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An Introduction to Quantitative Finance

An Introduction to Quantitative Finance Author Stephen Blyth
ISBN-10 9780199666591
Release 2013-11
Pages 175
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The quantitative nature of complex financial transactions makes them a fascinating subject area for mathematicians of all types. This book gives an insight into financial engineering while building on introductory probability courses by detailing one of the most fascinating applications of the subject.



Quantitative Finance for Physicists

Quantitative Finance for Physicists Author Anatoly B. Schmidt
ISBN-10 9780080492209
Release 2010-07-19
Pages 184
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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



Quantitative Finance

Quantitative Finance Author Erik Schlogl
ISBN-10 9781498785549
Release 2016-04-07
Pages 354
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Quantitative Finance: An Object-Oriented Approach in C++ provides readers with a foundation in the key methods and models of quantitative finance. Keeping the material as self-contained as possible, the author introduces computational finance with a focus on practical implementation in C++. Through an approach based on C++ classes and templates, the text highlights the basic principles common to various methods and models while the algorithmic implementation guides readers to a more thorough, hands-on understanding. By moving beyond a purely theoretical treatment to the actual implementation of the models using C++, readers greatly enhance their career opportunities in the field. The book also helps readers implement models in a trading or research environment. It presents recipes and extensible code building blocks for some of the most widespread methods in risk management and option pricing. Web Resource The author’s website provides fully functional C++ code, including additional C++ source files and examples. Although the code is used to illustrate concepts (not as a finished software product), it nevertheless compiles, runs, and deals with full, rather than toy, problems. The website also includes a suite of practical exercises for each chapter covering a range of difficulty levels and problem complexity.



Quantitative Finance

Quantitative Finance Author Matt Davison
ISBN-10 9781498782661
Release 2016-02-24
Pages 532
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Teach Your Students How to Become Successful Working Quants Quantitative Finance: A Simulation-Based Introduction Using Excel provides an introduction to financial mathematics for students in applied mathematics, financial engineering, actuarial science, and business administration. The text not only enables students to practice with the basic techniques of financial mathematics, but it also helps them gain significant intuition about what the techniques mean, how they work, and what happens when they stop working. After introducing risk, return, decision making under uncertainty, and traditional discounted cash flow project analysis, the book covers mortgages, bonds, and annuities using a blend of Excel simulation and difference equation or algebraic formalism. It then looks at how interest rate markets work and how to model bond prices before addressing mean variance portfolio optimization, the capital asset pricing model, options, and value at risk (VaR). The author next focuses on binomial model tools for pricing options and the analysis of discrete random walks. He also introduces stochastic calculus in a nonrigorous way and explains how to simulate geometric Brownian motion. The text proceeds to thoroughly discuss options pricing, mostly in continuous time. It concludes with chapters on stochastic models of the yield curve and incomplete markets using simple discrete models. Accessible to students with a relatively modest level of mathematical background, this book will guide your students in becoming successful quants. It uses both hand calculations and Excel spreadsheets to analyze plenty of examples from simple bond portfolios. The spreadsheets are available on the book’s CRC Press web page.



Introduction to R for Quantitative Finance

Introduction to R for Quantitative Finance Author Gergely Daróczi
ISBN-10 9781783280940
Release 2013-11-22
Pages 164
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This book is a tutorial guide for new users that aims to help you understand the basics of and become accomplished with the use of R for quantitative finance.If you are looking to use R to solve problems in quantitative finance, then this book is for you. A basic knowledge of financial theory is assumed, but familiarity with R is not required. With a focus on using R to solve a wide range of issues, this book provides useful content for both the R beginner and more experience users.



