Hedge Fund Modelling and Analysis using MATLAB
Hedge Fund Modelling and Analysis using MATLAB

Author: Paul Darbyshire

Publisher: John Wiley & Sons

Published: 2014-06-03

Total Pages: 215

ISBN-13: 1119967376

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The second book in Darbyshire and Hampton’s Hedge Fund Modelling and Analysis series, Hedge Fund Modelling and Analysis Using MATLAB® takes advantage of the huge library of built-in functions and suite of financial and analytic packages available to MATLAB®. This allows for a more detailed analysis of some of the more computationally intensive and advanced topics, such as hedge fund classification, performance measurement and mean-variance optimisation. Darbyshire and Hampton’s first book in the series, Hedge Fund Modelling and Analysis Using Excel & and VBA, is seen as a valuable supplementary text to this book. Starting with an overview of the hedge fund industry the book then looks at a variety of commercially available hedge fund data sources. After covering key statistical techniques and methods, the book discusses mean-variance optimisation, hedge fund classification and performance with an emphasis on risk-adjusted return metrics. Finally, common hedge fund market risk management techniques, such as traditional Value-at-Risk methods, modified extensions and expected shortfall are covered. The book’s dedicated website, www.darbyshirehampton.com provides free downloads of all the data and MATLAB® source code, as well as other useful resources. Hedge Fund Modelling and Analysis Using MATLAB® serves as a definitive introductory guide to hedge fund modelling and analysis and will provide investors, industry practitioners and students alike with a useful range of tools and techniques for analysing and estimating alpha and beta sources of return, performing manager ranking and market risk management.

Hedge Fund Modelling and Analysis using MATLAB
Hedge Fund Modelling and Analysis using MATLAB

Author: Paul Darbyshire

Publisher: John Wiley & Sons

Published: 2014-03-27

Total Pages: 215

ISBN-13: 1119967686

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The second book in Darbyshire and Hampton’s Hedge Fund Modelling and Analysis series, Hedge Fund Modelling and Analysis Using MATLAB® takes advantage of the huge library of built-in functions and suite of financial and analytic packages available to MATLAB®. This allows for a more detailed analysis of some of the more computationally intensive and advanced topics, such as hedge fund classification, performance measurement and mean-variance optimisation. Darbyshire and Hampton’s first book in the series, Hedge Fund Modelling and Analysis Using Excel & and VBA, is seen as a valuable supplementary text to this book. Starting with an overview of the hedge fund industry the book then looks at a variety of commercially available hedge fund data sources. After covering key statistical techniques and methods, the book discusses mean-variance optimisation, hedge fund classification and performance with an emphasis on risk-adjusted return metrics. Finally, common hedge fund market risk management techniques, such as traditional Value-at-Risk methods, modified extensions and expected shortfall are covered. The book’s dedicated website, www.darbyshirehampton.com provides free downloads of all the data and MATLAB® source code, as well as other useful resources. Hedge Fund Modelling and Analysis Using MATLAB® serves as a definitive introductory guide to hedge fund modelling and analysis and will provide investors, industry practitioners and students alike with a useful range of tools and techniques for analysing and estimating alpha and beta sources of return, performing manager ranking and market risk management.

Hedge Fund Modelling and Analysis Using Excel and VBA
Hedge Fund Modelling and Analysis Using Excel and VBA

Author: Paul Darbyshire

Publisher: John Wiley & Sons

Published: 2012-02-23

Total Pages: 294

ISBN-13: 111994564X

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Co-authored by two respected authorities on hedge funds and asset management, this implementation-oriented guide shows you how to employ a range of the most commonly used analysis tools and techniques both in industry and academia, for understanding, identifying and managing risk as well as for quantifying return factors across several key investment strategies. The book is also suitable for use as a core textbook for specialised graduate level courses in hedge funds and alternative investments. The book provides hands-on coverage of the visual and theoretical methods for measuring and modelling hedge fund performance with an emphasis on risk-adjusted performance metrics and techniques. A range of sophisticated risk analysis models and risk management strategies are also described in detail. Throughout, coverage is supplemented with helpful skill building exercises and worked examples in Excel and VBA. The book's dedicated website, www.darbyshirehampton.com provides Excel spreadsheets and VBA source code which can be freely downloaded and also features links to other relevant and useful resources. A comprehensive course in hedge fund modelling and analysis, this book arms you with the knowledge and tools required to effectively manage your risks and to optimise the return profile of your investment style.

