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Data Modeling Of Financial Derivatives


Data Modeling Of Financial Derivatives
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Data Modeling Of Financial Derivatives


Data Modeling Of Financial Derivatives
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Author : Robert Mamayev
language : en
Publisher: CreateSpace
Release Date : 2013-08-19

Data Modeling Of Financial Derivatives written by Robert Mamayev and has been published by CreateSpace this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-19 with Computers categories.


Written in plain English based on successful client engagements, this book introduces readers to the fascinating world of financial derivatives (futures, forwards, options, swaps, forward rate agreements) from the data modeling perspective and explains various rules that govern the world of financial engineering. Packed with numerous examples and techniques, this book can be useful tool for everyone with even a slightest interest in data modeling and business analysis. A knowledge of derivative instruments is not a prerequisite for reading this book. Every subject area is thoroughly explained before an attempt is made to model it. Similarly, a knowledge of data modeling is not required.



Data Modeling Of Financial Derivatives


Data Modeling Of Financial Derivatives
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Author : Robert Mamayev
language : en
Publisher: Apress
Release Date : 2014-02-28

Data Modeling Of Financial Derivatives written by Robert Mamayev and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-28 with Business & Economics categories.


Written in plain English and based on successful client engagements, Data Modeling of Financial Derivatives: A Conceptual Approach introduces new and veteran data modelers, financial analysts, and IT professionals to the fascinating world of financial derivatives. Covering futures, forwards, options, swaps, and forward rate agreements, finance and modeling expert Robert Mamayev shows you step-by-step how to structure and describe financial data using advanced data modeling techniques. The book introduces IT professionals, in particular, to various financial and data modeling concepts that they may not have seen before, giving them greater proficiency in the financial language of derivatives—and greater ability to communicate with financial analysts without fear or hesitation. Such knowledge will be especially useful to those looking to pick up the necessary skills to become productive right away working in the financial sector. Financial analysts reading this book will come to grips with various data modeling concepts and therefore be in better position to explain the underlying business to their IT audience. Data Modeling of Financial Derivatives—which presumes no advanced knowledge of derivatives or data modeling—will help you: Learn the best entity–relationship modeling method out there—Barker’s CASE methodology—and its application in the financial industry Understand how to identify and creatively reuse data modeling patterns Gain an understanding of financial derivatives and their various applications Learn how to model derivatives contracts and understand the reasoning behind certain design decisions Resolve derivatives data modeling complexities parsimoniously so that your clients can understand them intuitively Packed with numerous examples, diagrams, and techniques, this book will enable you to recognize the various design patterns that you aremost likely to encounter in your professional career and apply them successfully in practice. Anyone working with financial models will find it an invaluable tool and career booster.



Financial Derivatives Modeling


Financial Derivatives Modeling
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Author : Christian Ekstrand
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-08-26

Financial Derivatives Modeling written by Christian Ekstrand and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-26 with Business & Economics categories.


This book gives a comprehensive introduction to the modeling of financial derivatives, covering all major asset classes (equities, commodities, interest rates and foreign exchange) and stretching from Black and Scholes' lognormal modeling to current-day research on skew and smile models. The intended reader has a solid mathematical background and is a graduate/final-year undergraduate student specializing in Mathematical Finance, or works at a financial institution such as an investment bank or a hedge fund.



Mathematical Models Of Financial Derivatives


Mathematical Models Of Financial Derivatives
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Author : Yue-Kuen Kwok
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-07-10

Mathematical Models Of Financial Derivatives written by Yue-Kuen Kwok and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-07-10 with Mathematics categories.


Objectives and Audience In the past three decades, we have witnessed the phenomenal growth in the trading of financial derivatives and structured products in the financial markets around the globe and the surge in research on derivative pricing theory. Leading financial ins- tutions are hiring graduates with a science background who can use advanced analytical and numerical techniques to price financial derivatives and manage portfolio risks, a phenomenon coined as Rocket Science on Wall Street. There are now more than a hundred Master level degree programs in Financial Engineering/Quantitative Finance/Computational Finance on different continents. This book is written as an introductory textbook on derivative pricing theory for students enrolled in these degree programs. Another audience of the book may include practitioners in quantitative teams in financial institutions who would like to acquire the knowledge of option pricing techniques and explore the new development in pricing models of exotic structured derivatives. The level of mathematics in this book is tailored to readers with preparation at the advanced undergraduate level of science and engineering majors, in particular, basic profiiencies in probability and statistics, differential equations, numerical methods, and mathematical analysis. Advance knowledge in stochastic processes that are relevant to the martingale pricing theory, like stochastic differential calculus and theory of martingale, are introduced in this book. The cornerstones of derivative pricing theory are the Black–Scholes–Merton pricing model and the martingale pricing theory of financial derivatives.



