Hedge fund modelling and analysis using MATLAB® /
Darbyshire, Paul,author.
Hampton, David,1967-author.
"The second book in Darbyshire and Hampton's Hedge Fund Modelling and Analysis series, Hedge Fund Modelling and Analysis Using MATLAB(r) takes advantage of the huge library of built-in functions and suite of financial and analytic packages available to MATLAB(r). 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(r) source code, as well as other useful resources.Hedge Fund Modelling and Analysis Using MATLAB(r) 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"--
"The second book in Darbyshire and Hampton's Hedge Fund Modelling and Analysis series, Hedge Fund Modelling and Analysis Using MATLAB(r) takes advantage of the huge library of built-in functions and suite of financial and analytic packages available to MATLAB(r). 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(r) source code, as well as other useful resources.Hedge Fund Modelling and Analysis Using MATLAB(r) 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"--
Includes bibliographical references and index.
Machine generated contents note:  Preface xi 1 The Hedge Fund Industry 1 1.1 What are Hedge Funds? 1 1.2 The Structure of a Hedge Fund 4 1.3 The Global Hedge Fund Industry 6 1.4 Specialist Investment Techniques 10 1.5 New Developments for Hedge Funds 14 2 Hedge Fund Data Sources 19 2.1 Hedge Fund Databases 19 2.2 Major Hedge Fund Indices 20 2.3 Database and Index Biases 39 2.4 Benchmarking 42 3 Statistical Analysis 45 3.1 Basic Performance Plots 45 3.2 Probability Distributions 49 3.3 Probability Density Function 52 3.4 Cumulative Distribution Function 53 3.5 The Normal Distribution 54 3.5.1 Standard Normal Distribution 55 3.6 Visual Tests for Normality 56 3.7 Moments of a Distribution 58 3.8 Covariance and Correlation 63 3.9 Linear Regression 67 4 Mean-Variance Optimisation 77 4.1 Portfolio Theory 77 4.2 Efficient Portfolios 87 5 Performance Measurement 97 5.1 The Intuition Behind Risk-Adjusted Returns 97 5.2 Absolute Risk-Adjusted Return Metrics 103 5.3 Market Model Risk-Adjusted Return Metrics 110 5.4 MAR and LPM Metrics 125 5.5 Multi-Factor Asset Pricing Extensions 131 6 Hedge Fund Classification 137 6.1 Financial Instrument Building Blocks and Style Groups 137 6.2 Hedge Fund Clusters and Classification 138 7 Market Risk Management 155 7.1 Value-at-Risk 155 7.2 Traditional VaR Methods 159 7.3 Modified VaR 165 7.4 Expected Shortfall 166 7.5 Extreme Value Theory 172 References 179 Index 000 .
MATLAB.
Hedge funds