Hedge Fund Modelling and Analysis
Hedge Fund Modelling and Analysis

Author: Paul Darbyshire

Publisher: John Wiley & Sons

Published: 2016-10-26

Total Pages: 363

ISBN-13: 1118879562

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Use powerful C++ algorithms and Object Oriented Programming (OOP) to aid in hedge fund decision making Low interest rates, overcrowded markets and greater regulatory oversight are just some of the many reasons it is close to impossible for hedge funds to draw competitive returns. The solution for many hedge fund managers, quantitative investment analysts and risk managers is to adopt new technologies, platforms and programming languages to better manage their risks and maximise the benefits of their return profiles. Hedge Fund Modelling and Analysis is a full course in the latest analytic strategies for hedge fund investing, complete with a one-of-a-kind primer on both C++ and object oriented programming (OOP). Covering both basic and risk-adjusted performance measures, this practitioner's guide enables you to manage risk easily and make the most of key statistics with simple and advanced analysis techniques. This highly anticipated third book in the widely used Hedge Fund Modelling and Analysis series is the only guide available for applying the powerful C++ language to revolutionise hedge fund trading. Even if you've never worked with code before, the focused overview of C++ gives you everything you need to navigate the technical aspects of object oriented programming, which enables you to build sophisticated analysis programs from small units of reusable code. This book is your breakthrough introduction to winning with hedge funds in the new reality of trading. Jumpstart your new approach to beating the markets with: All the guidance and hands-on support you need to use quantitative strategies to optimise hedge fund decision-making. Illustrative modelling exercises and worked-out problems demonstrating what to expect when assessing risk and return factors in the real world. A companion website offering additional C++ programs, algorithms and data to download. Make reading Hedge Fund Modelling and Analysis your new routine and gain all the insight and relevant information you need to beat the markets.

Foundations of Computational Finance with MATLAB
Foundations of Computational Finance with MATLAB

Author: Ed McCarthy

Publisher: John Wiley & Sons

Published: 2018-06-13

Total Pages: 375

ISBN-13: 1119433851

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Graduate from Excel to MATLAB® to keep up with the evolution of finance data Foundations of Computational Finance with MATLAB® is an introductory text for both finance professionals looking to branch out from the spreadsheet, and for programmers who wish to learn more about finance. As financial data grows in volume and complexity, its very nature has changed to the extent that traditional financial calculators and spreadsheet programs are simply no longer enough. Today’s analysts need more powerful data solutions with more customization and visualization capabilities, and MATLAB provides all of this and more in an easy-to-learn skillset. This book walks you through the basics, and then shows you how to stretch your new skills to create customized solutions. Part I demonstrates MATLAB’s capabilities as they apply to traditional finance concepts, and PART II shows you how to create interactive and reusable code, link with external data sources, communicate graphically, and more. Master MATLAB’s basic operations including matrices, arrays, and flexible data structures Learn how to build your own customized solutions when the built-ins just won’t do Learn how to handle financial data and industry-specific variables including risk and uncertainty Adopt more accurate modeling practices for portfolios, options, time series, and more MATLAB is an integrated development environment that includes everything you need in one well-designed user interface. Available Toolboxes provide tested algorithms that save you hours of code, and the skills you learn using MATLAB make it easier to learn additional languages if you choose to do so. Financial firms are catching up to universities in MATLAB usage, so this is skill set that will follow you throughout your career. When you’re ready to step into the new age of finance, Foundations of Computational Finance with MATLAB provides the expert instruction you need to get started quickly.

Hedge Funds
Hedge Funds

Author: Andrew W. Lo

Publisher: Princeton University Press

Published: 2010-07-01

Total Pages: 388

ISBN-13: 140083581X

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The hedge fund industry has grown dramatically over the last two decades, with more than eight thousand funds now controlling close to two trillion dollars. Originally intended for the wealthy, these private investments have now attracted a much broader following that includes pension funds and retail investors. Because hedge funds are largely unregulated and shrouded in secrecy, they have developed a mystique and allure that can beguile even the most experienced investor. In Hedge Funds, Andrew Lo--one of the world's most respected financial economists--addresses the pressing need for a systematic framework for managing hedge fund investments. Arguing that hedge funds have very different risk and return characteristics than traditional investments, Lo constructs new tools for analyzing their dynamics, including measures of illiquidity exposure and performance smoothing, linear and nonlinear risk models that capture alternative betas, econometric models of hedge fund failure rates, and integrated investment processes for alternative investments. In a new chapter, he looks at how the strategies for and regulation of hedge funds have changed in the aftermath of the financial crisis.