Derivatives Analytics With Python


Derivatives Analytics With Python
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Author : Yves Hilpisch
language : en
Publisher: John Wiley & Sons
Release Date : 2015-08-03

Derivatives Analytics With Python written by Yves Hilpisch and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-03 with Business & Economics categories.


Supercharge options analytics and hedging using the power of Python Derivatives Analytics with Python shows you how to implement market-consistent valuation and hedging approaches using advanced financial models, efficient numerical techniques, and the powerful capabilities of the Python programming language. This unique guide offers detailed explanations of all theory, methods, and processes, giving you the background and tools necessary to value stock index options from a sound foundation. You'll find and use self-contained Python scripts and modules and learn how to apply Python to advanced data and derivatives analytics as you benefit from the 5,000+ lines of code that are provided to help you reproduce the results and graphics presented. Coverage includes market data analysis, risk-neutral valuation, Monte Carlo simulation, model calibration, valuation, and dynamic hedging, with models that exhibit stochastic volatility, jump components, stochastic short rates, and more. The companion website features all code and IPython Notebooks for immediate execution and automation. Python is gaining ground in the derivatives analytics space, allowing institutions to quickly and efficiently deliver portfolio, trading, and risk management results. This book is the finance professional's guide to exploiting Python's capabilities for efficient and performing derivatives analytics. Reproduce major stylized facts of equity and options markets yourself Apply Fourier transform techniques and advanced Monte Carlo pricing Calibrate advanced option pricing models to market data Integrate advanced models and numeric methods to dynamically hedge options Recent developments in the Python ecosystem enable analysts to implement analytics tasks as performing as with C or C++, but using only about one-tenth of the code or even less. Derivatives Analytics with Python — Data Analysis, Models, Simulation, Calibration and Hedging shows you what you need to know to supercharge your derivatives and risk analytics efforts.



Financial Models In Production


Financial Models In Production
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Author : Othmane Kettani
language : en
Publisher: Springer Nature
Release Date : 2020-09-16

Financial Models In Production written by Othmane Kettani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-16 with Mathematics categories.


This book provides a hands-on guide to how financial models are actually implemented and used in practice, on a daily basis, for pricing and risk-management purposes. It shows how to put these models into use in production while minimizing the cost of implementation and maximizing robustness and control. Addressing some of the most important and cutting-edge issues, it describes how to build the necessary models in order to risk manage all the costs involved in options fabrication within the world of equity derivatives and hybrids. This is achieved by extending classical models and improving them in order to account for complex features. The book is primarily aimed at market practitioners (traders, risk managers, risk control, top managers), as well as Masters students in Quantitative/Mathematical Finance. It will also be useful for instructors hoping to enrich their courses with practical examples. The prerequisites are basic stochastic calculus and a general knowledge of financial markets and financial derivatives.



Financial Modelling


Financial Modelling
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Author : Joerg Kienitz
language : en
Publisher: John Wiley & Sons
Release Date : 2012-09-10

Financial Modelling written by Joerg Kienitz and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-10 with Business & Economics categories.


Financial modelling Theory, Implementation and Practice with MATLAB Source Jörg Kienitz and Daniel Wetterau Financial Modelling - Theory, Implementation and Practice with MATLAB Source is a unique combination of quantitative techniques, the application to financial problems and programming using Matlab. The book enables the reader to model, design and implement a wide range of financial models for derivatives pricing and asset allocation, providing practitioners with complete financial modelling workflow, from model choice, deriving prices and Greeks using (semi-) analytic and simulation techniques, and calibration even for exotic options. The book is split into three parts. The first part considers financial markets in general and looks at the complex models needed to handle observed structures, reviewing models based on diffusions including stochastic-local volatility models and (pure) jump processes. It shows the possible risk-neutral densities, implied volatility surfaces, option pricing and typical paths for a variety of models including SABR, Heston, Bates, Bates-Hull-White, Displaced-Heston, or stochastic volatility versions of Variance Gamma, respectively Normal Inverse Gaussian models and finally, multi-dimensional models. The stochastic-local-volatility Libor market model with time-dependent parameters is considered and as an application how to price and risk-manage CMS spread products is demonstrated. The second part of the book deals with numerical methods which enables the reader to use the models of the first part for pricing and risk management, covering methods based on direct integration and Fourier transforms, and detailing the implementation of the COS, CONV, Carr-Madan method or Fourier-Space-Time Stepping. This is applied to pricing of European, Bermudan and exotic options as well as the calculation of the Greeks. The Monte Carlo simulation technique is outlined and bridge sampling is discussed in a Gaussian setting and for Lévy processes. Computation of Greeks is covered using likelihood ratio methods and adjoint techniques. A chapter on state-of-the-art optimization algorithms rounds up the toolkit for applying advanced mathematical models to financial problems and the last chapter in this section of the book also serves as an introduction to model risk. The third part is devoted to the usage of Matlab, introducing the software package by describing the basic functions applied for financial engineering. The programming is approached from an object-oriented perspective with examples to propose a framework for calibration, hedging and the adjoint method for calculating Greeks in a Libor market model. Source code used for producing the results and analysing the models is provided on the author's dedicated website, http://www.mathworks.de/matlabcentral/fileexchange/authors/246981.



