Investors who pursue active management are looking to generate portfolio returns in excess of benchmark returns (adjusted for all costs) for an appropriate level of risk. The excess return—also called active return (RA)—of an actively managed portfolio is driven by the difference in weights between the active portfolio and the benchmark.
The three main building blocks of portfolio construction are:
- Factor weightings.
- Alpha skills.
- Position sizing.
These three building blocks are integrated into a successful portfolio construction process through a fourth component: breadth of expertise
Overweight/Underweight Rewarded Factors
The growing understanding of rewarded factors is profoundly changing the view of active and passive investing. There are many investment products that allow investors to directly access such factors as Value, Size, Momentum, and Quality, and the bar for active managers is rising: An active value manager not only needs to outperform a passive value benchmark but may also need to outperform a rules-based value-tilted product.
This can be thought of as active return due to differences in beta, where beta refers to sensitivity to a rewarded risk factor such as the market risk of CAPM, or the market, size, and value factors of the Fama and French model. With exposures to rewarded factors increasingly accessible via rules-based index products, simple static exposure to rewarded factors is no longer widely considered a source of alpha.
This building block relates primarily to active return source number one: differences in exposures to long-term rewarded factors.
In principle, there are many approaches that can be used to generate alpha, but in practice, generating positive alpha in a zero-sum game environment (before fees) is a challenge. Furthermore, the alpha generated by active managers must be sufficient to cover the higher fees usually associated with active management.
In principle, alpha can also be generated from timing exposure to unrewarded factors, such as regional exposure, sector exposure, the price of commodities, or even security selection.
Alpha skills are excess returns related to the unique skills and strategies of the manager. A manager can generate alpha through factor timing, which is skill in identifying when a factor might outperform/underperform its average return.
This building block relates primarily to active return source number two: identifying mispricings.
Position sizing is about balancing managers’ confidence in their alpha and factor insights while mitigating idiosyncratic risks. Although position sizing influences all three components of Equation 2, its most dramatic impact is often on idiosyncratic risk.
The general rule is that smaller positions in a greater number of securities will diversify away idiosyncratic risk and lead to lower portfolio volatility.
A factor-oriented manager who spreads their portfolio across many assets is likely to minimize the impact of idiosyncratic risk. A stock-picker is likely to hold more concentrated positions based on their insights into individual securities, and hence, deliberately assume a higher degree of idiosyncratic risk.
Integrating the Building Blocks: Breadth of Expertise
Success at combining the three building blocks is a function of a manager’s breadth of experience. A manager with broader expertise is more likely to generate consistent active returns. This can be seen in the fundamental law of active management.
A manager who considers a single factor defined by a single metric is unlikely to be making truly independent decisions, because all investment decisions are being driven by the same dimension, and therefore, are likely to have low breadth.
A manager who uses multiple factors and multiple metrics for each factor is likely to make more independent decisions when constructing their portfolio, and hence, have higher breadth.