1 option
Hedge fund modelling and analysis using MATLAB® / Paul Darbyshire, David Hampton.
- Format:
- Book
- Author/Creator:
- Darbyshire, Paul, author.
- Hampton, David, 1967- author.
- Series:
- Wiley finance series.
- Wiley finance series
- Language:
- English
- Subjects (All):
- MATLAB.
- Hedge funds--Mathematical models.
- Hedge funds.
- BUSINESS & ECONOMICS / Finance.
- Local Subjects:
- BUSINESS & ECONOMICS / Finance.
- Hedge funds--Mathematical models.
- Hedge funds.
- MATLAB.
- Physical Description:
- 1 online resource (206 p.)
- Edition:
- 1st ed.
- Place of Publication:
- Chichester, West Sussex, United Kingdom : Wiley, 2014.
- Language Note:
- English
- Summary:
- 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.
- Contents:
- 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
- Notes:
- Description based upon print version of record.
- Includes bibliographical references (pages 179-181) and index.
- ISBN:
- 9781118905029
- 1118905024
- 9781119967675
- 1119967678
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.