A Fund Manager’s Time Horizon is the Shortest Common Denominator

For most fund managers there is nothing more important than adopting a long-term approach.  This enables them to insulate themselves from the noise and random fluctuations of financial markets, and hopefully exploit them.  Yet for many this is simply not possible. Perverse and misaligned incentives, the desire to measure everything over meaningless time periods and the ascendancy of outcomes over process mean that the long-term is nothing more than a collection of reporting months and quarters.  Even when a fund manager’s express intention is to operate with a long time horizon, often they cannot because it is decided by the behaviour of other people. They don’t get to choose.

Every investment strategy or fund has a chain of involvement.  This will range from the underlying clients, to the fund managers, risk teams, CIOs and even CEOs.  All have differing objectives, incentives and levels of influence.  Unless all parties involved are aligned, the actual investment time horizon may not be what is stated in the investment philosophy, but be set by the shortest common denominator.  That is the shortest time horizon of someone involved who holds influence. 

If investors have the ability to freely withdraw money from a fund and are focused on monthly performance figures, then the fact that the investment approach is designed to take a five year view becomes almost an irrelevance.  Short-term numbers matter. Equally, if the CEO of a listed asset manager is worried about near term outflows then performance over the next quarter is everything.  In both of these cases the power lies away from the fund manager.  The client has the ability to sell their fund; the CEO has the ability to sack them.

When short-termism arises in the chain it becomes highly infectious. It affects the behaviour of everyone involved, most importantly the fund manager.  Their behaviour will either consciously or subconsciously change to stave off career risk.  The typical route to this is by chasing momentum.  Buying what has worked recently is an easy way to please everyone in the chain, for that moment at least.

It is not that investors (whose money it is) and senior managers should not have influence or choice, but it is crucial to acknowledge the impact that this may have on the ability of a fund manager to stick with their investing disciplines. It is not easy making long-term decisions when everyone will be poring over the next set of performance figures.  As soon as all involved in the chain have defaulted to a short-term view the investment outcomes become captured by randomness. Success or failure is no longer about the validity of an investment approach, it is about the toss of a coin.

How much influence other people possess in a chain relative to a fund manager will be heavily dependent on past performance. A fund manager with strong historic results will have more influence – they have pedigree and a track record. They are at little risk of outflows or redundancy so can set the terms. As performance deteriorates this changes.  The manager becomes more vulnerable and the influence shifts. Without a track record to fall back on they are at the mercy of others, often with interests and incentives that are based on a horizon very different to what appears in a due diligence document. 

When we consider a fund manager’s investment time horizon we often focus on how they apply their philosophy and process; with maybe some consideration as to whether their incentive package is aligned with this, But that is not sufficient. The crucial issue is whether a fund manager operates in an environment where they are able to invest with a sufficiently long time horizon.  Who are the other people with potential influence over the strategy and what are their incentives? This is difficult to answer and will evolve, but is vital for understanding on what basis investment decisions are actually being made. 

Investment strategies with fixed capital or fixed terms partially overcome this problem as their illiquidity forces a level of alignment; but the real benefit is for private investors.  Private investors don’t have a chain of involvement; they have one time horizon and one objective – their own. They can make decisions free of competing interests and conflicted incentives. It is easy to underestimate the incredible advantage this offers in reaping the benefits of making genuinely long-term decisions. 

So many professional fund managers extol the virtues of adopting a long-term approach, but how many are in a position or environment  that allows their words to be validated by their actions?  The structure of influence and incentives within the industry make it increasingly difficult to achieve.

Good Investors Make Decisions They Hope Will Cost Money

We tend to judge the outcomes of our investments in binary terms.  We make money or lose money. We outperform or underperform. Our judgement was good or it was bad.  This type of thinking is flawed because of the role of luck in financial markets.  If I make a decision when the odds and evidence are heavily in my favour and it doesn’t work out; that doesn’t make it a poor decision. A small dose of randomness can heavily dilute the information provided by outcomes alone. But there is something else. A prudent investment approach means making certain decisions that you expect and hope to disappoint.

The need for investors to diversify is often framed as a means of smoothing investment performance or tailoring a portfolio to a specific appetite for risk.  Whilst this is true, it is not enough. Diversifying across a range of assets or securities is an acceptance that we cannot predict the future and that we will be wrong about many things. 

The more confident we are, the more concentrated our investments.  With perfect foresight we would only invest in one security.  If we want to understand an investor’s confidence, check their portfolio concentration.

Appropriate diversification means always holding some assets and securities that appear to be laggards. This is the intended result.  We can think of such positions as failures or costs. Alternatively, we can consider them to be holdings that would have fared better in a different scenario to the one which transpired*.

