Search results for: quantitative-finance-for-dummies

Quantitative Finance For Dummies

Author : Steve Bell
File Size : 45.81 MB
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An accessible introduction to quantitative finance by the numbers—for students, professionals, and personal investors The world of quantitative finance is complex, and sometimes even high-level financial experts have difficulty grasping it. 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 become familiar with 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 about applying mathematics and probability to financial markets, and involves using mathematical models to help make investing decisions. It's a highly technical discipline—but almost all investment companies and hedge funds use quantitative methods. The book breaks down the subject of quantitative finance into easily digestible parts, making it approachable for personal investors, finance students, and professionals working in the financial sector –especially in banking or hedge funds who are interested in what their quant (quantitative finance professional) colleagues are up to. This user-friendly guide will help you even if you have no previous experience of quantitative finance or even of the world of finance itself. With the help of Quantitative Finance For Dummies, you'll learn the mathematical skills necessary for success with quantitative finance and tips for enhancing your career in quantitative finance. Get your own copy of this handy reference guide and discover: An easy-to-follow introduction to the complex world of quantitative finance The core models, formulas, and methods used in quantitative finance Exercises to help augment your understanding of QF How QF methods are used to define the current market value of a derivative security Real-world examples that relate quantitative finance to your day-to-day job Mathematics necessary for success in investment and quantitative finance Portfolio and risk management applications Basic derivatives pricing Whether you're an aspiring quant, a top-tier personal investor, or a student, Quantitative Finance For Dummies is your go-to guide for coming to grips with QF/risk management.

Experiments in Quantitative Finance

Author : Joel Clarke Gibbons
File Size : 81.17 MB
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This book presents a novel approach to characterizing markets in quantitative terms. The examples cut across the world of interest rates, price of gold, stock market and corporate worlds that the stock market rests on, and the pricing of options on financial instruments. The emphasis is on methods of inquiry, methods that can just as easily be applied to other markets and other economic phenomena as well. The goal is to make the methods available to the widest possible audience of quantitative analysts and to the trading desks and investment plans they feed. Quantitative research and modeling in finance and economics have a long history going back to Frank Ramsey, mathematician, logician, and economist, who pioneered the application of dynamic models in economics in the 1920s, and to his theory of the Ramsey Tax, which is a rule for apportioning tax rates in a way that raises the maximum tax revenues while impacting the decisions of taxpayers as little as possible. The opposite would be a tax so inefficient that it causes people to avoid doing whatever it is that subjects them to the tax. These experiments yield valuable insight into economic affairs, but they are only a stepping-stone for others—a starting point for discovery. Foremost among them is locating usable statistical findings to the investment world. Gibbons’ intention is not to provide investment advice, it is to provide education. These data are subject to changing results, but that should not diminish their educational value. This is a proactive fusion of business economics and sound social science methods.

Paul Wilmott Introduces Quantitative Finance

Author : Paul Wilmott
File Size : 74.32 MB
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Paul Wilmott Introduces Quantitative Finance, Second Edition is an accessible introduction to the classical side of quantitative finance specifically for university students. Adapted from the comprehensive, even epic, works Derivatives and Paul Wilmott on Quantitative Finance, Second Edition, it includes carefully selected chapters to give the student a thorough understanding of futures, options and numerical methods. Software is included to help visualize the most important ideas and to show how techniques are implemented in practice. There are comprehensive end-of-chapter exercises to test students on their understanding.

Quantitative Finance for Physicists

Author : Anatoly B. Schmidt
File Size : 82.83 MB
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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

Theoretical Foundations for Quantitative Finance

Author : Luca Spadafora
File Size : 78.60 MB
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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.

A Benchmark Approach to Quantitative Finance

Author : Eckhard Platen
File Size : 25.49 MB
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A framework for financial market modeling, the benchmark approach extends beyond standard risk neutral pricing theory. It permits a unified treatment of portfolio optimization, derivative pricing, integrated risk management and insurance risk modeling. This book presents the necessary mathematical tools, followed by a thorough introduction to financial modeling under the benchmark approach, explaining various quantitative methods for the fair pricing and hedging of derivatives.

Quantitative Finance

Author : Erik Schlogl
File Size : 75.11 MB
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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

Author : Maria C. Mariani
File Size : 63.99 MB
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Presents a multitude of topics relevant to the quantitative finance community by combining the best of the theory with the usefulness of applications Written by accomplished teachers and researchers in the field, this book presents quantitative finance theory through applications to specific practical problems and comes with accompanying coding techniques in R and MATLAB, and some generic pseudo-algorithms to modern finance. It also offers over 300 examples and exercises that are appropriate for the beginning student as well as the practitioner in the field. The Quantitative Finance book is divided into four parts. Part One begins by providing readers with the theoretical backdrop needed from probability and stochastic processes. We also present some useful finance concepts used throughout the book. In part two of the book we present the classical Black-Scholes-Merton model in a uniquely accessible and understandable way. Implied volatility as well as local volatility surfaces are also discussed. Next, solutions to Partial Differential Equations (PDE), wavelets and Fourier transforms are presented. Several methodologies for pricing options namely, tree methods, finite difference method and Monte Carlo simulation methods are also discussed. We conclude this part with a discussion on stochastic differential equations (SDE’s). In the third part of this book, several new and advanced models from current literature such as general Lvy processes, nonlinear PDE's for stochastic volatility models in a transaction fee market, PDE's in a jump-diffusion with stochastic volatility models and factor and copulas models are discussed. In part four of the book, we conclude with a solid presentation of the typical topics in fixed income securities and derivatives. We discuss models for pricing bonds market, marketable securities, credit default swaps (CDS) and securitizations. Classroom-tested over a three-year period with the input of students and experienced practitioners Emphasizes the volatility of financial analyses and interpretations Weaves theory with application throughout the book Utilizes R and MATLAB software programs Presents pseudo-algorithms for readers who do not have access to any particular programming system Supplemented with extensive author-maintained web site that includes helpful teaching hints, data sets, software programs, and additional content Quantitative Finance is an ideal textbook for upper-undergraduate and beginning graduate students in statistics, financial engineering, quantitative finance, and mathematical finance programs. It will also appeal to practitioners in the same fields.

Quantitative Finance

Author : Matt Davison
File Size : 48.96 MB
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Teach Your Students How to Become Successful Working QuantsQuantitative 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 techn

Applied Quantitative Finance

Author : Wolfgang Karl Härdle
File Size : 32.70 MB
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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,, 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.