The Unspoken Behavioural Biases that Influence Professional Fund Investors

Although increasingly aware of the concept of behavioural biases; we remain poor at accepting that they directly relate to our own decision making, largely because we struggle with the negative inferences.  Take professional fund investors (a group I consider myself to be part of), we are vulnerable to a host of established biases but many of these are rarely acknowledged or discussed.  What can we infer from behavioural science research about the judgments made by buyers of mutual funds?

– We will favour fund management groups that have provided gifts and hospitality, no matter the price.  Small gestures may even be more influential than those of greater value.

Whilst undoubtedly the most difficult bias to acknowledge, the evidence on reciprocity – our desire or obligation to return a good deed – across all aspects of life is overwhelming, and professional  fund investors are not immune.  The fund industry (certainly in the UK) has sought to restrict the value of gifts and hospitality by asset managers seeking to sell their wares to prospective investors; however, the notion that limiting the monetary value prevents reciprocal behaviour is entirely spurious (see Katz, Caplan and Merx, 2003). Indeed, small gifts can be more influential – individuals provided with lavish gifts and hospitality may not invest in a fund managed by the giver for fear of the perception that their decision has been influenced, but as small gifts and hospitality are considered ‘inconsequential’, they can accept them without any questions raised about impartiality.  It is crucial to highlight here that reciprocity is an ingrained and often unconscious act, in most cases we will be blithely unaware of how our behaviour is being impacted, and indeed we are likely to rail against the very notion that we can be influenced in such a fashion.

– We are inclined toward investing with fund managers / sales people that we like.

Another of Robert Cialdini’s key pillars of influence (in addition to reciprocity) is ‘liking’; that is we are more readily persuaded by people that we like. This might be because they are similar to us, because they offer us compliments: “that was a great meeting, you really understand our fund”, or because we find them physically attractive.

– The further into an in-depth due diligence process we are for a fund; the less likely we are to identify a major problem with the strategy.

Detailed due diligence is crucial for any credible fund selector, but the time and effort of such a process can leaves us vulnerable to sunk costs – after multiple meetings and reams of analysis the prospect of abandoning research can become unpalatable.  More work makes us more committed (Garland 1990).

– The moment we see the performance track record of a fund our assessment of the quality of the philosophy, process and fund manager will change.

The grip of outcome bias is difficult to escape and even harder to see in ourselves.  In Baron and Hershey’s (1988) study on medical decisions and monetary gambles they found consistent evidence that participants rated the quality of a decision as better and the decision maker as more competent when the outcome were favourable rather than unfavourable (all other things being equal).  Given the amount of luck and randomness in the returns delivered by active funds, outcome bias is a particular problem for fund investors.

– We will recognise worrisome process related issues with underperforming fund managers that we would never have ‘identified’ had the performance been strong.

Outcome bias is so important to fund manager selection that I will mention it twice.  A classic case of the issue is evidenced by mutual fund investors propensity to sell losers and run winners (the reverse disposition effect), which is driven, in part, by our assumption that poor outcomes (disappointing performance) must be linked to problems with the process.  Thus, team changes, capacity issues or style drift are often cited as reasons for the sale of an underperforming fund; even if results can better be attributed to the general wax and wane of financial markets.

– We will blame the fund manager for poor performance and accept the credit for outperformance.

That we tend to internalise success and externalise failure has been well-documented in psychological research with a variety of causes, such as the desire to present ourselves in a favourable light or to enhance or confirm our own self-worth (Shepperd, Malone and Sweeny, 2008).  As fund investors we are, in essence, delegating investment decisions to a third party, and the opportunity to succumb to self-serving bias is great; as are the potential problems stemming from it – most notably an inability to learn from mistakes.

– We will erroneously associate strong presentation / public speaking with the possession of fund management skill.

The halo effect is a situation where we take one prominent and strong trait for an individual (or group) and extrapolate our positive view across of all of their characteristics (Nisbett & Wilson, 1977).  There is no proven correlation between communication skills and fund management aptitude, but we can easily become captivated by compelling presenters and discard those lacking the ability to converse in a convincing manner. It is also important to note that there is inevitably a selection bias in the pool of available active fund managers, with confident and persuasive individuals more likely to ascend to the upper echelons of the industry.