Stochastic Calculus for Quantitative Finance

Stochastic Calculus for Quantitative Finance Author Alexander A Gushchin
ISBN-10 9780081004760
Release 2015-08-26
Pages 208
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In 1994 and 1998 F. Delbaen and W. Schachermayer published two breakthrough papers where they proved continuous-time versions of the Fundamental Theorem of Asset Pricing. This is one of the most remarkable achievements in modern Mathematical Finance which led to intensive investigations in many applications of the arbitrage theory on a mathematically rigorous basis of stochastic calculus. Mathematical Basis for Finance: Stochastic Calculus for Finance provides detailed knowledge of all necessary attributes in stochastic calculus that are required for applications of the theory of stochastic integration in Mathematical Finance, in particular, the arbitrage theory. The exposition follows the traditions of the Strasbourg school. This book covers the general theory of stochastic processes, local martingales and processes of bounded variation, the theory of stochastic integration, definition and properties of the stochastic exponential; a part of the theory of Lévy processes. Finally, the reader gets acquainted with some facts concerning stochastic differential equations. Contains the most popular applications of the theory of stochastic integration Details necessary facts from probability and analysis which are not included in many standard university courses such as theorems on monotone classes and uniform integrability Written by experts in the field of modern mathematical finance



F for Quantitative Finance

F  for Quantitative Finance Author Johan Astborg
ISBN-10 9781782164630
Release 2013-12-26
Pages 286
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To develop your confidence in F#, this tutorial will first introduce you to simpler tasks such as curve fitting. You will then advance to more complex tasks such as implementing algorithms for trading semi-automation in a practical scenario-based format. If you are a data analyst or a practitioner in quantitative finance, economics, or mathematics and wish to learn how to use F# as a functional programming language, this book is for you. You should have a basic conceptual understanding of financial concepts and models. Elementary knowledge of the .NET framework would also be helpful.



Theoretical Foundations for Quantitative Finance

Theoretical Foundations for Quantitative Finance Author Luca Spadafora
ISBN-10 9789813202498
Release 2017-04-27
Pages 224
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This book provides simple introduction to quantitative finance for students and junior quants who want to approach the typical industry problems with practical but rigorous ambition. It shows a simple link between theoretical technicalities and practical solutions. Mathematical aspects are discussed from a practitioner perspective, with a deep focus on practical implications, favoring the intuition and the imagination. In addition, the new post-crisis paradigms, like multi-curves, x-value adjustments (xVA) and Counterparty Credit Risk are also discussed in a very simple framework. Finally, real world data and numerical simulations are compared in order to provide a reader with a simple and handy insight on the actual model performances. Request Inspection Copy Contents:IntroductionAll the Financial Math You Need to Survive with Interesting ApplicationsThe Pricing of Financial Derivatives — The Replica ApproachRisk-Neutral PricingThe Black and Scholes Framework and Its ExtensionRisk ModelingThe New Post-Crisis Paradigms Readership: Students and researchers in the fields of quantitative finance, risk management and stochastic analysis.



Introduction to Quantitative Finance

Introduction to Quantitative Finance Author Robert R. Reitano
ISBN-10 9780262013697
Release 2010-01-29
Pages 709
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Mathematical logic -- Number systems and functions -- Euclidean and other spaces -- Set theory and topology -- Sequences and their convergence -- Series and their convergence -- Discrete probability theory -- Fundamental probablility theorems -- Calculus I : differentiation -- Calculus II : integration



Quantitative Finance

Quantitative Finance Author A. Reghai
ISBN-10 9781137414502
Release 2014-11-25
Pages 223
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The series of recent financial crises have thrown open the world of quantitative finance and financial modeling. This book brings together proven and new methodologies from finance, physics and engineering, along with years of industry and academic experience to provide a cookbook of models for dealing with the challenges of today's markets.



