Quantitative Methods in Derivatives Pricing

An Introduction to Computational Finance

Author: Domingo Tavella

Publisher: John Wiley & Sons

ISBN: 9780471274797

Category: Business & Economics

Page: 304

View: 3048

This book presents a cogent description of the main methodologiesused in derivatives pricing. Starting with a summary of theelements of Stochastic Calculus, Quantitative Methods inDerivatives Pricing develops the fundamental tools of financialengineering, such as scenario generation, simulation for Europeaninstruments, simulation for American instruments, and finitedifferences in an intuitive and practical manner, with an abundanceof practical examples and case studies. Intended primarily as anintroductory graduate textbook in computational finance, this bookwill also serve as a reference for practitioners seeking basicinformation on alternative pricing methodologies. Domingo Tavella is President of Octanti Associates, aconsulting firm in risk management and financial systems design. Heis the founder and chief editor of the Journal of ComputationalFinance and has pioneered the application of advanced numericaltechniques in pricing and risk analysis in the financial andinsurance industries. Tavella coauthored Pricing FinancialInstruments: The Finite Difference Method. He holds a PhD inaeronautical engineering from Stanford University and an MBA infinance from the University of California at Berkeley.

Quantitative Methods in Finance

Author: Terry J. Watsham,Keith Parramore

Publisher: Cengage Learning EMEA

ISBN: 9781861523679

Category: Business & Economics

Page: 395

View: 1328

This text explains in an intuitive yet rigorous way the mathematical and statistical applications relevant to modern financial instruments and risk management techniques. It progresses at a pace that is comfortable for those with less mathematical expertise yet reaches a level of analysis that will reward even the most experienced. The strong applied emphasis makes this book ideal for anyone who is seriously interested in mastering the quantitative techniques underpinning modern financial decision making.

Derivatives and Equity Portfolio Management

Author: Bruce M. Collins,Frank J. Fabozzi, CFA

Publisher: John Wiley & Sons

ISBN: 9781883249601

Category: Business & Economics

Page: 230

View: 4685

Frank Fabozzi and Bruce Collins fully outline the ins and outs of the derivatives process for equity investors in Derivatives and Equity Portfolio Management. A significant investment tool of growing interest, derivatives offer investors options for managing risk in a diversified portfolio. This in-depth guide integrates the derivatives process into portfolio management and is replete with applications from authors with extensive Wall Street experience. Whether you're and individual investor or portfolio manager seeking to improve investment returns, you'll quickly learn about listed equity contracts, using listed options in equity portfolio management, risk management with stock index futures, OTC equity derivatives-and profit from your new found knowledge.

Market Risk Analysis, Quantitative Methods in Finance

Author: Carol Alexander

Publisher: John Wiley & Sons

ISBN: 047077102X

Category: Business & Economics

Page: 318

View: 3376

Written by leading market risk academic, Professor Carol Alexander, Quantitative Methods in Finance forms part one of the Market Risk Analysis four volume set. Starting from the basics, this book helps readers to take the first step towards becoming a properly qualified financial risk manager and asset manager, roles that are currently in huge demand. Accessible to intelligent readers with a moderate understanding of mathematics at high school level or to anyone with a university degree in mathematics, physics or engineering, no prior knowledge of finance is necessary. Instead the emphasis is on understanding ideas rather than on mathematical rigour, meaning that this book offers a fast-track introduction to financial analysis for readers with some quantitative background, highlighting those areas of mathematics that are particularly relevant to solving problems in financial risk management and asset management. Unique to this book is a focus on both continuous and discrete time finance so that Quantitative Methods in Finance is not only about the application of mathematics to finance; it also explains, in very pedagogical terms, how the continuous time and discrete time finance disciplines meet, providing a comprehensive, highly accessible guide which will provide readers with the tools to start applying their knowledge immediately. All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the accompanying CD-ROM . Empirical examples and case studies specific to this volume include: Principal component analysis of European equity indices; Calibration of Student t distribution by maximum likelihood; Orthogonal regression and estimation of equity factor models; Simulations of geometric Brownian motion, and of correlated Student t variables; Pricing European and American options with binomial trees, and European options with the Black-Scholes-Merton formula; Cubic spline fitting of yields curves and implied volatilities; Solution of Markowitz problem with no short sales and other constraints; Calculation of risk adjusted performance metrics including generalised Sharpe ratio, omega and kappa indices.

