Active Management
What you'll learn
- LOS 35.eCompare active management strategies, including market timing and security selection, and evaluate strategy changes in terms of the fundamental law of active management.
- LOS 35.fDescribe the practical strengths and limitations of the fundamental law of active management.
Market timing is simply a bet on the direction of the market (or a segment of the market). For example, an active manager may rotate money out of equities and into cash based on an expected decline in stock prices. For a market timer, the information coefficient is based on the proportion of correct calls:
IC = 2(% correct) − 1
If the manager is correct 50% the time, the IC will equal zero.
- Darsh Bhansali is a manager with Optimus Capital. Bhansali, a market timer, makes quarterly asset allocation decisions based on his forecast of the direction of the market. Bhansali’s forecasts are right 55% of the time.
- Mike Neal is an equity analyst focusing on technology stocks. Neal, a security selector, typically makes 50 active stock selections annually. Neal has an information coefficient of 0.04.
- Compute the information ratios of Bhansali and Neal, assuming that both managers construct unconstrained portfolios.
- Answer:
- Because both portfolios are unconstrained, TC = 1.
- Bhansali’s IC = 2(0.55) − 1 = 0.10
- Bhansali’s
- Neal’s
Sector Rotation
Market timing can also be used to make sector rotation decisions. For example, an active manager may allocate assets into sectors that are expected to outperform. Consider a two sector market made up of sectors X and Y.
Assume the expected sector return and volatility of returns are E(RX) and σX for Sector X, and E(RY) and σY for Sector Y.
If the correlation between the returns of sectors X and Y is given by rXY, the active risk of this strategy is the standard deviation of differential returns of the two sectors (i.e., RX − RY) and is given by σC:
The annualized active risk is a function of the number of bets made during the year. If, for example, the active manager makes quarterly bets, BR = 4:
annualized active risk
and the annualized active return
- Hwang Soi makes monthly allocation decisions between consumer discretionary and consumer staples based on a proprietary model. The historical correlation between the returns of the two sectors is 0.30 and Soi’s bets have been correct 60% of the time. Further information is in the following table.
- What is the annualized active risk of Soi’s sector rotation strategy?
- What is the expected annualized active return of Soi’s sector rotation strategy? 3. What will be the allocation to the consumer discretionary sector if Soi feels that consumer staples will outperform the consumer discretionary sector over the next month and if the active risk is limited to 5.20%?
- Answer:
Alternatively, active return from this strategy using a probability weighted average (given that Soi makes correct calls 60% of time) of combined risk is:
(0.60)(0.05) + (0.40)(−0.05) = 0.01 or 1% per month. Annual active return = 1% × 12 = 12%. 3. If active risk is limited to 5.20%, the deviation from the benchmark weights of 65% and 35% is limited to (5.20% / 17.32%) = 30%.
When Soi feels that consumer staples will outperform, the allocation to that sector will be 65% + 30%, or 95%, and the allocation to consumer discretionary will be 5%.
As we previously demonstrated, the fundamental law can be used to evaluate a range of active strategies, including security selection, market timing, and sector rotation. The practical limitations of the fundamental law of active management can be summarized as “garbage in, garbage out;” poor input estimates lead to incorrect evaluations. In the case of unconstrained optimization, the two components (inputs) that determine the information ratio are (1) the information coefficient (IC) and (2) the breadth (BR) of the manager’s strategy.
The limitations are generally derived from inaccurate estimates of the two inputs:
- Ex ante measurement of skill: The information coefficient is an estimate of the accuracy of an active manager’s forecasts on an ex ante basis. One problem with this is that managers tend to overestimate their ability to outperform the market and, hence, overestimate their IC. Regardless of the bias, the accuracy of the IC determines the accuracy of the ex ante information ratio.
- Independence: The breadth of a strategy is meant to measure the number of truly independent decisions that an active manager makes. If two or more decisions rely on same (or similar) information, then they are not independent. If individual decisions are correlated, then the breadth can be estimated as:
Decision independence may be compromised by systemic influences within a strategy, the cross sectional dependency. For example, a value strategy applied to different stocks within an industry may not be truly independent (most stocks will have similar fundamentals, such as P/E ratio). Similarly, decision independence can be compromised by time series dependency.
Monthly rebalancing decisions may not be truly independent from period to period.