History shows that, even over periods of positive market runs, it can be hard to predict how individual stocks will behave. Research also shows that manager selection is no easier: historically, a first quartile manager in a given five-year period has less than a one-in-five chance of repeating that performance in the following period.
Some even suggest that the effectiveness of stock-picking is in fact entirely cyclical, and that it depends on a combination of macroeconomic factors outside the fund manager’s control, like the correlation between stocks, for example. A pure ‘stock picking’ approach without the safety net of good processes looks like a tough game to play, and with no room for error. So is there any room left for skill?
When perfection is not enough
Investors are rarely content to sit through a bumpy ride. They appreciate stability and some predictability in their investment return. Given the level of noise in stock performance, it is a stark reality that strong stock-selection skill is not enough to deliver consistent long-term returns.
Ideally, we think analysts should also follow a disciplined strategy in the way they approach this research. Standardising details like valuation models, accounting adjustments or discount rates improves the transparency of the analysis and enables better direct comparisons between similar companies.
Yet these approaches are not perfect either. Even when a very talented fund manager uses this kind of framework, portfolio returns can still be somewhat unpredictable, so it is difficult to assess a manager’s skill just on the basis of short-term performance.
Can anything more be done?
Putting more thought and method into portfolio construction, including risk management, can help iron out the variations in returns. This can be done using tools that force portfolios to keep aggregate systematic and stock-specific exposures within a certain range around a performance benchmark.
As concentrated active portfolios have risen in popularity, some managers have turned from this kind of benchmark-constrained construction. However, we think that entirely doing away with benchmark constraints is throwing the baby out with the bathwater.
Market capitalisation provides an accurate reflection of the total ‘opportunity set’ of all investors taken together. More importantly, it is the only ‘truly passive’ investment strategy: once the initial allocation is set, the portfolio remains correctly weighted regardless of market movements (barring events like stock splits or dividends). Thus an active manager who is paid to perform detailed analyses is cut little slack by investors for underperforming this return.
Although the value of investments may go down as well as up and investors may not get back the original amount invested, portfolios that are loosely constrained to a benchmark are not allowed to stray too far from the said benchmark’s performance. In the short to mid-term, this means the portfolio cannot perform too far below (or above) the benchmark, since they are linked. At the same time, the constraints can remain loose enough to allow the manager to uncover opportunities and demonstrate their skill.
Telling skill from luck
When analysing performance, it is just as important to judge the success of active portfolios in context. We want to disentangle the returns that can be explained by the investment process itself from those due to the manager’s skill – both in implementing and adding value to the investment process.
We can apply techniques of financial mathematics to try to distinguish pure skill from process performance. Attribution analysis offers additional information: it is another mathematical method that can identify the specific exposures that have contributed to or harmed performance (e.g. it can tell that Stock A contributed to 4 per cent of the portfolio’s gains, while stock B made the portfolio lose 3 per cent over the last period, and so on for every security in the portfolio). Together, those tools can show when and how managers have added value, but can also tell if this performance comes from consistently good stock selection or from a single, lucky decision. In this way, we can measure the real benefits of manager skill.
When market conditions are turbulent, strong processes can remove some of the randomness in fund performance, coming to the aid of manager skill to help investors navigate difficult periods.
Vis Nayar is deputy CIO of equities at HSBC Global Asset Management.
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