As investors we all have opinions on markets, stocks and funds.  Diversifying our risks appropriately is challenging because it forces us to make decisions not only that we think are likely to be wrong and costly, but that we want to be wrong and costly. This is difficult to justify to ourselves, let alone others.  It is tough to tell a confident story about our view of the world, and then make investments that seem contrary to it. 

So, you have just told us there might be an inflationary problem around the corner, why are you holding nominal government bonds?”

“Well, I might be wrong and there could be a deflationary problem around the corner”.

That’s a hard sell.


Let’s make a bet. There is $100,000 on offer. You have to decide what will produce the highest return over the next decade. Emerging market equities or US equities. You have to allocate the $100k between the two options. You will receive the amount you stake on the strongest market.  If you are supremely confident, you can put it on a single outcome and risk losing the entire amount. If you are ambivalent you can split it equally and guarantee $50k.

Most investors will have a view on this choice. Some more forthright than others.  If you had a strong disposition towards US equities, how aggressive would your stake be?  Given the huge uncertainty surrounding the result it makes little sense to go all in.  You need to diversify and put money on both. This means allocating money to something that you think is wrong and want to be wrong.  It is sensible and prudent, but uncomfortable.

If you wager $70k on US equities and they outstrip emerging market equities, how do you feel? You are likely to curse your conservatism, rather than think about the other possible paths taken. You were right, why didn’t you back yourself more?

After the event, diversification only feels gratifying if we were wrong.  If we were right it feels like a cost. If I bet each-way on a horse that wins a race, I will rue the fact that I didn’t bet solely on a victory.

As always, the most challenging aspects of these types of decisions are when it involves changing our mind.  Let’s expand on the emerging market versus US equities bet. Five years in and the returns from both markets are identical.  You are asked if you want to adjust your stakes.  As you have some new information, you still favour US equities but now have less confidence in your view. So you alter your bet to $60k US equities / $40k emerging markets.

You have made a decision that you explicitly want to be incorrect.  At the end of the ten year period, it is in your interests if you were to look back and regret making this choice.  The level of cognitive dissonance here is pronounced.  I prefer US equities but I am reducing my bet. I am making a decision and I want it to cost me money. 

The central problem here is that when we are making an investment decision there are a huge range of potential, unknowable paths. After the event, only one route has been taken and a binary judgement will be made – were you right, or wrong?  To make matters worse,  everyone now feels that the result was obvious at the time you made your decision. 

Sensible investment is not about predicting a single path and trying to maximise your returns if it comes to pass.  It is about ensuring that you are appropriately positioned for a reasonable range of outcomes.  By all means have a view, but it needs to be heavily tempered with an acknowledgement that the future is inherently unpredictable.  

How often do you hear this phrase?

“Based on the information you had at the time, that seemed a sensible decision – even if it didn’t work out”.

In life? Rarely, In financial markets? Never. 

The best investors are those that are well-calibrated. They understand what they don’t and cannot know. Their decisions reflect this.  In simpler language they are comfortable making choices that they feel are wrong and that they hope come with a cost.


*This doesn’t absolve us from investing mistakes.

A Little Bit of Friction Can Make Us Better Long-Term Investors

One of the most effective methods for changing our behaviour is to alter the level of friction we face when making a decision. If we want to encourage an action, make it simple. If we want to restrict it, put up obstacles. We use this method intuitively in our everyday life – when we are trying to eat healthily we know it’s best not to have chocolate readily accessible in the fridge – but we tend to understate how the introduction of small amounts of friction can have profound consequences for the choices we make.

Take the case of paracetamol.  It is estimated that after the UK introduced limits on the number of tablets contained in a single packet, overdose deaths fell by 43%[i]*.  It seems absurd to believe that the implementation of a seemingly slight change could materially influence a decision of unparalleled consequence, but it can.  When behaviours are driven by emotion and moments, even minor amounts of friction can exhibit incredible leverage. This is a concept that matters a great deal for investors.

Technological developments have profoundly changed the decision-making experience of both professional and private investors in recent decades.  We are awash with information (noise) and stimulus; and have the freedom to transact at any given moment. Technology has made investing seamless.  It has removed the friction.

The greater transparency and control investors enjoy is regularly lauded, and it has brought us a wave of benefits; but it also comes with a major shortcoming.  The absence of friction allows us to easily take decisions based on how we feel at a given point in time.  It makes the most pernicious investing behaviours – performance chasing / market timing / panic selling – easy, and the most important – adopting a long-term approach – more difficult.

