Understanding the impact of cutting the dead wood
Nothing sells funds like performance. Despite all the regulator’s railings that past performance is no guide to the future, we see flows being directed to the funds at the top of the league tables time and time again. There are, of course, far too many funds out there and some “dog” funds seem to have a remarkably long life. Perhaps the fund sponsor has an overly nurturing nature or, more likely, they are just too busy to consider whittling down their range.
Nevertheless, fund groups do periodically cull their range and put a handful of particularly canine funds out of their (and their holders’) misery.
Companies in the asset management community regularly experience takeovers and mergers.
These events often result in a duplication of funds, or on occasions, entire fund ranges, which need to be tidied up.
In such circumstances, fund mergers rather than closures are the preferred route, as this offers the best chance of hanging on to those precious assets under management.
Funds with the best track records are considered the choicest ones to keep, although rules on merging funds’ track records have been tightened over the years. However, the rules remain far from watertight.
I recall a particularly egregious example from early in my career when two UK equity funds were merged into one.
One of these funds was about five times larger than the other and it had a much longer track record. The other had a superior track record over one, three and five years.
There are no prizes for guessing which fund track record was “retained”.
In those days, I was responsible for running my shop’s fund quant monitor. Old hands will remember the Micropal fund performance database, probably with the same affection as I do.
This desktop-based system was delightfully responsive, especially when compared with the web-based systems of today.
It did have its quirks though and some of the early versions wouldn’t even export to Excel.
Young hands today might snigger but prepping my earliest fund meetings involved laboriously transcribing fund performance data into my company’s prescribed format.
The arrival of Excel exporting functions greatly sped up the process and allowed me to calculate novelties such as sector averages.
The sectors I defined myself; even in those days, I was a bit sniffy about using the Investment Association sector definitions.
Each year, I recorded the sector average over various periods and this included the calendar year return going back five years.
In time, I noticed that the sector average return recorded for single year would gradually improve as the calculation was repeated in the following years.
The difference between the numbers was strikingly large. Over the years, I reckoned a rule of thumb that sector averages would “improve” by 0.5 per cent one year later, and by a weighty 1 per cent two years later. The impact thereafter was inconsequential and, on occasions, even caused the average to “fall”. Clearly, the culled funds were the ones with the weakest 12- to 24-month records.
Later, I discovered that academics had also analysed this phenomenon in a far more rigorous manner than my own investigations.
I recently tasked my assistant to set about recreating my original approach to investigate whether survivor bias is still a factor in today’s markets. His approach involved a far more elegant way to examine the data. The table above details the results.
The approach involves comparing IA sectors in relation to a subset of the sector that just contains funds with a 10-year history. The data speaks for itself. Survivor bias remains alive and kicking in today’s funds market.
Fund groups continually prune the dead wood from their ranges and this inflates the average of the sector. Doubtless, passive fund zealots will seize upon this analysis as further evidence as to why active funds are just plain awful.
Some certainly are, though many funds are OK, and a few can bring exceptional returns.
Survivor bias is one of the reasons why quantitative techniques to identify winning funds are far more complex than it might seem at first sight and why many quant fund selection processes deliver mixed success.
I believe that qualitative research, while more laborious, better identifies funds that meet their performance objectives.
Jason Broomer is head of investment at Square Mile Investment Consulting & Research