Key Reading:

Baron, J., & Hershey, J. C. (1988). Outcome bias in decision evaluation. Journal of personality and social psychology54(4), 569.

Cialdini, R. B., & Cialdini, R. B. (2007). Influence: The psychology of persuasion New York: Collins.

Garland, H. (1990). Throwing good money after bad: The effect of sunk costs on the decision to escalate commitment to an ongoing project. Journal of Applied Psychology75(6), 728.

Katz, D., Caplan, A. L., & Merz, J. F. (2003). All gifts large and small. American Journal of Bioethics3(3), 39-46.

Nisbett, R. E., & Wilson, T. D. (1977). The halo effect: Evidence for unconscious alteration of judgments. Journal of personality and social psychology35(4), 250.

Shepperd, J., Malone, W., & Sweeny, K. (2008). Exploring causes of the self‐serving bias. Social and Personality Psychology Compass2(2), 895-908.

Please note all views expressed in this article are my own and are not necessarily shared by my employer.

Things That Fund Managers Don’t Say Enough

When talking to active managers, fund investors can focus on the wrong things – we are heavily biased toward the short-term, and obsess over issues that are recent and salient.  We also drastically overvalue confidence as a characteristic, whilst punishing circumspection, realism and humility.  Given this, it is unsurprising that conversations with active managers are often shaped in a manner that is entirely at odds with the capricious and unpredictable nature of financial markets, and do little to help identify skill.

Active managers inevitably attempt to present themselves in the manner that they believe most appeals to investors and there are, therefore, many things that they should say, but rarely do.  Here are some examples:

“It was a genuine mistake – our analysis was incorrect, but I will make sure I learn from this for future decisions.”

“Whilst I believe in this investment, given that I will get at least 40% of my decisions wrong (assuming I do a very good job), this could be such an occasion.”

“It is important to highlight the pronounced style tailwind that I have enjoyed during this period of outperformance”.

“I can’t confidently predict the outcome of this event and, even if I could, it would be difficult to gauge how markets would react”.

“Although the trade was profitable, the situation did not develop as I had imagined and its success was actually just a dose of good fortune”

“Whilst the event is material and may have significant ramifications for markets I just don’t know what these will be with any certainty, so have decided to do nothing”.

“I appreciate that recent market volatility feels significant, but I don’t want to focus on it because, on a ten year view, it is likely to seem meaningless”.

“I am happy to give my perspective on the macro environment, but I have no particular expertise in the area, certainly relative to the thousands of others opining on the same subject”

“Of course I can review three month performance, but the results are almost entirely random market noise”

“I appreciate that I previously held a high level of confidence in this view, but, after careful analysis of new evidence, I realised that I was wrong”.

“I have absolutely no idea what equity markets will do over the next 12 months, but the odds are in favour of them going up”.

“I am fully aware of our propensity to make behavioural mistakes, and this is how I aim to minimise them…”

“On the balance of probabilities…”

How Can You Tell When a Factor Stops Working?

There is persuasive evidence that a select group of risk factors in equity investment provide investors with a return premium – that is they offer a long-term performance advantage relative to the broad market, on a risk-adjusted basis.  The most established and robust are value, momentum and size.  All three of these meet the crucial criteria of being present over an extended time horizon, pervasive across markets and supported by a behavioural / economic foundation.

Based on this, I consider it prudent to have exposure to these factors in a portfolio. However, this acceptance raises an immediate question – if I believe in the efficacy of these factors now, is this decision irrevocable? If I take a view about there being certain structural risk premia in equity markets, is it possible to change my mind? What could the rationale be for such a shift of view?

It is important to make a distinction here – I am not referring to the cyclicality of returns from a factor, I fully acknowledge that the performance of all equity risk factors will wax and wane, often over long cycles.  Rather, my concern is a situation where the long-term expected risk premium for a particular factor evaporates because of some change in the drivers of the anomaly.  I do not worry that the size factor will fail to deliver for sustained periods (for example), but that the premium no longer exists.

Whilst such an occurrence may be considered to hold a low probability, it surely cannot be impossible. Therefore a risk exists, yet one that is difficult to identify and quantify for a variety of reasons:

–  The pillars of all credible equity risk premia are economic and behavioural rationale. Structural excess returns cannot simply be present in the data; there must be a reason for their existence – I have written previously about behavioural drivers for value and momentum.  The problem is that these are only suppositions, in most cases it is impossible to precisely and unequivocally identify the causes of certain risk premia. It therefore follows that we cannot confidently observe when these alter.