Financial Mathematics Derivatives And Structured Products


Financial Mathematics Derivatives And Structured Products
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Author : Raymond H. Chan
language : en
Publisher: Springer Nature
Release Date : 2024-06-12

Financial Mathematics Derivatives And Structured Products written by Raymond H. Chan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-12 with Mathematics categories.


This book introduces readers to the financial markets, derivatives, structured products and how the products are modelled and implemented by practitioners. In addition, it equips readers with the necessary knowledge of financial markets needed in order to work as product structurers, traders, sales or risk managers. This second edition substantially extends, updates and clarifies the previous edition. New materials and enhanced contents include, but not limited to, the role of central counterparties for derivatives transactions, the reference rates to replace LIBOR, risk-neutral modelling for futures and forward, discussions and analysis on risk-neutral framework and numéraires, discrete dividend modelling, variance reduction techniques for Monte Carlo method, finite difference method analysis, tree method, FX modelling, multi-name credit derivatives modelling, local volatility model, forward variance model and local-stochastic volatility model to reflect market practice. As the book seeks to unify the derivatives modelling and the financial engineering practice in the market, it will be of interest to financial practitioners and academic researchers alike. The book can also be used as a textbook for the following courses: • Financial Mathematics (undergraduate level) • Stochastic Modelling in Finance (postgraduate level) • Financial Markets and Derivatives (undergraduate level) • Structured Products and Solutions (undergraduate/postgraduate level)



Derivatives


Derivatives
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Author : Jiří Witzany
language : en
Publisher: Springer Nature
Release Date : 2020-11-04

Derivatives written by Jiří Witzany and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-04 with Business & Economics categories.


This book helps students, researchers and quantitative finance practitioners to understand both basic and advanced topics in the valuation and modeling of financial and commodity derivatives, their institutional framework and risk management. It provides an overview of the new regulatory requirements such as Basel III, the Fundamental Review of the Trading Book (FRTB), Interest Rate Risk of the Banking Book (IRRBB), or the Internal Capital Assessment Process (ICAAP). The reader will also find a detailed treatment of counterparty credit risk, stochastic volatility estimation methods such as MCMC and Particle Filters, and the concepts of model-free volatility, VIX index definition and the related volatility trading. The book can also be used as a teaching material for university derivatives and financial engineering courses.



Financial Data Engineering


Financial Data Engineering
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Author : Tamer Khraisha
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-10-09

Financial Data Engineering written by Tamer Khraisha and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-09 with Computers categories.


Today, investment in financial technology and digital transformation is reshaping the financial landscape and generating many opportunities. Too often, however, engineers and professionals in financial institutions lack a practical and comprehensive understanding of the concepts, problems, techniques, and technologies necessary to build a modern, reliable, and scalable financial data infrastructure. This is where financial data engineering is needed. A data engineer developing a data infrastructure for a financial product possesses not only technical data engineering skills but also a solid understanding of financial domain-specific challenges, methodologies, data ecosystems, providers, formats, technological constraints, identifiers, entities, standards, regulatory requirements, and governance. This book offers a comprehensive, practical, domain-driven approach to financial data engineering, featuring real-world use cases, industry practices, and hands-on projects. You'll learn: The data engineering landscape in the financial sector Specific problems encountered in financial data engineering The structure, players, and particularities of the financial data domain Approaches to designing financial data identification and entity systems Financial data governance frameworks, concepts, and best practices The financial data engineering lifecycle from ingestion to production The varieties and main characteristics of financial data workflows How to build financial data pipelines using open source tools and APIs Tamer Khraisha, PhD, is a senior data engineer and scientific author with more than a decade of experience in the financial sector.