Friction in investment has a bad image.  We tend to think of it slowing our decision making.  Rendering us unable to access opportunities as they arise and suppressing our best instincts.  This view is illogical.  For most investors, the ability to exploit near-term opportunities or react rapidly to changing market dynamics is a danger not an advantage.  Whilst a very select group will attempt such activity for most of us it is a damaging distraction or at best an irrelevance.  We tend to perceive friction as a hindrance, but it can quell some of our worst dispositions and promote long-term investing.

It is important to differentiate friction in decision making from outright prohibition.  Friction does not prevent us from taking a particular path entirely, it simply slows the process.  It introduces time and reflection.  Although there may be some investing activities where a complete block might be prudent; in most cases the simple introduction of some level of difficulty or delay is likely to have significant ramifications for our decision making.

For private investors, the notion of friction is often allied to being trapped in poorly performing, expensive funds where extricating yourself from them is seen as too painful, costly or complicated to be worthwhile.  This is an undoubted negative friction. Freedom and ease of movement here is essential.  Yet a consequence of removing such friction is the ability it gives us to lurch between in-vogue investments and make judgements based on ever-dwindling time horizons.   

To counter this, we can introduce our own inhibitors.  Part of our long-term investment plan should be specifying limits on how frequently we check our investments (the most effective way to reduce volatility is to review your portfolio less) or put restrictions on the amounts of trades we place.  Setting the password for your account to something you are unlikely to remember might have an even greater impact.

It would also be helpful if the investment platforms that we use allowed us to apply our own restrictions when setting-up an account – creating frictions in a cold state that will prevent us making poor decisions in a hot one.  For example, there could be a feature where your ability to place trades online is switched off, unless you make a request (which might take 7 days to be approved).  Not removing the choice, but introducing a pause.

Even for professional investors, the use of friction can be beneficial.  It is typical to pour scorn on ‘committee-led’ decision making and any element of an investment process that seems to undermine the unadulterated views of a fund manager.  But they are not immune to short-term thinking or the pressure to react to the prevailing market narrative.  Frictions in the process can allow them to be more faithful to their investment objectives, rather than act as an impediment. 

Long-term investing has never been more difficult. The freedom, transparency and choice now available to investors which has brought many benefits, also increases the opportunity to make poor decisions.  Doing less and enjoying the power of compounding sounds simple but it is far from easy.  The more we engage with markets, the greater the temptation is to make choices that feel good now, that we later come to regret.

Taking a long-term approach takes effort and requires assistance.  A little bit of friction can go a long way.

−−−

* Not all of these will be suicides, and there are several confounding variables that mean that there is significant uncertainty around the 43% figure.  There is general agreement, however, that there has been a meaningful impact.


[i] https://www.nhs.uk/news/medication/smaller-paracetamol-packs-may-have-reduced-deaths/

How Much Conviction Do You Hold in Your Investment Views?

I recently read War and Chance by Jeffrey A. Friedman, which considers how foreign policy specialists deal with the uncertainty that surrounds their high stakes decisions.  Friedman focuses on an historic reticence to explicitly discuss either probabilities or confidence levels when making subjective judgements.  Whilst the impact of decisions made around the whereabouts of Osama bin Laden or the presence of WMD in Iraq have consequences that are far more profound, it struck me that the challenges and concerns highlighted by Friedman are also relevant to how we make investment decisions. In particular, the struggle we have in articulating how much conviction we hold in a position or opinion. 

The conviction that we express in any investment view reflects our expectations around the likelihood of certain outcomes.  We are constantly making judgements that are founded on our subjective belief about probabilities and our confidence in the available evidence. Despite this we seem unwilling to talk in these terms.  Instead, there is a tendency to frame investment positions in a definitive fashion – I believe X will happen because of Y.  The absence of nuance entirely belies both our own fallibility and the sheer uncertainty of the environment in which we operate. Ignoring these factors not only impacts the type and size of risks we take, but materially inhibits our ability to change our mind and learn from past decisions.

Why don’t we talk about probabilities?

In a similar fashion to foreign policy, the reluctance to address uncertainty and be specific around our probability judgements is driven by several factors.  Many people recoil at the spurious accuracy that appears to exist when numeric probabilities are expressed – how can you be 67% sure of something?  But this misses the point.  We are making this judgement whether we are transparent about it or not.  It is better to offer some level of clarity rather than not mention it at all or cloak it in vague language that will be interpreted differently by everyone who sees it.