–  Long term horizons (large sample sizes) are a prerequisite to build confidence in the robustness of equity risk premia. If we require multiple decades of data (at the very minimum) to support our behavioural / economic hypothesis, we need similar periods of time to ‘disprove’ them.  By the time there is sufficient evidence to support the contention that a risk factor no longer effective, you are likely to be enjoying retirement.

– The problem is exacerbated by the fact that even if a currently sound factor stopped working it would still behave, at times, as if it did.  Let’s assume that from this day on there was no value premium in equity markets – even in such a scenario there would continue to be extended periods when value outperformed.  Expensive stocks can (and do) generate prolonged periods of excess returns, despite there being no evidence of a structural premium.

–  In the event that you are willing to declare the demise of a previously robust equity risk premium, you are likely to be wrong, and at a particularly inopportune time – the sounding of the death knell for value investing will almost inevitably be prelude to resurgent performance from the factor.  It is easy to mistake the cyclical for the structural, and abandon a style of investing when it is depressed and the valuation dispersion wide.

– It is simply not in the interests of the majority of groups working within the burgeoning factor investment sub-industry to state that an prominent risk premium has lost its efficacy – informing clients that the factor they have invested billions in is unlikely to work in the future seems to be an unwise and unlikely business decision.  There are undoubtedly investors who would seek to exploit the change in factor dynamics, but these would be the exception rather than the rule.  It is not an industry renowned for parsimony.

As with all investment judgement, the consideration of factor viability it is about uncertainty and subjective probability. On the weight of evidence, it is likely that established equity risk premia will continue to deliver over the long term, however, there is a low probability that they will not, and it is important to incorporate this possibility into your decision making.  It is also prudent to assess how rich or cheap a particular factor is relative to its own history, which may provide some protection in the event that the presumed structural risk premium is no longer present. Neither of these options directly addresses the central question posed in this article, simply because there are no obvious answers.

Investors Should Embrace Probabilities to Improve Decision Making

One of the many oddities of the investment industry is that whilst it operates in a constant state of uncertainty and flux, its participants talk in the language of certainty.  Confident forecasts and dogmatic opinions are valued far more highly than circumspection and caveats.  This bias stems from the mistaken belief that expertise is related to conviction – that an expert must know the ‘right answer’.  Whilst this might hold in certain situations where the environment is stable and skill dominates outcomes; the reverse is true in random and unpredictable domains, such as financial markets. Here, expertise is more evident in humility, a willingness to revise views and to deal in probabilities.

There is certainly truth to the view that we are poor when it comes to thinking in terms of probabilities, and there are multiple examples of our irrationalities in this area – such as the tendency to neglect probabilities when considering extreme scenarios, and our propensity to overweight or ignore small probabilities.  The notion, however, that we should not talk about probability because we have limitations in this regard is entirely spurious; we cannot make a decision without taking some view on the likelihood of potential outcomes, even if we are not explicit about it.  If we bring our probability assessments into the open; it materially improves our ability to understand our biases, receive feedback on our judgements and learn.

Aside from our general struggle with thinking in such a manner, there are a range of other issues that limit the use of probabilities when making investment decisions and forecasts:

 Lack of expertise: As soon as probabilities are expressed around a variety of potential outcomes, there is an acknowledgement of uncertainty, which is often erroneously viewed as a lack of expertise and akin to the cardinal sin of stating “I don’t know”.  This issue is exacerbated by the fact that there will be others making bold, singular predictions – surely, they must know better?

Spurious accuracy: In uncertain environments views on probabilities are necessarily based on subjective judgements. Applying specific probabilities to a range of scenarios can appear overly scientific – what does it mean to believe the likelihood of an event is 17%?  This view, however, misses the value of applying probabilities.  Its use is not as a precise figure but as a measure of confidence and a means to monitor how our views evolve through time.

Implementation challenges: It is far easier to translate a strident, narrow view into an investment decision, than to attempt to reflect uncertainty and a variety of potential outcomes.