Quantitative Finance and Risk Management

Quantitative Finance and Risk Management Author Jan W Dash
ISBN-10 9789814571258
Release 2016-05-10
Pages 1000
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Written by a physicist with extensive experience as a risk/finance quant, this book treats a wide variety of topics. Presenting the theory and practice of quantitative finance and risk, it delves into the "how to" and "what it's like" aspects not covered in textbooks or papers. A "Technical Index" indicates the mathematical level for each chapter. This second edition includes some new, expanded, and wide-ranging considerations for risk management: Climate Change and its long-term systemic risk; Markets in Crisis and the Reggeon Field Theory; "Smart Monte Carlo" and American Monte Carlo; Trend Risk — time scales and risk, the Macro–Micro model, singular spectrum analysis; credit risk: counterparty risk and issuer risk; stressed correlations — new techniques; and Psychology and option models. Solid risk management topics from the first edition and valid today are included: standard/advanced theory and practice in fixed income, equities, and FX; quantitative finance and risk management — traditional/exotic derivatives, fat tails, advanced stressed VAR, model risk, numerical techniques, deals/portfolios, systems, data, economic capital, and a function toolkit; risk lab — the nuts and bolts of risk management from the desk to the enterprise; case studies of deals; Feynman path integrals, Green functions, and options; and "Life as a Quant" — communication issues, sociology, stories, and advice.



Quantitative Finance For Dummies

Quantitative Finance For Dummies Author Steve Bell
ISBN-10 9781118769430
Release 2016-06-07
Pages 408
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An accessible, thorough introduction to quantitative finance Does the complex world of quantitative finance make you quiver? You're not alone! It's a tough subject for even high-level financial gurus to grasp, but Quantitative Finance For Dummies offers plain-English guidance on making sense of applying mathematics to investing decisions. With this complete guide, you'll gain a solid understanding of futures, options and risk, and get up-to-speed on the most popular equations, methods, formulas and models (such as the Black-Scholes model) that are applied in quantitative finance. Also known as mathematical finance, quantitative finance is the field of mathematics applied to financial markets. It's a highly technical discipline—but almost all investment companies and hedge funds use quantitative methods. This fun and friendly guide breaks the subject of quantitative finance down to easily digestible parts, making it approachable for personal investors and finance students alike. With the help of Quantitative Finance For Dummies, you'll learn the mathematical skills necessary for success with quantitative finance, the most up-to-date portfolio and risk management applications and everything you need to know about basic derivatives pricing. Covers the core models, formulas and methods used in quantitative finance Includes examples and brief exercises to help augment your understanding of QF Provides an easy-to-follow introduction to the complex world of quantitative finance Explains how QF methods are used to define the current market value of a derivative security Whether you're an aspiring quant or a top-tier personal investor, Quantitative Finance For Dummies is your go-to guide for coming to grips with QF/risk management.



A First Course in Quantitative Finance

A First Course in Quantitative Finance Author Thomas Mazzoni
ISBN-10 9781108419574
Release 2018-03-31
Pages
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Using stereoscopic images and other novel pedagogical features, this book offers a comprehensive introduction to quantitative finance.



Mastering R for Quantitative Finance

Mastering R for Quantitative Finance Author Edina Berlinger
ISBN-10 9781783552085
Release 2015-03-10
Pages 362
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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.