The even greater impediment to being clear about probabilities when expressing an investment view is the value that the investment industry places on confidence. The conclusion we reach will either be right or wrong, and therefore there is a desire for our rationale to be consistent with that. It is all or nothing.  This is a meaningful decision and therefore we want it to appear as if it is an objective one (even though we know that this is an impossibility). 

When we discuss uncertainty and probability, we are admitting how much we do not and cannot know.  This jars with the fact that we are being paid for our investment acumen, and it is rarely a prudent marketing strategy to highlight your limitations. Particularly as everyone else seems more certain than we do.   

The value placed on (illusory) certainty and (over) confidence is vividly apparent in the categorical fashion in which we discuss our investment views. For example,  if I take the position that the dominant, large tech / consumer stocks in the US are overvalued and will underperform over the next five years, most of my time will be spent justifying why this perspective is correct and other theories are false.  If presented with a counter argument – such as certain names in this space becoming virtual monopolies that will not see their excess returns competed away as quickly as in ‘traditional’ industries – my instinct is to debunk this point to validate my own position. Yet if I accept uncertainty and a range of potential outcomes, I should not be discrediting all other scenarios, but rather acknowledging that there are other plausible paths. Albeit ones I ascribe a lower probability to than my central view. 

Disentangling confidence and probability

A crucial distinction that Friedman makes is between probability and confidence, which are often conflated.  Probability is based on the likelihood that something is true, whilst confidence is based on our belief in the robustness of the evidence supporting that view.  I believe that the chances of a single fair coin flip coming up tails is 50%; I also consider the chances of value stocks outperforming growth over the next 12 months to be 50%.  The probability I have ascribed to both outcomes is identical, but my confidence in my coin flip view is far greater than in the value versus growth call.  In the first case my 50% forecast is based on what I do know, the second case is based on what I do not know.  Expressing conviction is about both probabilities and confidence.  

Friedman states that the confidence we hold in our own analysis has three distinct components: i) The reliability of the evidence, ii) the breadth of reasonable views around a judgement, and iii) the extent to which fresh information could alter our perspective. 

Overtly utilising such a framework is crucial for a robust decision-making process and for understanding the level of conviction we should hold.  A cynic might suggest that financial markets are too noisy to distil confidence in this fashion, but if that is the case then it simply means we do not have sufficient confidence to take a view – which is perfectly reasonable. Also, when making an investment decision these three aspects are always implicit in the conviction we possess; it is far better to be open about these assumptions, particularly if we want to encourage consistency in our decision making and have the ability to learn from mistakes.

The benefits of probabilistic thinking 

Being clear about the probabilities we ascribe to potential outcomes and our own confidence in our views can be incredibly important to our investment decision making; especially when informing our level of conviction.  There are at least five clear benefits: 

1) Clarity of view:  Investment views tend to be either absolute or obscured (sometimes deliberately) by vague and ambiguous language. This means that they are either negligent of uncertainty or useless.  Addressing this by being more specific – by using numeric probabilities, for example – provides far more transparency around what we believe.     

2) Realism:  All investment decisions are made amidst uncertainty, although most of us behave as if that is not the case.  As soon as we employ probabilities in a consistent manner, we open ourselves to alternate scenarios.  It is crucial to concede the uncertainty both of an event and our own ability to foresee it. 

3) Ability to change our mind:  Moving away from categorical views makes it far easier to change our mind and update our thinking.  If we predict something will happen, we invariably become committed to that position, and often defined by it. Utilising a more nuanced approach that acknowledges other possible outcomes affords us the freedom to adapt and update as we receive new information. 

4) Ability to learn: All investors will be wrong and wrong frequently.  We cannot hope to improve our decision making unless we are consistent in how we record and convey our views.  If we are clear about probabilities and our level confidence at the point a decision is made; it becomes possible to review this in the future and understand the flaws in our judgements when we err. It allows us to become better calibrated. 

5) Consistency and comparability:  Given that investors will be expressing numerous views at any given point in time (and through time) the ability to treat them consistently and compare them equitably is paramount to effective decision making.  If our conviction differs between views, what is causing that? Why are we happy to take more risk in position A than position B? We can only answer such questions if we have a clear framework to understand probabilities and confidence levels.  

Don’t forget the magnitude 

Whilst our conviction should be driven by probabilities and confidence, that is not all that is required. We must always consider the magnitude of potential outcomes. The most significant example being situations where there is something unpleasant lurking in the tail of the distribution.  A bet with a 99% chance of a favourable outcome, may be unappealing if there is a 1% risk of ruin.  In such a scenario we might have an incredibly high conviction in our view, but still decline the ‘bet’ or at least size it in a manner that seems optically inconsistent with the strength of our beliefs.  Being more open to considering probabilities offers some protection against being ignorant of such tail risks because we are explicitly incorporating other possible scenarios in our thinking. 