Computational Methods in Finance

Author: Ali Hirsa

Publisher: CRC Press

ISBN: 1466576049

Category: Business & Economics

Page: 444

View: 2814

As today’s financial products have become more complex, quantitative analysts, financial engineers, and others in the financial industry now require robust techniques for numerical analysis. Covering advanced quantitative techniques, Computational Methods in Finance explains how to solve complex functional equations through numerical methods. The first part of the book describes pricing methods for numerous derivatives under a variety of models. The book reviews common processes for modeling assets in different markets. It then examines many computational approaches for pricing derivatives. These include transform techniques, such as the fast Fourier transform, the fractional fast Fourier transform, the Fourier-cosine method, and saddlepoint method; the finite difference method for solving PDEs in the diffusion framework and PIDEs in the pure jump framework; and Monte Carlo simulation. The next part focuses on essential steps in real-world derivative pricing. The author discusses how to calibrate model parameters so that model prices are compatible with market prices. He also covers various filtering techniques and their implementations and gives examples of filtering and parameter estimation. Developed from the author’s courses at Columbia University and the Courant Institute of New York University, this self-contained text is designed for graduate students in financial engineering and mathematical finance as well as practitioners in the financial industry. It will help readers accurately price a vast array of derivatives.

Computational Methods for Quantitative Finance

Finite Element Methods for Derivative Pricing

Author: Norbert Hilber,Oleg Reichmann,Christoph Schwab,Christoph Winter

Publisher: Springer Science & Business Media

ISBN: 3642354017

Category: Mathematics

Page: 299

View: 1474

Many mathematical assumptions on which classical derivative pricing methods are based have come under scrutiny in recent years. The present volume offers an introduction to deterministic algorithms for the fast and accurate pricing of derivative contracts in modern finance. This unified, non-Monte-Carlo computational pricing methodology is capable of handling rather general classes of stochastic market models with jumps, including, in particular, all currently used Lévy and stochastic volatility models. It allows us e.g. to quantify model risk in computed prices on plain vanilla, as well as on various types of exotic contracts. The algorithms are developed in classical Black-Scholes markets, and then extended to market models based on multiscale stochastic volatility, to Lévy, additive and certain classes of Feller processes. This book is intended for graduate students and researchers, as well as for practitioners in the fields of quantitative finance and applied and computational mathematics with a solid background in mathematics, statistics or economics.​

Quantitative Methods for Electricity Trading and Risk Management

Advanced Mathematical and Statistical Methods for Energy Finance

Author: S. Fiorenzani

Publisher: Springer

ISBN: 023059834X

Category: Business & Economics

Page: 181

View: 1879

This book presents practical Risk Management and Trading applications for the Electricity Markets. Various methodologies developed over the last few years are considered and current literature is reviewed. The book emphasizes the relationship between trading, hedging and generation asset management.

Change of Time Methods in Quantitative Finance

Author: Anatoliy Swishchuk

Publisher: Springer

ISBN: 331932408X

Category: Mathematics

Page: 128

View: 9237

This book is devoted to the history of Change of Time Methods (CTM), the connections of CTM to stochastic volatilities and finance, fundamental aspects of the theory of CTM, basic concepts, and its properties. An emphasis is given on many applications of CTM in financial and energy markets, and the presented numerical examples are based on real data. The change of time method is applied to derive the well-known Black-Scholes formula for European call options, and to derive an explicit option pricing formula for a European call option for a mean-reverting model for commodity prices. Explicit formulas are also derived for variance and volatility swaps for financial markets with a stochastic volatility following a classical and delayed Heston model. The CTM is applied to price financial and energy derivatives for one-factor and multi-factor alpha-stable Levy-based models. Readers should have a basic knowledge of probability and statistics, and some familiarity with stochastic processes, such as Brownian motion, Levy process and martingale.

