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Author: William Johnson Publisher: HiTeX Press ISBN: Category : Business & Economics Languages : en Pages : 574
Book Description
"Advanced Quantitative Finance: Trading, Risk, and Portfolio Optimization" unfolds as an essential guide for anyone eager to delve into the sophisticated world of modern finance. This comprehensive text blends theoretical underpinnings with practical insights, offering a robust exploration of the quantitative techniques driving today's markets. Each chapter systematically demystifies complex subjects—from risk management and derivatives pricing to algorithmic trading and asset pricing models—empowering readers to grasp the nuances of financial analysis with clarity and precision. Structured for both novices and seasoned professionals, the book navigates the latest advancements in machine learning, big data analytics, and behavioral finance, presenting them as indispensable tools for the contemporary financial landscape. With a focus on actionable knowledge and strategic applications, readers will gain the proficiency needed to enhance their decision-making, optimize investment portfolios, and effectively manage risk in an ever-evolving economic environment. This book is your invitation to not only understand quantitative finance but to excel in it, unlocking new levels of insight and innovation in your financial pursuits.
Author: Alonso Peña Publisher: CreateSpace ISBN: 9781508461401 Category : Languages : en Pages : 124
Book Description
Create and implement mathematical models in C++ using quantitative finance Overview Describes the key mathematical models used for price equity, currency, interest rates, and credit derivatives The complex models are explained step-by-step along with a flow chart of every implementation Illustrates each asset class with fully solved C++ examples, both basic and advanced, that support and complement the text In Detail This book will introduce you to the key mathematical models used to price financial derivatives, as well as the implementation of main numerical models used to solve them. In particular, equity, currency, interest rates, and credit derivatives are discussed. In the first part of the book, the main mathematical models used in the world of financial derivatives are discussed. Next, the numerical methods used to solve the mathematical models are presented. Finally, both the mathematical models and the numerical methods are used to solve some concrete problems in equity, forex, interest rate, and credit derivatives. The models used include the Black-Scholes and Garman-Kohlhagen models, the LIBOR market model, structural and intensity credit models. The numerical methods described are Monte Carlo simulation (for single and multiple assets), Binomial Trees, and Finite Difference Methods. You will find implementation of concrete problems including European Call, Equity Basket, Currency European Call, FX Barrier Option, Interest Rate Swap, Bankruptcy, and Credit Default Swap in C++. What you will learn from this book Solve complex pricing problems in financial derivatives using a structured approach with the Bento Box template Explore some key numerical methods including binomial trees, finite differences, and Monte Carlo simulation Develop your understanding of equity, forex, interest rate, and credit derivatives through concrete examples Implement simple and complex derivative instruments in C++ Discover the most important mathematical models used in quantitative finance today to price derivative instruments Effectively Incorporate object oriented programming (OOP) principles into the code Approach The book takes the reader through a fast but structured crash-course in quantitative finance, from theory to practice.
Author: Robert R. Reitano Publisher: MIT Press ISBN: 026201369X Category : Mathematics Languages : en Pages : 747
Book Description
An introduction to many mathematical topics applicable to quantitative finance that teaches how to “think in mathematics” rather than simply do mathematics by rote. This text offers an accessible yet rigorous development of many of the fields of mathematics necessary for success in investment and quantitative finance, covering topics applicable to portfolio theory, investment banking, option pricing, investment, and insurance risk management. The approach emphasizes the mathematical framework provided by each mathematical discipline, and the application of each framework to the solution of finance problems. It emphasizes the thought process and mathematical approach taken to develop each result instead of the memorization of formulas to be applied (or misapplied) automatically. The objective is to provide a deep level of understanding of the relevant mathematical theory and tools that can then be effectively used in practice, to teach students how to “think in mathematics” rather than simply to do mathematics by rote. Each chapter covers an area of mathematics such as mathematical logic, Euclidean and other spaces, set theory and topology, sequences and series, probability theory, and calculus, in each case presenting only material that is most important and relevant for quantitative finance. Each chapter includes finance applications that demonstrate the relevance of the material presented. Problem sets are offered on both the mathematical theory and the finance applications sections of each chapter. The logical organization of the book and the judicious selection of topics make the text customizable for a number of courses. The development is self-contained and carefully explained to support disciplined independent study as well. A solutions manual for students provides solutions to the book's Practice Exercises; an instructor's manual offers solutions to the Assignment Exercises as well as other materials.
