Advanced Quantitative Finance PDF Download

Author: Alonso Peña
Publisher: CreateSpace
ISBN: 9781508461401
Category :
Languages : en
Pages : 124

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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

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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

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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

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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

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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: Edina Berlinger
Publisher: Packt Publishing Ltd
ISBN: 1783552085
Category : Computers
Languages : en
Pages : 362

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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

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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: Maria Cristina Mariani
Publisher: John Wiley & Sons
ISBN: 1118629965
Category : Business & Economics
Languages : en
Pages : 494

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Book Description
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.

Author: Gianluca Fusai
Publisher: Springer Science & Business Media
ISBN: 3540499598
Category : Business & Economics
Languages : en
Pages : 606

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Book Description
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.

Author: Julia Di Nunno
Publisher: Springer Science & Business Media
ISBN: 364218412X
Category : Mathematics
Languages : en
Pages : 532

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Book Description
This book presents innovations in the mathematical foundations of financial analysis and numerical methods for finance and applications to the modeling of risk. The topics selected include measures of risk, credit contagion, insider trading, information in finance, stochastic control and its applications to portfolio choices and liquidation, models of liquidity, pricing, and hedging. The models presented are based on the use of Brownian motion, Lévy processes and jump diffusions. Moreover, fractional Brownian motion and ambit processes are also introduced at various levels. The chosen blend of topics gives an overview of the frontiers of mathematics for finance. New results, new methods and new models are all introduced in different forms according to the subject. Additionally, the existing literature on the topic is reviewed. The diversity of the topics makes the book suitable for graduate students, researchers and practitioners in the areas of financial modeling and quantitative finance. The chapters will also be of interest to experts in the financial market interested in new methods and products. This volume presents the results of the European ESF research networking program Advanced Mathematical Methods for Finance.