Embracing uncertainty

Uncertainty is uncomfortable and unappealing, but it is also the reality of financial markets. The unequivocal investment opinions that we so often hear, and offer, feel bold and informed but are incongruous with the environment in which we make decisions.

Whether we acknowledge it or not, the conviction or strength of belief we hold in our investment views must be based on assumptions around probabilities and confidence.  Yet we rarely discuss our investments in this manner.   This is a problem not simply because it is hard to understand how much weight to give to other peoples’ opinions, but it also impairs our own decision making.  If we are to formulate, compare, scale and adjust our investment views appropriately we need to be clear not only about what we believe and why, but how much we believe it.

Friedman, J. A. (2019). War and chance: Assessing uncertainty in international politics. Oxford University Press.

 

Active Management has Become a Game of Musical Chairs

An often heard lament in recent years has been how the torrent of flows into passive strategies is distorting financial markets.  Although this is an inevitable angle for much maligned active managers to take, it is also somewhat absurd.  What is a broad, market cap index if not a reflection of the decisions of other ‘active’ investors?  Passive investors will replicate the prevailing weights of the target index; active investors will move those weights*.  The opprobrium directed at the rise of passive investing is mostly misguided.  Indeed, it is a sharp irony that the major impact of increased indexing has been for active investors to become more benchmark aware and myopic.  Their attempts to insulate themselves from the threat actually weakens the case for using them.

In an ideal world a market capitalisation index should be a reflection of the behaviour of other investors – a simple derivative outcome.  Unfortunately,  the market cap index or benchmark is now far more than that .  It has become the lodestar for the majority of active managers.  Not only is it a yardstick to evaluate quality over increasingly short and meaningless time horizons, but it has become the foundation of many investment processes. This is not because there is a widespread, philosophical belief that this is the correct approach to adopt; but because of skewed incentives and the management of business and career risk.

Active managers are under severe competitive pressure.  If they don’t perform they will be removed and the money will go to a passive option, or at least an outperforming peer.  Therefore their desire to take significant risk away from the benchmark is low.  Active management has become like a game of musical chairs where it makes sense to hover close to the chairs at all times, rather than risk being at the other side of the room when one is pulled away. 

Allied to this defensive behaviour is the closely related problem of increased short-term thinking.  The threat that most active managers face of being fired tomorrow has profound implications for decision making, both for individual managers and their employers.  Is there any purpose in making a long-term investment decision if there is little chance you will be around to witness it come to fruition?  Indeed, making such farsighted decisions may well hasten your departure.  Investing is a long-term endeavour,  active management has become a short-term game.

Success in this game is based on the measurement of performance over increasingly contracted time horizons.  Investors in active funds and managers of them consistently talk about results in terms of days, weeks and months.  This is nonsense.  Financial markets are hugely unpredictable and chaotic, and discerning skill is incredibly difficult.  Over short-time horizons it is impossible. 

Although suggesting so is often met with derision, judging investment quality by performance alone is deeply flawed.  In a system where there can be profound randomness in outcomes, it is crucial to focus on decision quality rather than results.  Performance outcomes (particularly over short horizons) are incredibly noisy.  There will inevitably be periods where the skilful (or just sensible) will appear inept and the lucky will appear to be sagacious.

Judging decision quality in financial markets is fraught with difficulty, and it is far easier to use the shorthand of relative performance instead.  Replace a difficult question with an easy one.  More importantly, however, if everyone else cares about short-term performance outcomes, then you have to as well.  There is no point playing in a game where your idea of winning is different to the other players.

Our investment behaviours pose major agency problems for active management.  Listed asset manager share price performance is driven by asset flows, which are led by short-term performance .  Executives at these firms are incentivised to raise assets under management  and therefore become focused on near-term results.  Although underlying investors are unlikely to be well-served by such myopia, the structure of the system means that executives and fund managers have to play a different game where the pay-offs arrive at a different point in time.  What is rational for the manager or business, may not always be rational for the client. 

We therefore exist in an environment where underperforming active fund managers are sacked, lose assets, forced to collapse their unrewarded risks and review their processes.  Even if you are a talented long-term investor you might not make it through your inevitable barren spell in-tact.  The result of all of these aspects is more money flowing into areas that have been ‘working’, exacerbating any perceived market distortions . Passive strategies reflect this, active strategies cause it.