The SAGE Handbook of Quantitative Methods in Psychology

Author: Roger E Millsap,Alberto Maydeu-Olivares

Publisher: SAGE

ISBN: 144620667X

Category: Psychology

Page: 800

View: 755

`I often... wonder to myself whether the field needs another book, handbook, or encyclopedia on this topic. In this case I think that the answer is truly yes. The handbook is well focused on important issues in the field, and the chapters are written by recognized authorities in their fields. The book should appeal to anyone who wants an understanding of important topics that frequently go uncovered in graduate education in psychology' - David C Howell, Professor Emeritus, University of Vermont Quantitative psychology is arguably one of the oldest disciplines within the field of psychology and nearly all psychologists are exposed to quantitative psychology in some form. While textbooks in statistics, research methods and psychological measurement exist, none offer a unified treatment of quantitative psychology. The SAGE Handbook of Quantitative Methods in Psychology does just that. Each chapter covers a methodological topic with equal attention paid to established theory and the challenges facing methodologists as they address new research questions using that particular methodology. The reader will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area. Drawing on a global scholarship, the Handbook is divided into seven parts: Part One: Design and Inference: addresses issues in the inference of causal relations from experimental and non-experimental research, along with the design of true experiments and quasi-experiments, and the problem of missing data due to various influences such as attrition or non-compliance. Part Two: Measurement Theory: begins with a chapter on classical test theory, followed by the common factor analysis model as a model for psychological measurement. The models for continuous latent variables in item-response theory are covered next, followed by a chapter on discrete latent variable models as represented in latent class analysis. Part Three: Scaling Methods: covers metric and non-metric scaling methods as developed in multidimensional scaling, followed by consideration of the scaling of discrete measures as found in dual scaling and correspondence analysis. Models for preference data such as those found in random utility theory are covered next. Part Four: Data Analysis: includes chapters on regression models, categorical data analysis, multilevel or hierarchical models, resampling methods, robust data analysis, meta-analysis, Bayesian data analysis, and cluster analysis. Part Five: Structural Equation Models: addresses topics in general structural equation modeling, nonlinear structural equation models, mixture models, and multilevel structural equation models. Part Six: Longitudinal Models: covers the analysis of longitudinal data via mixed modeling, time series analysis and event history analysis. Part Seven: Specialized Models: covers specific topics including the analysis of neuro-imaging data and functional data-analysis.

Frequently Asked Questions in Quantitative Finance

Author: Paul Wilmott

Publisher: John Wiley & Sons

ISBN: 0470972963

Category: Business & Economics

Page: 428

View: 1406

Paul Wilmott writes, "Quantitative finance is the most fascinating and rewarding real-world application of mathematics. It is fascinating because of the speed at which the subject develops, the new products and the new models which we have to understand. And it is rewarding because anyone can make a fundamental breakthrough. "Having worked in this field for many years, I have come to appreciate the importance of getting the right balance between mathematics and intuition. Too little maths and you won't be able to make much progress, too much maths and you'll be held back by technicalities. I imagine, but expect I will never know for certain, that getting the right level of maths is like having the right equipment to climb Mount Everest; too little and you won't make the first base camp, too much and you'll collapse in a heap before the top. "Whenever I write about or teach this subject I also aim to get the right mix of theory and practice. Finance is not a hard science like physics, so you have to accept the limitations of the models. But nor is it a very soft science, so without those models you would be at a disadvantage compared with those better equipped. I believe this adds to the fascination of the subject. "This FAQs book looks at some of the most important aspects of financial engineering, and considers them from both theoretical and practical points of view. I hope that you will see that finance is just as much fun in practice as in theory, and if you are reading this book to help you with your job interviews, good luck! Let me know how you get on!"

Introduction to Quantitative Methods for Financial Markets

Author: Hansjoerg Albrecher,Andreas Binder,Volkmar Lautscham,Philipp Mayer

Publisher: Springer Science & Business Media

ISBN: 3034805195

Category: Mathematics

Page: 191

View: 7167

Swaps, futures, options, structured instruments - a wide range of derivative products is traded in today's financial markets. Analyzing, pricing and managing such products often requires fairly sophisticated quantitative tools and methods. This book serves as an introduction to financial mathematics with special emphasis on aspects relevant in practice. In addition to numerous illustrative examples, algorithmic implementations are demonstrated using "Mathematica" and the software package "UnRisk" (available for both students and teachers). The content is organized in 15 chapters that can be treated as independent modules. In particular, the exposition is tailored for classroom use in a Bachelor or Master program course, as well as for practitioners who wish to further strengthen their quantitative background.

