Contrast active strategies such as security selection and market timing, and use active management's fundamental law to assess shifts in strategy
The idea
A market timer makes a few calls a year on broad asset classes, so breadth is small and a high information coefficient is needed. For binary calls, right or wrong each time, the coefficient is IC = 2 × proportion correct − 1, so a timer right 60% of the time has an IC of 0.20. A stock picker covering a large universe makes many independent bets, so a modest IC can still produce a good information ratio. To evaluate a strategy change, ask what it does to each term: relaxing a long-only constraint raises the transfer coefficient and the IR in proportion; adding securities or rebalancing more often raises breadth, but only if the new bets are genuinely independent. The trap is to compare strategies on expected active return alone rather than on the IR each delivers.
In the app: 2 practice questions on this outcome, a narrated walkthrough with diagrams, spaced review that brings it back before you forget it.
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- Explain how the value that active management adds is gauged
- Work out the information ratio on both an ex post and an ex ante basis, explain what it means, and contrast it with the Sharpe ratio
- Set out and explain the fundamental law of active management for portfolios and each of its terms: breadth, the information coefficient, the transfer coefficient, and active risk (aggressiveness)
- Explain how the information ratio can help in picking investment managers and in deciding how much active risk a portfolio should carry
- Set out where active management's fundamental law is useful in practice and where it falls short