Frustrated active managers will often complain that fundamentals don’t matter any longer.  They do, they are just not important in the game being played.  The desperation of active managers to ward off the threat posed by passive investments is leading to less differentiation and more short-term performance chasing, which only makes the case for passives more compelling.  Time for a rethink.

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*In this context we can think about passives as exposure to broad, market capitalisation indices. Of course, securities not captured in these can be more impacted by increasing flows into passive strategies.

Financial Markets Are No More Uncertain Today Than They Were Last Year

One of the most common statements since the outbreak of the coronavirus pandemic is that the economic and market outlook has become more uncertain.  Given that the future is inherently difficult to predict with any level of confidence and we are generally terrible forecasters can it really be true that the world is now more uncertain?

The environment unquestionably feels more unstable.  There are a range of imponderables around the development of the virus itself that none of us can hope to anticipate.  From the potential of a ‘second wave’ to the production of a viable vaccine.  We have also experienced an unprecedented economic ‘stop’, and credible cases can be made for an inflationary or deflationary future. 

Yet before accepting the ‘greater uncertainty’ idea at face value, it is worth deconstructing the meaning of such a claim.  What we are really saying is:

“I was much more confident in predicting the future of the economy and financial markets before that unexpected event occurred”.

Which can be expanded to:

“I was much more confident in predicting the future of the economy and financial markets before that unexpected event occurred, and showed that my level of certainty was exaggerated.”

It seems paradoxical to suggest that things were more certain before something we hadn’t expected happened and upended our prior beliefs. 

When we say things are now more uncertain we are usually implying that something has altered which has meant that the future has become increasingly difficult to predict.  It has not.  It was unpredictable before and it remains unpredictable now.  Rather than making the world more uncertain, unanticipated events serve to show us that we were understating how uncertain things were before. When claiming greater uncertainty in the future, we actually get it backwards.

Although we should not conflate greater uncertainty with changes in the forecastability of the world, this does not mean that the notion is meaningless; it just needs to be considered in a different way.  What we perceive to be an increase in uncertainty is really a change in the frame through which we view the world.  We have taken a particular path and now face a different distribution of possible outcomes. 

Let’s take a simple example.  My range of potential future personal outcomes involves me losing my job tomorrow.  This is (hopefully) a tail risk, yet it is a possibility.  If I am made redundant tomorrow then my life has taken that specific course.  My future is still unknowable, but the routes and their likelihood from this starting point have changed.  Although it feels like my life is more uncertain now I am without a job or salary, it is nonsensical to suggest that my life was more certain before it was struck by a remote risk that I failed to predict. 

If my life following a job loss hasn’t become more uncertain, then what has it become?  More fragile. When we discuss greater uncertainty following a particular event,  we often focus on how the shock has left us more vulnerable to future negative events.  Since losing my job I am now more susceptible to failing to pay my mortgage and losing my house.  There are a range of unpleasant scenarios that are now more likely.  This is the same for many businesses through the current recession.  The probability of ruin has changed.  Our certainty in predicting the future hasn’t.

The perception of greater uncertainty is not just about fragility, but how we make sense of the world.  When we perceive  a sharp rise in uncertainty it is a case of the narratives we use to explain the world becoming untethered.  The cause and effect stories we weave help give us some comfort navigating the randomness and chaotic nature of life.  If there is an occurrence that dramatically alters the environment then the threads that hold together our own explanatory narratives quickly break apart.  

The world has not become any harder to predict, but rather the stories we previously used to explain it are no longer valid.  If we cannot construct a coherent narrative things begin to feel distinctly uncomfortable.  To address this we will create new stories, or simply adjust our previous ones.  Restoring our prior (misplaced) sense of confidence and control

The very occurrence of the coronavirus pandemic means that any certainty we may have held before was unfounded.  We never know what will happen tomorrow.  We should act accordingly.

Do Fund Investors Prefer Lower Fees or Strong Past Performance?

Performance chasing is endemic in mutual fund selection.   Despite the randomness and luck involved,  the decisions that we make and narratives we weave are inextricably influenced by historic returns.  Although we may only spend a fraction of our time considering performance, it has an overwhelming impact on the judgements we make.

Supporting the results of previous studies in this area, a new piece of research by Leonardo Weiss-Cohen, Philip W.S. Newall and Peter Ayton shows individuals using  strong past performance to inform their fund choices rather than lower fees.

The researchers devised a task where investors had to select between one high fee (0.7%) and one low fee fund (0.1%) over 60 periods (months).  Both funds generated returns which were index plus random noise.  The mean of the random noise was set at zero, so the only long-term performance differential was the fee load.  For the first selection participants were shown a 12 month historic return for each fund and asked to make an initial choice.  At the end of each subsequent period they were shown the performance of both funds and again selected between the two options.  The compensation participants received for taking part in the study was in part based on the wealth they managed to accumulate through the game.