Multi-moment Asset Allocation and Pricing Models

Author: Emmanuel Jurczenko,Bertrand Maillet

Publisher: John Wiley & Sons

ISBN: 0470057998

Category: Business & Economics

Page: 258

View: 3588

While mainstream financial theories and applications assume that asset returns are normally distributed and individual preferences are quadratic, the overwhelming empirical evidence shows otherwise. Indeed, most of the asset returns exhibit “fat-tails” distributions and investors exhibit asymmetric preferences. These empirical findings lead to the development of a new area of research dedicated to the introduction of higher order moments in portfolio theory and asset pricing models. Multi-moment asset pricing is a revolutionary new way of modeling time series in finance which allows various degrees of long-term memory to be generated. It allows risk and prices of risk to vary through time enabling the accurate valuation of long-lived assets. This book presents the state-of-the art in multi-moment asset allocation and pricing models and provides many new developments in a single volume, collecting in a unified framework theoretical results and applications previously scattered throughout the financial literature. The topics covered in this comprehensive volume include: four-moment individual risk preferences, mathematics of the multi-moment efficient frontier, coherent asymmetric risks measures, hedge funds asset allocation under higher moments, time-varying specifications of (co)moments and multi-moment asset pricing models with homogeneous and heterogeneous agents. Written by leading academics, Multi-moment Asset Allocation and Pricing Models offers a unique opportunity to explore the latest findings in this new field of research.

Quantitative Energy Finance

Modeling, Pricing, and Hedging in Energy and Commodity Markets

Author: Fred Espen Benth,Valery A. Kholodnyi,Peter Laurence

Publisher: Springer Science & Business Media

ISBN: 1461472482

Category: Business & Economics

Page: 308

View: 6955

Finance and energy markets have been an active scientific field for some time, even though the development and applications of sophisticated quantitative methods in these areas are relatively new—and referred to in a broader context as energy finance. Energy finance is often viewed as a branch of mathematical finance, yet this area continues to provide a rich source of issues that are fuelling new and exciting research developments. Based on a special thematic year at the Wolfgang Pauli Institute (WPI) in Vienna, Austria, this edited collection features cutting-edge research from leading scientists in the fields of energy and commodity finance. Topics discussed include modeling and analysis of energy and commodity markets, derivatives hedging and pricing, and optimal investment strategies and modeling of emerging markets, such as power and emissions. The book also confronts the challenges one faces in energy markets from a quantitative point of view, as well as the recent advances in solving these problems using advanced mathematical, statistical and numerical methods. By addressing the emerging area of quantitative energy finance, this volume will serve as a valuable resource for graduate-level students and researchers studying financial mathematics, risk management, or energy finance.

Financial Mathematics

A Comprehensive Treatment

Author: Giuseppe Campolieti,Roman N. Makarov

Publisher: CRC Press

ISBN: 1315360489

Category: Business & Economics

Page: 829

View: 4355

Versatile for Several Interrelated Courses at the Undergraduate and Graduate Levels Financial Mathematics: A Comprehensive Treatment provides a unified, self-contained account of the main theory and application of methods behind modern-day financial mathematics. Tested and refined through years of the authors’ teaching experiences, the book encompasses a breadth of topics, from introductory to more advanced ones. Accessible to undergraduate students in mathematics, finance, actuarial science, economics, and related quantitative areas, much of the text covers essential material for core curriculum courses on financial mathematics. Some of the more advanced topics, such as formal derivative pricing theory, stochastic calculus, Monte Carlo simulation, and numerical methods, can be used in courses at the graduate level. Researchers and practitioners in quantitative finance will also benefit from the combination of analytical and numerical methods for solving various derivative pricing problems. With an abundance of examples, problems, and fully worked out solutions, the text introduces the financial theory and relevant mathematical methods in a mathematically rigorous yet engaging way. Unlike similar texts in the field, this one presents multiple problem-solving approaches, linking related comprehensive techniques for pricing different types of financial derivatives. The book provides complete coverage of both discrete- and continuous-time financial models that form the cornerstones of financial derivative pricing theory. It also presents a self-contained introduction to stochastic calculus and martingale theory, which are key fundamental elements in quantitative finance.

Implementing Models in Quantitative Finance: Methods and Cases

Author: Gianluca Fusai,Andrea Roncoroni

Publisher: Springer Science & Business Media

ISBN: 9783540499596

Category: Business & Economics

Page: 607

View: 6369

This book puts numerical methods in action for the purpose of solving practical problems in quantitative finance. The first part develops a toolkit in numerical methods for finance. The second part proposes twenty self-contained cases covering model simulation, asset pricing and hedging, risk management, statistical estimation and model calibration. Each case develops a detailed solution to a concrete problem arising in applied financial management and guides the user towards a computer implementation. The appendices contain "crash courses" in VBA and Matlab programming languages.