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Trading active funds: another loser’s game


Academic research evidence about the distribution of relative returns from active managers and about persistency (and hence predictability) tell us that the game of picking stocks is essentially random – near enough all luck. Collectively, therefore, the rewards are zero gain and a loss in line with the cost of playing. But that’s not the whole story, only the start of it.

The game of picking stocks is mirrored in a game of picking managers who pick stocks. The performance effects of playing the active management game are the sum of behavioural impacts at both levels: fund managers and the ‘end investor’ or his/her agent.

Because most investors playing this game are doing so because they believe past performance is predictive of future performance, rather than random, they will naturally tend to select new holdings from the sample of managers/funds that have performed better than average over some recent period. If, on the other hand, it really is random (or even much less predictable than they thought), there is a very high chance of disappointment – where disappointment is defined as the ‘unexpected’ slippage of the fund through the rankings table. Consistent with the beliefs they held when they bought, they will now tend to sell, because they will assume that they made a mistake or that the manager in question has lost his/her touch – in other words the new performance is predicting more of the same. Because they have not changed their beliefs, they then go through the same exercise to select the replacement fund. And so it goes on, turning random underperformance of holdings into a non-random string of portfolio underperformance – until they realise it is their beliefs that are wrong.

This second behavioural effect is under-researched in academic studies, perhaps because the key insight itself has not attracted nearly as much attention as the effects at manager level. However, there are a number of industry firms that survey money-weighted returns in mutual funds (measuring client-experienced average returns): Dalbar, Vanguard and Morningstar. This analysis suggests playing the loser’s game costs up to 6% pa – far more than just the incremental costs of active funds (which in the UK we put at between 0.6 and 2% depending on the buyer’s agency relationships).

The data available to researchers is fund performance (obviously) and fund flows. But when making a connection between the two there are some problems:

  • Both are absolute – so if people sell after poor performance they could be making a market timing decision or a switching decision based on poor relative return but the data won’t tell them which. The two may of course be positively correlated. Given the evidence (in Dalbar’s annual surveys, for instance) that net flows are positively rather than inversely associated with market movements, it seems likely most of the effect is due to poor market timing rather than switching, so a reaction to absolute rather than relative performance.

  • Flows are partly idiosyncratic decisions and partly regular contributions/withdrawals but the two are not distinguished.

  • Money-weighted return calculations are affected by the sequential pattern of returns and flows – although I’m not convinced this methodology point ‘explains’ the apparent behaviour effect.

In ‘Mutual Fund Flows and Investor Returns: An Empirical Examination of Fund Investor Timing Ability’ (Friesen and Travis, 2007) the authors say this about the relative-return impulses to trade funds:

In testimony to the United States Senate, investment guru John Bogle (2003) argued that the Dalbar (2003) study ignores an additional “selection cost” borne by investors, whereby investors place a disproportionate amount of money into actively managed funds that subsequently underperform the S&P 500 index. Bogle suggests that after accounting for this selection cost, the average mutual fund investor return over the 1984-2002 period is actually negative.

Whilst it may be difficult to measure actual effects for a universe of mutual fund investors, it is possible to model the behavioural effects to test for the likely scale of impact of the relative-return impulse, by applying some simple decision rules, based on rank orders, for both buying and selling. This is a project for future research.

It is, however, possible to infer something today about the prevalence of this impact just from observation of a limited sample of portfolios. We have taken in new clients from a wide range of advisers/banks/wealth managers over the past six years. Because our clients have well above-average wealth, their previous agents are typically respected and popular firms, so we would expect them to be less prone than the average to systematic wealth-destroying behaviour. We also take on clients who are more experienced than average and so many have previously been wholly or partly self-directed. Our initial financial planning process for all new clients includes a critical appraisal of existing investment arrangements. We observe, in most cases, the same destructive behaviour by both agents and self-directed investors.

Even in the case of investors with agents, we suspect the investor’s own ‘predicted’ behaviour effectively encourages the agents to sell, because the agents think individuals think that poor performance tells them something about the agent’s skill.

When looking at agent behaviours, it is always sensible to consider whether incentives or game theory might explain them. Whilst I believe this is realistic in the case of fund managers, whose active-management payoffs are quite different from their investors, I do not think gaming validates the behaviour of agents selecting funds. Because both these agents and their clients are acting consistent with a set of beliefs (however false) about skill, it looks more like a case of the blind leading the blind.

‘It’s a miracle! I can see!’ cries Eddie Murphy in Trading Places when rumbled as a ‘blind’ beggar. In investing, miracles do happen and when an investor truly can see, their rumbled agents are unlikely to get away with it. They, rather than their clients, are the ones who should have known better.

#activemanagement #investmentprocess #markettiming #performance #pressmentions

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