There were two separate experiments.  The first featured subjects (400) who had previous investment experience, and two conditions – one where they received a standard disclaimer: “Past performance does not guarantee future results” and one without this disclaimer.  The second experiment recruited subjects (596) without investing experience.  Here there was a third condition – a ‘social disclaimer’ stating:  “Some people invest based on past performance, but funds with low fees have the highest future results.”.  All participants also took a test to grade their level of financial literacy.

The were a number of informative results:

– Performance chasing behaviour was evident across all trials, in both initial and subsequent fund selections. The fund with the highest returns in the last trial was selected with greater regularity.  Recent performance was more influential than fees.

– The standard performance disclaimer had limited impact on reducing performance chasing behaviour and led to worse outcomes for those with low financial literacy and no experience.

– In the second experiment participants chose the low fee option more often when they had been shown the ‘social disclaimer’.

– Participants with lower financial literacy and no investment experience actually chose the expensive fund more frequently when they received the standard disclosure: “Past performance does not guarantee future returns”.

– Participants were more likely to choose the low fee option as the trials progressed, but the overall effect of this was modest.

Of course such ‘lab’ studies are imperfect and never a substitute for natural experiments. Furthermore, the paper does not provide full details on the exact scenarios faced by the participants or a granular breakdown of the results achieved .  These issues notwithstanding there are a range of insights that are worthy of greater research and consideration:

-It is fascinating that participants tended to favour highly uncertain (indeed random) future performance at the expense of the certain performance advantage of a cheaper fund.  Their decisions were made absent any information about the forthcoming returns of the funds meaning choices were guided only by fees or previous results.  This could be an example of our struggle to accept randomness and tendency to see information in noise (the outperforming fund must have some advantage).  Or, as the authors suggests, higher fees can be associated with quality.

– In the real world, performance chasing behaviour is typically intertwined by some form of narrative.  A story that validates why past performance will indeed be a prelude to future excess returns – it could be the exceptional skill of a certain fund manager or the wonderful prospects of a particular economy.  In this experiment there was no story to tell just the numbers, and individuals still tended to be led by them.

– As suggested by the authors, one of the potential issues with recurring fees is that because they can be small relative to the volatility in performance, investors may neglect to attend to them, or fail to understand the huge influence they can have when compounded over the long-term.

– Those with low financial literacy performed worse in the task, which goes to reaffirm that it is individuals in such groups who require the most protection and direction.

– Perhaps the most fascinating aspect of the study is the role of the disclaimers. The “Past performance does not guarantee future results” wording has always seemed a woefully ineffective message because if offers no meaningful guidance.  The social disclaimer provides a clear nudge by directly stating that lower fee funds achieve better outcomes than higher fee funds. Whilst this wording is not without its own problems – fees alone are not sufficient to make an investment decision –  it does suggest that such disclaimers could be re-worded in a manner which genuinely helps investors, particularly those with less experience and knowledge.

Although it is no surprise to observe performance chasing behaviour;  it is particularly interesting to see it play out in a sterile, artificial environment absent the narratives, newsflow and incentives that contribute greatly to performance chasing in the real world.  The structure of the research also allows for a clear distinction to be made between past performance and fee levels as a decision driver, which are otherwise impossible to isolate.  The study provides further support to the idea that past performance and neglect of costs are real problems for investors, and behavioural interventions – such as changing disclaimer wordings – might be part of a solution.

https://www.thinkforwardinitiative.com/research/persistent-chasing-of-past-performance-when-selecting-mutual-funds

Why is Extrapolation so Dangerous for Investors?

At the start of the last decade everyone was bullish on emerging market equities.  It is hard to recall now, but it was the consensus trade.  You couldn’t attend a meeting or conference without being told how many people there were in China or how underwhelming the growth prospects were for developed economies compared to their emerging counterparts.  The irresistible optimism was to prove unfounded as the asset class delivered a prolonged spell of underwhelming performance.  This disappointment is merely one prominent example of perhaps the most common (and often damaging) investor behaviour; we take past performance, combine it with a persuasive story and extrapolate into the future.

Dealing with uncertainty

 Our desire to extrapolate is an understandable reaction to the uncertainty of financial markets.  If we cannot predict the future then our best approach may be to assume a continuation of previous trends.  It is not, however, simply a case of presuming performance patterns will persist; the power of extrapolation comes from the narrative that we use to explain what has happened in the past.  The stories we tell are what make us believe that things will continue.

