Hedge Fund and Investment Analysis
Course Outline
The course develops a clear understanding of the principles of investment analysis and the informational content gained through the modelling of hedge fund returns data. The theoretical material is supplemented throughout the course with applied problem solving and implementation using key quantitative techniques and methods. In a nutshell, the course will provide the necessary theoretical foundations as well as the implementation and subsequent analysis of key hedge fund and investment models and practices.
Excel computer-based workshops will provide an excellent opportunity to get hands-on experience analysing hedge fund returns data, building hedge fund performance models, and developing hedge fund risk management techniques and strategies. These models will be available to take away and be immediately applied to real-world hedge fund investment analysis which can be developed further into more robust quantitative analysis and risk management toolsets for the working environment.
Delegates will receive a copy of Paul's recently published book ‘Hedge Fund Modelling and Analysis Using Excel & VBA’ .
Who The Course is For
- Fund managers, asset managers, portfolio managers
- Institutional investors and corporate finance professionals
- Investment managers and professionals
- Risk managers
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Prior Knowledge
Working knowledge of the hedge fund industry and the main investment strategies employed is a prerequisite for the course since this material will not be covered. some basic statistics and mathematics (e.g. probability distributions, mean and standard deviation, and portfolio management) would also be an advantage.
Experience of using Excel built-in functions and packages (e.g. matrix algebra, the Solver tool and regression analysis) in order to develop dynamic spreadsheet models is also recommended as well as some knowledge of VBA programming although not essential. Pre-course reading material will be provided to facilitate the above.
This
program is eligible for
16 Continuing Education credit hours from the CFA Institute. If you are a
CFA Institute member, CE credit for your participation in this program
will be automatically recorded in your CE Diary.
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Day One
Session 1 – Understanding Hedge Fund data
- Major hedge fund databases
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Database biases:
- Survivorship
- Instant History
- Backfill
- Benchmarking
- Tracking error
-
Hedge fund drivers:
- Alpha
- Beta
- Alternative beta
-
Hedge fund indices:
- Investable
- Non-investable indices
Session 2 - Statistics for Hedge Funds
- Risk and return measures
-
Higher moments:
- Skewness
- Kurtosis
-
Visual tests of normality:
- Inspection
- Normal Q-Q plot
-
Linear regression:
- Ordinary Least Squares (OLS)
- Coefficient of determination
-
Numerical tests of normality:
- Jarque-Bera test for normality
- Hypothesis testing
-
Portfolio theory:
- Mean-variance analysis
- Optimisation
Workshops:
- An empirical hedge fund return distribution
- A Q-Q plot to test for normality
- Performing a regression analysis
- Optimisation a fund of hedge funds allocation
Session 3 - Risk-adjusted performance measures
- Sharpe ratio
- Modified Sharpe ratio
- Sortino ratio
- Drawdown ratio
- Information ratio
- Treynor ratio
- Jensen alpha
Workshop: Analysing a range of risk-adjusted Hedge Fund performance measures
Day Two
Session 4 - Hedge Funds asset pricing models
-
Capital Asset pricing Model (CAPM)
- Theoretical foundations
- Validation
- New extensions and developments
-
Multi-factor models:
- Principal Components Analysis (PCA)
-
Style analysis:
- Radar charts
- Herfindahl-Hirschmann Index (HHI)
- Rolling windows
- Kalman filters
-
Cluster analysis:
- Manhattan distance
Workshops:
- Analysing the CAPM market model
- Developing a style analysis model
Session 5 - Market risk management for Hedge Funds
- What is market risk?
-
Traditional VaR measures:
- Historical
- Covariance
- Monte-Carlo
- Modified VaR
- Expected shortfall
-
Extreme Value Theory:
- Block maxima
- Peak over threshold
Workshops: Implementing a range of VaR models for a Hedge Fund
