Hedge fund modelling and analysis using MATLAB® / / Paul Darbyshire, David Hampton

• Autore: Darbyshire Paul
• Pubblicazione: Chichester, West Sussex, United Kingdom : , : Wiley, , 2014
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (206 p.)
• Disciplina: 332.64; 332.64/5240285554
• Soggetto topico: Hedge funds - Mathematical models; BUSINESS & ECONOMICS / Finance; Hedge funds -- Mathematical models; Hedge funds; MATLAB; Finance; Business & Economics; Investment & Speculation
• Persona (resp. second.): HamptonDavid <1967->
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references (pages 179-181) and index.
• Nota di contenuto: Hedge Fund Modelling and Analysis Using MATLAB®; Contents; Preface; 1 The Hedge Fund Industry; 1.1 What are Hedge Funds?; 1.2 The Structure of a Hedge Fund; 1.2.1 Fund Administrators; 1.2.2 Prime Brokers; 1.2.3 Custodian, Auditors and Legal; 1.3 The Global Hedge Fund Industry; 1.3.1 North America; 1.3.2 Europe; 1.3.3 Asia; 1.4 Specialist Investment Techniques; 1.4.1 Short Selling; 1.4.2 Leverage; 1.4.3 Liquidity; 1.5 New Developments for Hedge Funds; 1.5.1 UCITS III Hedge Funds; 1.5.2 The European Passport; 1.5.3 Restrictions on Short Selling; 2 Hedge Fund Data Sources ; 2.1 Hedge Fund Databases2.2 Major Hedge Fund Indices; 2.2.1 Non-Investable and Investable Indices; 2.2.2 Dow Jones Credit Suisse Hedge Fund Indices (www.hedgeindex.com); 2.2.3 Hedge Fund Research (www.hedgefundresearch.com); 2.2.4 FTSE Hedge (www.ftse.com); 2.2.5 Greenwich Alternative Investments (www.greenwichai.com); 2.2.6 Morningstar Alternative Investment Center ( http:www.morningstar.com/advisor/alternative-investments); 2.2.7 EDHEC Risk and Asset Management Research Centre (www.edhec-risk.com); 2.3 Database and Index Biases; 2.3.1 Survivorship Bias; 2.3.2 Instant History Bias ; 2.4 Benchmarking2.4.1 Tracking Error; 3 Statistical Analysis; 3.1 Basic Performance Plots; 3.1.1 Value Added Index; 3.1.2 Histograms; 3.2 Probability Distributions; 3.2.1 Populations and Samples; 3.3 Probability Density Function; 3.4 Cumulative Distribution Function; 3.5 The Normal Distribution; 3.5.1 Standard Normal Distribution; 3.6 Visual Tests for Normality; 3.6.1 Inspection; 3.6.2 Normal Probability Plot; 3.7 Moments of a Distribution; 3.7.1 Mean and Standard Deviation; 3.7.2 Skew; 3.7.3 Kurtosis; 3.8 Covariance and Correlation; 3.9 Linear Regression; 3.9.1 Coefficient of Determination ; 3.9.2 Residual Plots3.9.3 Jarque-Bera Test; 4 Mean-Variance Optimisation; 4.1 Portfolio Theory; 4.1.1 Mean-Variance Analysis; 4.1.2 An Optimisation Problem; 4.1.3 Sharpe Ratio Maximisation; 4.2 Efficient Portfolios; 5 Performance Measurement; 5.1 The Intuition Behind Risk-Adjusted Returns; 5.1.1 Risk-Adjusted Returns; 5.2 Absolute Risk-Adjusted Return Metrics; 5.2.1 The Sharpe Ratio; 5.2.2 The Modified Sharpe Ratio; 5.2.3 The Maximum Drawdown Ratio; 5.3 Market Model Risk-Adjusted Return Metrics; 5.3.1 The Information Ratio; 5.3.2 The Treynor Ratio; 5.3.3 Jensens Alpha; 5.3.4 GH1 Metric ; 5.3.5 The M2 Metric5.3.6 The GH2 Metric; 5.4 MAR and LPM Metrics; 5.4.1 The Sortino Ratio; 5.4.2 The Omega Ratio; 5.4.3 The Upside Potential Ratio and Group Rankings; 5.5 Multi-Factor Asset Pricing Extensions; 5.5.1 The Choice of Factors; 6 Hedge Fund Classification; 6.1 Financial Instrument Building Blocks and Style Groups; 6.2 Hedge Fund Clusters and Classification; 6.2.1 Metric Definitions; 6.2.2 Creating Dendrograms; 6.2.3 Interpreting Dendrograms; 7 Market Risk Management; 7.1 Value-at-Risk; 7.2 Traditional VaR Methods; 7.2.1 Historical Simulation; 7.2.2 Parametric Method ; 7.2.3 Monte-Carlo Simulation
• Sommario/riassunto: 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.
• Titolo autorizzato: Hedge fund modelling and analysis using MATLAB®
• ISBN: 1-118-90502-4; 1-119-96767-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910810143303321
• Lo trovi qui: Univ. Federico II
• Serie: Wiley finance series.