Ch8 Performance Analysis (1)

1. Introduction
The goal of perfromance analysis is to distinguish skilled from unskilled investment managers
- time series analysis: separate skill form luck by measuring return and risk
- cross-sectional comparison: distinguish winners from losers

Performance analysis can help the manager avoid two major pitfalls in implementing an active strategy.
- incidental risk: growth stocks -> concentrations on certain industy and group of stocks with high volatility
- incremental decision making: sequence of individual asset decisions

2. Skill & Luck
2-1. Dimensions of skill & luck
- Blessed
- Insufferable
- Fortorn
- Doomed
*the challenge is to separate the blessed & the insufferable

2-2. Standard Error of Information Ration (IR)

where:
Y = number of years of observation

**IR: a ratio of portfolio returns above the returns of a benchmark to the volatility of those returns. IR measures a portfolio manager's ability to generate excess returns relative to a benchmark and attempts to identify the consistency of the investor. Generally, portfolios with higher betas will tend to have lower information ratios and vice versa, However, the higher beta enhances the portfolio's alpha and contributes to a higher information ratio if the benchmark underperforms the risk-free return during a period.

IR = (Rp - Ri) / Sp-i
where:
Rp = Return of the portfolio
Ri = Return of the benchmark
Sp-i = Tracking error (standard deviation of the difference between returns of the portfolio & the returns of the benchmark), residual risk

3. Defining-Based Performance Analysis
3-1. Returns

3-2. Returns Regression
- regressing the time series of portfolio excess returns against benchmark excess returns

4. Cross-Sectional Comparisons
4-1. Drawbacks of cross-sectional comparisons
- do not represent the complete population of institutional investment manages
- survivorship bias
- ingnore the size
- do not adjust for risk (cannot untangle luck & skill)