Learning Quantitative Finance with R

Learning Quantitative Finance with R Author Dr. Param Jeet
ISBN-10 9781786465252
Release 2017-03-23
Pages 284
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Implement machine learning, time-series analysis, algorithmic trading and more About This Book Understand the basics of R and how they can be applied in various Quantitative Finance scenarios Learn various algorithmic trading techniques and ways to optimize them using the tools available in R. Contain different methods to manage risk and explore trading using Machine Learning. Who This Book Is For If you want to learn how to use R to build quantitative finance models with ease, this book is for you. Analysts who want to learn R to solve their quantitative finance problems will also find this book useful. Some understanding of the basic financial concepts will be useful, though prior knowledge of R is not required. What You Will Learn Get to know the basics of R and how to use it in the field of Quantitative Finance Understand data processing and model building using R Explore different types of analytical techniques such as statistical analysis, time-series analysis, predictive modeling, and econometric analysis Build and analyze quantitative finance models using real-world examples How real-life examples should be used to develop strategies Performance metrics to look into before deciding upon any model Deep dive into the vast world of machine-learning based trading Get to grips with algorithmic trading and different ways of optimizing it Learn about controlling risk parameters of financial instruments In Detail The role of a quantitative analyst is very challenging, yet lucrative, so there is a lot of competition for the role in top-tier organizations and investment banks. This book is your go-to resource if you want to equip yourself with the skills required to tackle any real-world problem in quantitative finance using the popular R programming language. You'll start by getting an understanding of the basics of R and its relevance in the field of quantitative finance. Once you've built this foundation, we'll dive into the practicalities of building financial models in R. This will help you have a fair understanding of the topics as well as their implementation, as the authors have presented some use cases along with examples that are easy to understand and correlate. We'll also look at risk management and optimization techniques for algorithmic trading. Finally, the book will explain some advanced concepts, such as trading using machine learning, optimizations, exotic options, and hedging. By the end of this book, you will have a firm grasp of the techniques required to implement basic quantitative finance models in R. Style and approach This book introduces you to the essentials of quantitative finance with the help of easy-to-understand, practical examples and use cases in R. Each chapter presents a specific financial concept in detail, backed with relevant theory and the implementation of a real-life example.



Ethics in Quantitative Finance

Ethics in Quantitative Finance Author Timothy Johnson
ISBN-10 9783319610399
Release 2017-10-28
Pages 339
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This book presents an ethical theory for financial transactions that underpins the stability of modern economies. It combines elements from history, ethics, economics and mathematics to show how these combined can be used to develop a pragmatic theory of financial markets. Written in three sections; section one examines the co-evolution of finance and mathematics in an ethical context by focusing on three periods: pre-Socratic Greece, Western Europe in the thirteenth century and North-western Europe in the seventeenth century to demonstrate how the historical development of markets and finance were critical in the development of European ideas of science and democracy. Section two interprets the evidence presented in section one to provide examples of the norms reciprocity, sincerity and charity and introduce the pragmatic theory. Section three uses the pragmatic theory to interpret recent financial crises, address emergent phenomena and relate the theory to alternative contemporary theories of markets. Presenting a unique synthesis of mathematical and behavioural approaches to finance this book provides explicit ethical guidance that will be of interest to academics and practitioners alike.



Applied Quantitative Finance

Applied Quantitative Finance Author Wolfgang Karl Härdle
ISBN-10 9783662544860
Release 2017-08-02
Pages 372
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This volume provides practical solutions and introduces recent theoretical developments in risk management, pricing of credit derivatives, quantification of volatility and copula modeling. This third edition is devoted to modern risk analysis based on quantitative methods and textual analytics to meet the current challenges in banking and finance. It includes 14 new contributions and presents a comprehensive, state-of-the-art treatment of cutting-edge methods and topics, such as collateralized debt obligations, the high-frequency analysis of market liquidity, and realized volatility. The book is divided into three parts: Part 1 revisits important market risk issues, while Part 2 introduces novel concepts in credit risk and its management along with updated quantitative methods. The third part discusses the dynamics of risk management and includes risk analysis of energy markets and for cryptocurrencies. Digital assets, such as blockchain-based currencies, have become popular b ut are theoretically challenging when based on conventional methods. Among others, it introduces a modern text-mining method called dynamic topic modeling in detail and applies it to the message board of Bitcoins. The unique synthesis of theory and practice supported by computational tools is reflected not only in the selection of topics, but also in the fine balance of scientific contributions on practical implementation and theoretical concepts. This link between theory and practice offers theoreticians insights into considerations of applicability and, vice versa, provides practitioners convenient access to new techniques in quantitative finance. Hence the book will appeal both to researchers, including master and PhD students, and practitioners, such as financial engineers. The results presented in the book are fully reproducible and all quantlets needed for calculations are provided on an accompanying website. The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book.