The forty percent problem:  Probabilities can be misused when making forecasts – the classic case is an individual assigning a 40% probability to an outlier event (a recession, typically). The 40% level means that if the event doesn’t occur their forecast was correct (on balance), but if the scenario does transpire it is of a high enough likelihood for them to be feted for the prediction.  This is an example of probabilities being utilised in a strategic, unhelpful fashion.

Changing minds:  When we frame outcomes in terms of probabilities, we allow ourselves the freedom to alter our view.  Whilst this should be considered positive and a reflection of realistic pragmatism; it is more often stigmatised as ‘sitting on the fence’ or providing a pre-prepared excuse for ‘being wrong’.

None of these arguments are particularly compelling and they are outweighed by the manifold benefits of thinking explicitly in terms of probabilities when making investment decisions:

Humility:  Simply by framing potential outcomes in terms of probabilities, we immediately acknowledge the uncertainty and unpredictability of any given judgement. We are divorcing ourselves from hubristic, narrow forecasts from the outset.

Reduce confirmation and commitment bias: When we espouse high conviction and overly precise views we come to be defined by them. Instead of refining or rejecting our beliefs in light of contrary evidence, we instead seek to preserve our ego by becoming increasingly committed and ignoring countervailing information.  By ascribing probabilities to a range of different scenarios we are more likely to remain open-minded and diminish the influence of being committed to any particular outcome.

Understand strength of view: It is often difficult to gauge the strength of someone’s view – this is particularly the case for binary situations where a ‘yes’ decision could either represent a marginal call or be a display of resounding confidence.  For example, if we had to predict the result of two coin tosses one, which was biased 55% in favour or tails and the other 95% towards tails – our ultimate view on the most likely outcome should be the same – but the level of confidence wildly different. Given that the investment industry tends to favour those making binary, conviction calls; such nuances are often lost and marked uncertainty can exit beneath a veneer of confidence – employing probabilities can help to reveal this.

Consider alternative scenarios: The use of probabilities forces us to consider alternative (often negative) scenarios; an individual with a high level of confidence in a specific outcome is still likely to ascribe some probability to other less favourable results.  Even if the chance of these occurring is regarded as minimal, there is an undoubted benefit from considering them, rather than ignoring them entirely and focusing solely on the primary case.  The best example of this would be in assigning a probability of a bullish case for a particular stock – the simple act of not giving the positive scenario 100% likelihood, compels consideration of other potential outcomes, and hopefully encourages debate.

Incorporate new information: A crucial element of successful decision making is the ability and willingness to revise views in the light of new information. If we make binary decisions (such as buy or sell) we can easily avoid incorporating fresh evidence by claiming our view has not altered (“it is still a buy”); however, by specifying probabilities it becomes increasingly difficult to ignore developments that are likely to impact your level of confidence.

For example, imagine you buy an active mutual fund and hold a 70% confidence that it will outperform its benchmark over three years; after one year the fund has generated significant excess returns – do you revise your view? If it is a simple, vague buy decision you are likely to continue to hold; however, if you have to update your confidence level there is likely to be an impact. Given the evidence of mean reversion in active manager returns, can you really still can you really continue to ascribe the same probability of outperformance over the next three years, or should it be revised lower?  Being explicit with probabilities forces us, and others, to challenge and update our thinking.

Evaluate past decisions: Given the scourge of hindsight bias it is often impossible to assess the quality of our historic decisions, as we cannot accurately recall our thought processes and feelings at the particular time. If, however, we consistently review and document our decision / forecast confidence level, we are in a far better position to understand how we came to a particular viewpoint and the manner in which we reacted to new information.  This can become a vital tool in learning from past behaviours.

Ascribing likelihoods to potential outcomes is not easy, as with all our behaviours it will be blighted by noise and bias; however, even if we are not openly expressing opinion in probabilistic terms, they are still deeply embedded in the views we hold.  As highlighted in Philip Tetlock’s Superforecasters and Annie Duke’s Thinking in Bets, being explicit about probabilities when making judgements or forecasts allows us to embrace uncertainty, affords us the freedom to revise our opinion as new information arrives and fosters the ability to learn from previous decisions.  In complex and ambiguous financial markets such features are invaluable.

Momentum Investing is Easy – So Why Does it Work?

