Mutual Fund Selection: In Praise of the Quantitative Screen

Mutual fund selection is a combination of art and science. The art is qualitative assessment and evaluation. The science is the forensic breakdown and analysis of performance outcomes. We are constantly reminded by regulators of the frailty of relying on the past to predict the future–and rightly so. Investors must treat past performance with caution.

Past performance—the only evidence we have

The simple fact is that past performance is the only meaningful footprint any fund manager leaves behind. It is the only tangible evidence to verify–or indeed counter–the slick marketing collateral fund groups use to seduce us.

How we analyse this past performance is crucial. It is too simple to allude, as many critics of past performance do, to the randomness of future outcomes. Certainly the future is random, but not the contribution of skill to future outcomes. Taking a fund manager’s percentile ranking at any point in time poses the same problems for a potential investor as does looking at the balance sheet of a company. It is just a snapshot.

What is more important for us to do is to break down the performance over many periods and examine it forensically.

Data mining the wheat from the chaff

There are some 13,000 genuine cross-border funds from which European buyers can choose. There is no way any fund buyer can be intimate with the entire universe of available funds. A well-built quantitative screen is a sensible approach to identifying those funds which warrant further investigation.

A high-quality database of funds is essential for a robust quantitative screen. Lipper for Investment Management is a very powerful tool for building screens. It allows users to incorporate, with ease, a plethora of relative and absolute return metrics over rolling periods and within multiple sector classifications. Lipper sectors are constantly monitored to ensure that like-for-like data can be readily extracted and compared.

Is there evidence of consistent alpha?

The starting point for any meaningful quantitative screen is to extract the fund manager’s performance and examine it within the context of how much active risk the fund manager has taken relative to a benchmark and, if necessary, a fixed-return outcome such as cash. At its simplest the quantitative screen must answer the question: “Has my fund manager consistently converted active positions into alpha?”

In building a quantitative screen, fund selectors will have their own preference for different metrics and calibrations. My example below (Figure 1.) ranks U.S. funds by a combination of three one-year rolling periods of relative return (40% weighting to current year, 30% to t-1 year, 20% to  t-2 year) and 10% to the current three-year Sortino ratio.

Figure 1. Output of a Lipper generated Quantitative Screen for U.S. Equities 

Source: Lipper for Investment Management, Jake Moeller.

Science plus art equals better fund research outcomes

The rudimentary quantitative screen above highlights funds that have produced strong risk-adjusted returns with consistency—a good starting point for further investigation.

There are some obvious limitations to the type of returns-based analysis in a quantitative fund screen. They are limited to the track record of the fund and they do not provide much colour on elements such as style and factor biases. However, this is where the importance of the qualitative component (the “art”) of fund research comes in.

The qualitative art of fund selection is for me, as important as the science, but I wouldn’t even commence my search without a decent quantitative screen to point me in the right direction.