was written with the purpose of presenting new results previously developed in a series of papers and explaining them consistently, starting from the general concept of Dupire, Derman and Kani and then concentrating on various extensions proposed by the author and his co-authors. This volume collects all the results in one place, and provides some typical examples of the problems that can be efficiently solved using the proposed methods. This also results in a faster calibration of the local and implied volatility surfaces as compared to standard approaches.The methods and solutions presented in this volume are new and recently published, and are accompanied by various additional comments and considerations. Since from the mathematical point of view, the level of details is closer to the applied rather than to the abstract or pure theoretical mathematics, the book could also be recommended to graduate students with majors in computational or quantitative finance, financial engineering or even applied mathematics. In particular, the author used to teach some topics of this book as a part of his special course on computational finance at the Tandon School of Engineering, New York University.

eBook Price : $88

This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.

eBook Price : $1399

The study of heavy-tailed distributions allows researchers to represent phenomena that occasionally exhibit very large deviations from the mean. The dynamics underlying these phenomena is an interesting theoretical subject, but the study of their statistical properties is in itself a very useful endeavor from the point of view of managing assets and controlling risk. In this book, the authors are primarily concerned with the statistical properties of heavy-tailed distributions and with the processes that exhibit jumps. A detailed overview with a Matlab implementation of heavy-tailed models applied in asset management and risk managements is presented. The book is not intended as a theoretical treatise on probability or statistics, but as a tool to understand the main concepts regarding heavy-tailed random variables and processes as applied to real-world applications in finance. Accordingly, the authors review approaches and methodologies whose realization will be useful for developing new methods for forecasting of financial variables where extreme events are not treated as anomalies, but as intrinsic parts of the economic process.

eBook Price : $188

Written by two of the most distinguished finance scholars in the industry, this introductory textbook on derivatives and risk management is highly accessible in terms of the concepts as well as the mathematics.With its economics perspective, this rewritten and streamlined second edition textbook, is closely connected to real markets, and: Beginning at a level that is comfortable to lower division college students, the book gradually develops the content so that its lessons can be profitably used by business majors, arts, science, and engineering graduates as well as MBAs who would work in the finance industry. Supplementary materials are available to instructors who adopt this textbook for their courses. These include: Solutions Manual with detailed solutions to nearly 500 end-of-chapter questions and problemsPowerPoint slides and a Test Bank for adoptersPRICED In line with current teaching trends, we have woven spreadsheet applications throughout the text. Our aim is for students to achieve self-sufficiency so that they can generate all the models and graphs in this book via a spreadsheet software, Price

eBook Price : $148

A class of highly mathematical algorithms works with three-dimensional (3D) data known as graphs. Our research challenge focuses on applying these algorithms to solve more complex problems with financial data, which tend to be in higher dimensions (easily over 100), based on probability distributions, with time subscripts and jumps. The 3D research analogy is to train a navigation algorithm when the way-finding coordinates and obstacles such as buildings change dynamically and are expressed in higher dimensions with jumps.Our short title 'iaai' symbolizes how investment analytics is not a simplistic reapplication of artificial intelligence (AI) techniques proven in engineering. This book presents best-of-class sophisticated techniques available today to solve high dimensional problems with properties that go deeper than what is required to solve customary problems in engineering today.Dr Bernard Lee is the Founder and CEO of HedgeSPA, which stands for Sophisticated Predictive Analytics for Hedge Funds and Institutions. Previously, he was a managing director in the Portfolio Management Group of BlackRock in New York City as well as a finance professor who has taught and guest-lectured at a number of top universities globally.

eBook Price : $98

This book discusses the interplay of stochastics (applied probability theory) and numerical analysis in the field of quantitative finance. The stochastic models, numerical valuation techniques, computational aspects, financial products, and risk management applications presented will enable readers to progress in the challenging field of computational finance.When the behavior of financial market participants changes, the corresponding stochastic mathematical models describing the prices may also change. Financial regulation may play a role in such changes too. The book thus presents several models for stock prices, interest rates as well as foreign-exchange rates, with increasing complexity across the chapters. As is said in the industry, 'do not fall in love with your favorite model.' The book covers equity models before moving to short-rate and other interest rate models. We cast these models for interest rate into the Heath-Jarrow-Morton framework, show relations between the different models, and explain a few interest rate products and their pricing.The chapters are accompanied by exercises. Students can access solutions to selected exercises, while complete solutions are made available to instructors. The MATLAB and Python computer codes used for most tables and figures in the book are made available for both print and e-book users. This book will be useful for people working in the financial industry, for those aiming to work there one day, and for anyone interested in quantitative finance. The topics that are discussed are relevant for MSc and PhD students, academic researchers, and for quants in the financial industry.

eBook Price : $58

The 2008 financial crisis shook the financial derivatives market to its core, revealing a failure to fully price the cost of doing business then. As a response to this, and to cope with regulatory demands for massively increased capital and other measures with funding cost, the pre-2008 concept of Credit Valuation Adjustment (CVA) has evolved into the far more complex hybrid Cross Valuation Adjustment (XVA).This book presents a clear and concise framework and provides key considerations for the computation of myriad adjustments to the price of financial derivatives, to fully reflect costs. XVA has been of great interest recently due to heavy funding costs (FVA), initial margin (MVA) and capital requirements (KVA) required to sustain a derivatives business since 2008, in addition to the traditional concepts of cost from counterparty default or credit deterioration (CVA), and its mirror image -- the cost of one own's default (DVA).The book takes a practitioner's perspective on the above concepts, and then provides a framework to implement such adjustments in practice. Models are presented too, taking note of what is computationally feasible in light of portfolios typical of investment banks, and the different instruments associated with these portfolios.

eBook Price : $98

The link between commodities prices and the business cycle, including variables such as real GDP, industrial production, unemployment, inflation, and market uncertainty, has often be debated in the macroeconomic literature. To quantify the impact of commodities on the economy, one can distinguish different modeling approaches. First, commodities can be represented as the pinnacle of cross-sectional financial asset prices. Second, price fluctuations due seasonal variations, to dramatic market changes, political and regulatory decisions or technological shocks may adversely impact producers who use commodities as input. This latter effect creates the so called 'commodities risk'. Additionally, commodities price fluctuations may spread off to other sectors in the economy, via contagion effects. Besides, stronger investor interest in commodities may create closer integration with conventional asset markets; as a result, the financialization process also enhances the correlation between commodity markets and financial markets.Our objective in this book, Risk Factors and Contagion in Commodity Markets and Stocks Markets, lies in answering the following research questions: What are the interactions between commodities and stock market sentiment? Do some of these markets move together overtime? Whether the financialization in energy commodities occurs after the 2008 global financial crisis? These questions are essential to understand whether commodities are driven only by their fundamentals, or whether there is also a systemic component influenced by the volatility present within the stock markets.

eBook Price : $128