Evidence on the effectiveness of momentum investing is overwhelming – it has delivered a return premium across markets and asset classes, and there is over two centuries’ worth of data (see Asness et al. 2014).  Whilst the performance advantage delivered is difficult to refute, it does present something of a puzzle – why should a strategy that is both technically simple to apply and behaviourally attractive deliver excess returns? Before exploring this question, it is worth clarifying these two claims:

Momentum is Easy:  A standard time series, price momentum strategy is relatively easy to construct and operate. Although there are a vast range of iterations and nuances (this is the investment industry, after all) – the basic premise is to go long assets rising in value, and short those falling. The technical barriers to employing this strategy in some form are limited.

Momentum is Behaviourally Attractive: Most of us are wired to be momentum investors. Being part of the trend plays to our desire to be ‘right’, to be a member of the herd and to conform to the compelling narratives that price momentum inevitably generates.  Participating in a momentum trade is psychologically comfortable.

Yet whilst most of us are momentum investors of some variety (often indirectly), rather than obtain the documented return premium – we help to create it.  Our behavioural limitations mean that our attempts at discretionary momentum investing (driven by human decision making) are deeply flawed and incur a cost, which can be exploited by systematic approaches.  It is important to remember that the evidence upon which the case for excess returns to momentum is built necessarily relates to systematic / rules based strategies.

In his book ‘Following the Trend’ Andreas Clenow described a traditional managed futures approach – a basic trend following strategy – as such:

“A statistical game with a slight tilt in your favour and that you just have to keep throwing the dice long enough to get the law of big numbers on your side”

This description bodes ill for the ability of humans to capture a momentum return.  Victor Haghani and Richard Dewey produced a study where financially literate individuals (including some investment professionals) had to bet on the result of a coin flip, which was loaded in their favour 60/40. They started with $25, could bet stakes as small as $0.01 and were given 30 minutes. Despite this favourable setup, only 21% reached the maximum payout of $250 and 28% went bust. Even more curiously, 48% of players bet on tails (which had the 40% probability) more than 5 times. If our behaviour can be so irrational and erratic in such a dispassionate setting, it is no wonder that investors make consistently poor decisions in stimulating and emotion-laden financial markets.

To understand how momentum investing driven by human judgement serves to create a fecund environment for rules based momentum approaches, it is helpful to consider the central tenets of a typical systematic process and understand how this compares to the features of discretionary (or human) decisions:

Momentum Systematic Discretionary
Winners Purchased Earlier Later
Winners Sold Later Earlier
Losers Sold Earlier Later
Diversification High Low
Rules Clear Vague
Persistence High Low

The characteristic approach of a discretionary, ‘human’ investor described above is driven and shaped by a range of behavioural factors:

Buying Winners Late:  Investors tend to underreact to news that fundamentally alters the value of a security.  Whilst this phenomenon may be caused simply by the pace of information dissemination; it is more likely a result of commitment bias (our reticence to recant prior views) and also the gradual development of a new narrative – one piece of newsflow or data is unlikely to shift the prevailing market story, but if this persists the story surrounding it will build strength, drawing in investors.  Also, as highlighted by Mark Granovetter (1978), we all have a different threshold for joining the riot (or herd) simply based on how many other people are participating. Momentum begets momentum.

Selling Winners Early:  As detailed by Shefrin (2010), the disposition effect – the tendency to cut winners and run losers – has a material impact on asset prices and the momentum effect.  In the case of relinquishing winning positions, investor willingness to sell on good news (and capture gains) serves to slow the adjustment of an asset price to its new fundamental value, thereby helping to foster momentum.

Selling Losers Late:  Whilst arriving conspicuously late to the party, discretionary investors often overstay their welcome in loss making positions.  Investors are committed to their viewpoint and suffer from confirmation bias, so may simply ignore new information that runs contrary to the view implicit in their positioning. This situation is exacerbated by cognitive dissonance, which makes them unwilling to crystallise losses and acknowledge error.

Lack of Diversification: Spreading risk across a variety of positions and asset classes is crucial to all sound investment approaches, but is particularly relevant (essential) for momentum-driven investing.  The hit rate for individual positons can be low and predicting where momentum will arise (and be sustained) before the event is difficult. There is also the constant threat of sharp reversals, which can rapidly destroy gains made in previously successful positions.  The danger for discretionary investors is that they become overconfident in their ability to identify the best trades and also overweight the most recent market activity.  This can lead to exceptionally narrow portfolios focused on securities that have the strongest current momentum, rather than holding a diverse range of positions with varying levels of price strength.  Whilst systematic momentum approaches can become concentrated, they consistently maintain a broad opportunity set and (should) have prudent risk controls.