Environmental Data Analysis with MatLab
Environmental Data Analysis with MatLab

Author: William Menke

Publisher: Elsevier

Published: 2011-09-02

Total Pages: 282

ISBN-13: 0123918863

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"Environmental Data Analysis with MatLab" is for students and researchers working to analyze real data sets in the environmental sciences. One only has to consider the global warming debate to realize how critically important it is to be able to derive clear conclusions from often-noisy data drawn from a broad range of sources. This book teaches the basics of the underlying theory of data analysis, and then reinforces that knowledge with carefully chosen, realistic scenarios. MatLab, a commercial data processing environment, is used in these scenarios; significant content is devoted to teaching how it can be effectively used in an environmental data analysis setting. The book, though written in a self-contained way, is supplemented with data sets and MatLab scripts that can be used as a data analysis tutorial. It is well written and outlines a clear learning path for researchers and students. It uses real world environmental examples and case studies. It has MatLab software for application in a readily-available software environment. Homework problems help user follow up upon case studies with homework that expands them.

Computational Finance
Computational Finance

Author: Francesco Cesarone

Publisher: Routledge

Published: 2020-06-11

Total Pages: 284

ISBN-13: 1000169030

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Computational finance is increasingly important in the financial industry, as a necessary instrument for applying theoretical models to real-world challenges. Indeed, many models used in practice involve complex mathematical problems, for which an exact or a closed-form solution is not available. Consequently, we need to rely on computational techniques and specific numerical algorithms. This book combines theoretical concepts with practical implementation. Furthermore, the numerical solution of models is exploited, both to enhance the understanding of some mathematical and statistical notions, and to acquire sound programming skills in MATLAB®, which is useful for several other programming languages also. The material assumes the reader has a relatively limited knowledge of mathematics, probability, and statistics. Hence, the book contains a short description of the fundamental tools needed to address the two main fields of quantitative finance: portfolio selection and derivatives pricing. Both fields are developed here, with a particular emphasis on portfolio selection, where the author includes an overview of recent approaches. The book gradually takes the reader from a basic to medium level of expertise by using examples and exercises to simplify the understanding of complex models in finance, giving them the ability to place financial models in a computational setting. The book is ideal for courses focusing on quantitative finance, asset management, mathematical methods for economics and finance, investment banking, and corporate finance.

Statistical Methods for Financial Engineering
Statistical Methods for Financial Engineering

Author: Bruno Remillard

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 490

ISBN-13: 1439856958

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While many financial engineering books are available, the statistical aspects behind the implementation of stochastic models used in the field are often overlooked or restricted to a few well-known cases. Statistical Methods for Financial Engineering guides current and future practitioners on implementing the most useful stochastic models used in f

The Heston Model and its Extensions in Matlab and C#
The Heston Model and its Extensions in Matlab and C#

Author: Fabrice D. Rouah

Publisher: John Wiley & Sons

Published: 2013-08-01

Total Pages: 437

ISBN-13: 1118695178

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Tap into the power of the most popular stochastic volatility model for pricing equity derivatives Since its introduction in 1993, the Heston model has become a popular model for pricing equity derivatives, and the most popular stochastic volatility model in financial engineering. This vital resource provides a thorough derivation of the original model, and includes the most important extensions and refinements that have allowed the model to produce option prices that are more accurate and volatility surfaces that better reflect market conditions. The book's material is drawn from research papers and many of the models covered and the computer codes are unavailable from other sources. The book is light on theory and instead highlights the implementation of the models. All of the models found here have been coded in Matlab and C#. This reliable resource offers an understanding of how the original model was derived from Ricatti equations, and shows how to implement implied and local volatility, Fourier methods applied to the model, numerical integration schemes, parameter estimation, simulation schemes, American options, the Heston model with time-dependent parameters, finite difference methods for the Heston PDE, the Greeks, and the double Heston model. A groundbreaking book dedicated to the exploration of the Heston model—a popular model for pricing equity derivatives Includes a companion website, which explores the Heston model and its extensions all coded in Matlab and C# Written by Fabrice Douglas Rouah a quantitative analyst who specializes in financial modeling for derivatives for pricing and risk management Engaging and informative, this is the first book to deal exclusively with the Heston Model and includes code in Matlab and C# for pricing under the model, as well as code for parameter estimation, simulation, finite difference methods, American options, and more.