Author: Jennifer Voitle Publisher: ISBN: Category : Business & Economics Languages : en Pages : 324
Book Description
Professional career guide from the Vault Career Library covering bond fundamentals, statistics, derivatives (with detailed Black-Scholes calculations, fixed income securities, equity markets, currency and commodity markets, risk management.
Author: Jan Kallsen Publisher: Springer ISBN: 3319458752 Category : Mathematics Languages : en Pages : 508
Book Description
This Festschrift resulted from a workshop on “Advanced Modelling in Mathematical Finance” held in honour of Ernst Eberlein’s 70th birthday, from 20 to 22 May 2015 in Kiel, Germany. It includes contributions by several invited speakers at the workshop, including several of Ernst Eberlein’s long-standing collaborators and former students. Advanced mathematical techniques play an ever-increasing role in modern quantitative finance. Written by leading experts from academia and financial practice, this book offers state-of-the-art papers on the application of jump processes in mathematical finance, on term-structure modelling, and on statistical aspects of financial modelling. It is aimed at graduate students and researchers interested in mathematical finance, as well as practitioners wishing to learn about the latest developments.
Author: William Johnson Publisher: HiTeX Press ISBN: Category : Business & Economics Languages : en Pages : 574
Book Description
"Advanced Quantitative Finance: Trading, Risk, and Portfolio Optimization" unfolds as an essential guide for anyone eager to delve into the sophisticated world of modern finance. This comprehensive text blends theoretical underpinnings with practical insights, offering a robust exploration of the quantitative techniques driving today's markets. Each chapter systematically demystifies complex subjects—from risk management and derivatives pricing to algorithmic trading and asset pricing models—empowering readers to grasp the nuances of financial analysis with clarity and precision. Structured for both novices and seasoned professionals, the book navigates the latest advancements in machine learning, big data analytics, and behavioral finance, presenting them as indispensable tools for the contemporary financial landscape. With a focus on actionable knowledge and strategic applications, readers will gain the proficiency needed to enhance their decision-making, optimize investment portfolios, and effectively manage risk in an ever-evolving economic environment. This book is your invitation to not only understand quantitative finance but to excel in it, unlocking new levels of insight and innovation in your financial pursuits.
Author: Chenghu Ma Publisher: World Scientific ISBN: 184816632X Category : Business & Economics Languages : en Pages : 818
Book Description
This book provides a broad introduction to modern asset pricing theory. The theory is self-contained and unified in presentation. Both the no-arbitrage and the general equilibrium approaches of asset pricing theory are treated coherently within the general equilibrium framework. It fills a gap in the body of literature on asset pricing for being both advanced and comprehensive. The absence of arbitrage opportunities represents a necessary condition for equilibrium in the financial markets. However, the absence of arbitrage is not a sufficient condition for establishing equilibrium. These interrelationships are overlooked by the proponents of the no-arbitrage approach to asset pricing.This book also tackles recent advancement on inversion problems raised in asset pricing theory, which include the information role of financial options and the information content of term structure of interest rates and interest rates contingent claims.The inclusion of the proofs and derivations to enhance the transparency of the underlying arguments and conditions for the validity of the economic theory made it an ideal advanced textbook or reference book for graduate students specializing in financial economics and quantitative finance. The detailed explanations will capture the interest of the curious reader, and it is complete enough to provide the necessary background material needed to delve deeper into the subject and explore the research literature.Postgraduate students in economics with a good grasp of calculus, linear algebra, and probability and statistics will find themselves ready to tackle topics covered in this book. They will certainly benefit from the mathematical coverage in stochastic processes and stochastic differential equation with applications in finance. Postgraduate students in financial mathematics and financial engineering will also benefit, not only from the mathematical tools introduced in this book, but also from the economic ideas underpinning the economic modeling of financial markets.Both these groups of postgraduate students will learn the economic issues involved in financial modeling. The book can be used as an advanced text for Masters and PhD students in all subjects of financial economics, financial mathematics, mathematical finance, and financial engineering. It is also an ideal reference for practitioners and researchers in the subjects.