Vague Rules: The best defence against the impulses of emotion or narrative-led decision making is a set of decision rules, which dictate investment behaviour.  Systematic momentum approaches are founded on such principles, and actively divorce decision making from all intrusive elements except the key variable – which is typically price, but can include fundamentals, such as earnings.  Discretionary human decisions are rarely driven by a binding set of rules and, absent strict guidelines, our actions are impacted by a range of factors, most of which have limited relevance to the judgement at hand. These might include: how we feel at the time of making a decision (our emotional state), our prior experience with a particular investment, the most recent news we have read, our belief in a particular narrative, or even how hungry we are (Danziger,  Levav,  & Avnaim-Pesso, 2011), and the weather (Hirshleifer & Shumway, 2003).

Being behaviourally consistent without a set of rules to adhere to is close to impossible; this was highlighted by Daniel Kahnemann (alongside Rosenfield, Gandhi and Blaser) in an article published in Harvard Business Review in 2016.  The authors discussed how the influence of irrelevant factors can lead to huge variability in decision making; unlike biases, which tend to be consistent and persistent, the impact of noise is random and erratic – and therefore more difficult to mitigate.  Even with the best intentions, the ability of a human decision maker to remain disciplined is severely limited.

Low Persistence: Perseverance is undoubtedly a key requirement for successfully capturing the momentum premium, and its return patterns make this an exacting challenge. The hit rate is unlikely to be high – therefore you will be ‘wrong’ frequently; furthermore, there will be many false dawns where momentum appears and rapidly evaporates.  There will also be prolonged fallow periods in choppy markets where returns to momentum are poor, and short-term shifts in markets that see prevailing trends whipsaw and sharp losses incurred.  Whilst a systematic, rules based strategy can be agnostic on such a performance profile (and indeed specifically designed to withstand it); the foibles of momentum are hugely problematic for discretionary investors, for whom it would be a herculean task to remain sufficiently controlled amidst the welter of behavioural impediments.

Whilst most of us are invariably attracted to momentum investing and carry it out in some form (even if it is merely implicit in our actions, rather than an express choice), few of us do it well.  Our decision making is blighted by our behavioural shortcomings and the substantial influence of irrelevant ‘noise’.  Human decision makers are willing but inferior momentum investors, creating the opportunity for systematic approaches to capture a premium.

Key reading:   

Asness, C. S., Frazzini, A., Israel, R., & Moskowitz, T. J. (2014). Fact, fiction and momentum investing.

Clenow, A. F. (2012). Following the trend: diversified managed futures trading. John Wiley & Sons.

Danziger, S., Levav, J., & Avnaim-Pesso, L. (2011). Extraneous factors in judicial decisions. Proceedings of the National Academy of Sciences108(17), 6889-6892.

Granovetter, M. (1978). Threshold models of collective behavior. American journal of sociology83(6), 1420-1443.

Haghani, V., & Dewey, R. (2016). Rational Decision-Making Under Uncertainty: Observed Betting Patterns on a Biased Coin.

Hirshleifer, D., & Shumway, T. (2003). Good day sunshine: Stock returns and the weather. The Journal of Finance58(3), 1009-1032.

Hurst, B., Ooi, Y. H., & Pedersen, L. H. (2017). A century of evidence on trend-following investing.

Kahneman, D., Rosenfield, A. M., Gandhi, L., & Blaser, T. (2016). Noise: How to overcome the high, hidden cost of inconsistent decision making. Harvard business review94(10), 38-46.

Shefrin, H. (2010). How the disposition effect and momentum impact investment professionals.

Five Simple Heuristics to Make Us Smarter Investors

Heuristics, or what we might call ‘rules of thumb’, have become somewhat maligned as a method of decision making in recent years. They are often erroneously conflated with cognitive biases and suffer their negative connotations.  Furthermore, the scepticism regarding the effectiveness of heuristics has been exacerbated by the ubiquitous system one (fast) / system two (slow) thinking construct (popularised by Daniel Kahneman), which can frame system one as the domain of rash, unthinking errors and system two the home of cool, rational and correct calculation.  System one and system two is frequently used as shorthand for ‘bad’ and ‘good’ thinking respectively, with the mental shortcuts that define heuristics firmly in the former grouping.

Even without exploring the limitations of the ‘two systems’ theory (see Osman, 2004); it is clear that heuristics do not fit within such a binary framework.  They can be either instinctive or deliberate, and often deliver results that are more robust than more complex methods of judgement.  For example, see Serwe and Frings (2006) on predicting the result of Wimbledon tennis matches, and McCammon and Hageli (2007) on avalanche risk.  Andrew Haldane’s speech around this topic is also excellent.

Unsurprisingly, the best definition of heuristics comes from Gerd Gigerenzer, who has been the pre-eminent voice on this subject, and the most vocal critic of the work of Kahneman.  He defines the heuristic approach as such:

“A strategy that ignores part of the information, with the goal of making decisions more quickly, frugally, and/or accurately than more complex methods” (Gigerenzer & Gaissmaier, 2011).

Although heuristics do feature in the world of investment there is an undoubted preference for complexity.  This is understandable – financial markets are intricate, unpredictable and often unfathomable; therefore we struggle to believe that simple solutions can be effective – a complex problem must be untangled by a complex process.  Furthermore, it is difficult to justify fees (and our own existence in the industry) by recommending quick and easy solutions.

This is not to suggest that everything in investment can be improved through simplification; rather we should not pour scorn on approaches that seek to streamline decision making in the midst of high uncertainty or difficulty. Sensible heuristics should be viewed as a valuable tool for investors, and below I have suggested five simple rules.

Jam Yesterday Heuristic:  If an investment has produced strong returns in the recent past, reduce your expectations for future performance.

Whilst this is self-explanatory, it often seems to run contrary to the behaviour of most investors. The gains registered by an investment before you decided to purchase, are returns you will not be enjoying in the future!

Upside Down Heuristic:  If an investment has outperformed its benchmark by a significant margin on the upside, it can also do so on the downside by a similar magnitude. If this is not acceptable, do not invest.

The lure of funds that have generated material excess returns can be irresistible, but if they have taken sufficient active risk for their performance to diverge markedly on the upside, they could generate similarly divergent returns in a less favourable fashion. Whilst index +20% is attractive over three years, only invest if you are willing to withstand the reverse 

– Keep it Simple Heuristic:  If presented with similar investment choices that differ in terms of complexity, select the simpler option.  

Simple investments are certainly no panacea, nor should they always be the preferred choice.  However, in situations where it is difficult to differentiate between alternatives in terms of quality, the preference should be towards that which is most easily understood.  Having clear and well-calibrated expectations is crucial for any investor.  If an investment strategy is straightforward, it is less likely to deliver negative surprises and you are more likely to stay invested for the long-term.

Hedge Your Bets Heuristic: If you have any uncertainty over the timing of an investment, phase it into the market in equal tranches.

Phasing investment decisions is an effective behavioural trick, not only does it reduce the potential reference point impact of a single price on entry or exit; it also allows for the positive framing of your decision. If the price of your targeted asset rises as you stagger your investment you can feel content that you initiated the purchase when you did, whereas if it falls you can be glad that you decided not to invest in one hit.

– Double for Drawdown Heuristic:  Your absolute minimum expectation for drawdown in any diversified investment (outside of cash) should be double its expected long-term volatility.  If this is not palatable, do no further work.

This rule is not a comment on the appropriateness on volatility as a measure of risk, nor the expected distribution of asset class returns (which are often skewed); rather it seeks to translate the most commonly employed investment risk metric (volatility) into a simple yes / no decision based on a willingness to bear (temporary) losses.  Of course, volatility is a woefully inadequate measure of risk for illiquid investments with artificially low volatility, and both undiversified or ‘penny in front of steamroller’ strategies, which suffer from sharp tail risks.

None of these heuristics is likely to be revelatory, but amidst the myriad options that investors face as they seek to meet their financial objectives, it is easy to lose sight of crucial principles that can lead to improved investment behaviour and better long-term outcomes.  Although lacking the intellectual cachet of more sophisticated approaches; easy to remember, simple to apply rules of thumb can be remarkably effective way to navigate a complex investment landscape.