Author: Jherek Healy Publisher: ISBN: Category : Languages : en Pages : 536
Book Description
In its third edition, this book presents the most significant equitya derivatives models used these days. It is not a book around esoteric or cutting-edge models, but rather a book on relatively simple and standard models, viewed from the angle of a practitioner. A few key subjects explained in this book are: cash dividends for European, American, or exotic options; issues of the Dupire local volatility model and possible fixes; finite difference techniques for American options and exotics; Non-parametric regression for American options in Monte-Carlo, randomized simulations; the particle method for stochastic-local-volatility model with quasi-random numbers; numerical methods for the variance and volatility swaps; quadratures for options under stochastic volatility models; VIX options and dividend derivatives; backward/forward representation of exotics.The January 2021 third edition adds significant details around the physical exercise feature, how to imply the Black-Scholes volatility, the projected successive over-relaxation as well as the recent policy iteration method for the pricing of American options (particularly relevant in the case of negative interest rates), the Andersen-Lake algorithm as fast pricing routine for the case of vanilla American options under the Black-Scholes model, random number generation, antithetic variates, the vectorization of the Monte-Carlo simulation, RBF interpolation of implied volatilities, the Cos method for European option under stochastic volatility models, the Vega in stochastic volatility models. The new text also includes important corrections around the pricing of forward starting and knock-in options with finite difference methods.
Author: Anatoly B. Schmidt Publisher: Elsevier ISBN: 0080492207 Category : Business & Economics Languages : en Pages : 179
Book Description
With more and more physicists and physics students exploring the possibility of utilizing their advanced math skills for a career in the finance industry, this much-needed book quickly introduces them to fundamental and advanced finance principles and methods. Quantitative Finance for Physicists provides a short, straightforward introduction for those who already have a background in physics. Find out how fractals, scaling, chaos, and other physics concepts are useful in analyzing financial time series. Learn about key topics in quantitative finance such as option pricing, portfolio management, and risk measurement. This book provides the basic knowledge in finance required to enable readers with physics backgrounds to move successfully into the financial industry. - Short, self-contained book for physicists to master basic concepts and quantitative methods of finance - Growing field—many physicists are moving into finance positions because of the high-level math required - Draws on the author's own experience as a physicist who moved into a financial analyst position
Author: Edina Berlinger Publisher: Packt Publishing Ltd ISBN: 1783552085 Category : Computers Languages : en Pages : 362
Book Description
This book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R.
Author: Hao Ni Publisher: World Scientific ISBN: 1786349388 Category : Business & Economics Languages : en Pages : 263
Book Description
In today's world, we are increasingly exposed to the words 'machine learning' (ML), a term which sounds like a panacea designed to cure all problems ranging from image recognition to machine language translation. Over the past few years, ML has gradually permeated the financial sector, reshaping the landscape of quantitative finance as we know it.An Introduction to Machine Learning in Quantitative Finance aims to demystify ML by uncovering its underlying mathematics and showing how to apply ML methods to real-world financial data. In this book the authorsFeatured with the balance of mathematical theorems and practical code examples of ML, this book will help you acquire an in-depth understanding of ML algorithms as well as hands-on experience. After reading An Introduction to Machine Learning in Quantitative Finance, ML tools will not be a black box to you anymore, and you will feel confident in successfully applying what you have learnt to empirical financial data!
Author: William Johnson
Author: Alonso Peña
Author: Robert R. Reitano
Author: Jennifer Voitle
Author: Jan Kallsen
Author: William Johnson
Author: Chenghu Ma
Author: Jherek Healy
Author: Anatoly B. Schmidt
Author: Edina Berlinger
Author: Hao Ni