Key Reading:

Gigerenzer, G., Todd, P. M., & ABC Research Group, T. (1999). Simple heuristics that make us smart. Oxford University Press.

Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual review of psychology, 62, 451-482.

McCammon, I., & Hägeli, P. (2007). An evaluation of rule-based decision tools for travel in avalanche terrain. Cold Regions Science and Technology, 47(1-2), 193-206.

Osman, M. (2004). An evaluation of dual-process theories of reasoning. Psychonomic bulletin & review, 11(6), 988-1010.

Serwe, S., & Frings, C. (2006). Who will win Wimbledon? The recognition heuristic in predicting sports events. Journal of Behavioral Decision Making, 19(4), 321-332.

Performance Consistency is not an Indicator of Equity Fund Manager Skill

One of the most commonly employed methods for judging whether an active equity fund manager possesses skill is monitoring performance consistency that is the regularity with which a particular manager outperforms their benchmark index over specific time periods (frequently calendar years, but often briefer).  This shorthand gauge of quality is pervasive across asset management groups (sellers), fund selectors (buyers) and the media.  The use of such a context free number is deeply flawed.  Not only does it disassociate process from outcome, and lure investors into strategies with a high probability of mean reversion; but it biases us against the distinctive, high conviction equity managers that better justify the use of active management.

Although the pull of performance ‘reliability’ is difficult to resist; the use of short-term excess return consistency measures to assess active equity managers is predicated on two flawed notions:

– Active equity managers have the ability to dependably predict short-term market behaviour.

It is surely now incontestable that the short-term movement of equity markets is highly unpredictable.  For an active manager to deliver consistent returns across discrete time periods through the application of skill, they must hold the uncommon ability to anticipate market direction and drivers, and appropriately shape their portfolios to benefit.

– The market consistently rewards good investment decisions.

To believe that short-term performance consistency can be employed to identify skill, one must contend not only that a manager makes consistently good investment decisions (on average) but that the market duly rewards these judgements in the near-term.  Markets are reflexive and for sustained periods can be driven by narratives and momentum, detaching dramatically from any semblance of fundamental reality.  Objectively robust decisions can go unrewarded for prolonged periods.  The implicit assumption embedded in performance consistency analysis of an active equity funds is that the market has unerringly validated the manager’s investment decision making.

Although the point of this post may seem relatively minor, it is critical to how we view and assess active equity management.  Performance consistency is employed in marketing campaigns, is frequently used by fund selectors to ‘screen’ sectors for talented managers, and often drives the external ratings given to funds.  This widespread acceptance of consistency as a robust indicator of skill exacerbates the damaging focus on short-term outcomes and leads to extensive attribution errors.  Furthermore; it must reduce the opportunities available for genuinely long-term focused active equity investors.

As difficult as it is to separate performance consistency from the skill of any active equity manager, unless a specific link can be drawn between the outcomes delivered and the underlying investment process, this should be our default stance.  Markets embark on prolonged trends and are driven for sustained periods by in-vogue themes;  against such a backdrop it is inevitable that groups of active managers will deliver consistent headline performance as they (often inadvertently) hold style biases that benefit from the prevailing tailwinds.  Given the structure of the market it would be surprising if there were not clusters of equity managers exhibiting consistent excess returns.

The behaviour of financial markets creates patterns of outcomes that are ideal for establishing a mirage of skill, and whilst we are hardwired to draw links between these outcomes and the related process, the simple fact is that skill in active equity management cannot be gleaned from performance alone, irrespective of the form it takes.

It is not only that headline performance consistency is a deeply misleading means of assessing the ability of an active equity manager, but as a characteristic it is the exact opposite of what fund selectors should be seeking.  By definition, long-term, high active share, conviction investors will not deliver performance consistency over the short-term.  There will be periods (often prolonged) when their style is out of favour and the ‘market’s perception’ diverges materially from their own.  Through such spells of challenging performance we should expect them to remain disciplined and faithful to their philosophy and approach; not wish them to latch onto the latest market fad in an effort to achieve improved short-term returns.

Consistency is absolutely paramount to the assessment of active equity managers, but we are focused on the wrong sort of consistency.  Rather than obsess over the persistence of short-term outcomes; we should focus our attention on the consistency of manager behaviour relative to their stated philosophy.  Doing so would improve the probability of achieving excess returns from holding active equity managers over the long-term.