When themes or narratives are discussed regarding investment decisions; it is often done in such a way that suggests that the story is driving the price.  This is misleading.  On many occasions the reverse is true – our inability to explain complex, chaotic markets means that we wrap a compelling narrative around the performance after it has occurred.  Extrapolation in investment is driven by a circular relationship between these two elements.  Performance creates story creates performance.

These post-hoc rationalisations are hugely problematic however.  Whilst the futility of market forecasts and predictions about future market movements is often discussed, this doesn’t go far enough.  On most occasions it is difficult to provide robust and complete explanations for market movements even after the event.  If markets are largely chaotic and random then simply observing outcomes does not mean you can then draw a straight line of cause and effect.

We cannot confidently explain the past in financial markets, let alone predict the future.  Given this, how do we construct narratives that support our desire to extrapolate?  We simplify.  Let’s take the argument that reinforced the extrapolation of emerging market outperformance in 2010; fundamentally, it can be distilled to this: economic growth in emerging markets will be higher than in developed markets in the future.

Although a naive and fragile argument; from an extrapolation perspective it is incredibly powerful because it is easy and ‘feels’ right – of course you want to invest in higher growth markets.  Also, crucially, there was evidence to support it.  By evidence, I mean that in the prior decade emerging market equities hugely outperformed and emerging market economic growth was higher than developed markets.  Whether the relationship between these two variables is strong or not (it’s not) is immaterial – what matters is whether the story is a convincing explanation of performance.  Once the link is forged between narrative and price, it becomes hard to break.  Any attempts to refute it are met with puzzlement – “of course it is right, haven’t you seen the performance?”

Creating a simple, powerful story to describe historic performance is ineffective and illusory, but it is also relatively harmless if all we are doing is explaining the past.  Unfortunately, that is not all we are doing.  The narratives we create don’t just help us decipher yesterday; they set our expectations for tomorrow.  We believe that if our story still holds, then performance will persist.

Extrapolation in three easy steps

 Extrapolation is an exercise in simplifying things that are uncertain or unknowable in order to make some form of prediction.  The process for extrapolation in investment contains three crucial steps:

1)      Take a significant performance pattern: Performance needs to be meaningful and sustained – a convincing narrative is hard to forge if returns are noisy or absent a convincing trend.

2)      Construct simple explanatory narrative:  Markets are too complex to understand or define the precise drivers of previous performance.  With a great deal of effort we can make educated guesses, but it is far easier to simplify the task by creating a straightforward explanation that is understandable, convincing and difficult to refute.

3)      Consider whether the narrative holds into the future:  Our desire to weave simple, intuitive and optically powerful explanations often means that we assume the performance trend will continue provided the narrative explanation holds.  If emerging markets grow faster than developed markets their equity markets will continue to outperform, if rates stay low quality will outperform value etc…

We create a compelling narrative to justify why past performance has been particularly strong or weak.  We then use that same narrative to predict its continuation.

The problem with extrapolation

Investors can and do make money from the propensity of other investors to extrapolate, but whilst it creates opportunities; it also causes a host of problems:

–         Extrapolation is an exercise in simple forecasting:    Our explanation for what happened in the past quickly becomes our prediction for the future.  This is dangerous because we cannot accurately explain the past let alone predict the future.  Even in the event that we are correct in our diagnosis of the drivers of previous returns; it is unlikely that they will persist unchecked.

–          We often imply structural changes when extrapolating:  Although much market behaviour is inherently cyclical, when we extrapolate it often tends toward being a structural pronouncement.  Things are either in a new paradigm or dead, rather than be in some form of natural cyclical decline or boom.  This is because when we extrapolate we do so in perpetual terms – this will continue indefinitely.

–          Stories are often wrong and missing key variables:  The narratives we utilise are almost always too simplistic to be meaningful or even close to comprehensive.  Sometimes they are entirely wrong.  Yet when it comes to stories it is not the validity that matters but the coherence.  There will be some occasions in financial markets when Occam’s razor does apply – and a simple explanation does fit – but it has to be supported by robust evidence, not just be a convincing yarn.

–          Extrapolation can leave us concentrated and overconfident: The longer a performance trend persists and the more investors participate, the more the underpinning narrative is bolstered.  Our growing assurance can leave us unable to see any other environment prevailing; indeed, doing anything but following the dominant trend probably comes at a cost.  It is at these times when we are most vulnerable to abandoning sensible investment disciplines such as diversification.  After all, the more certain you are about the future, the less you need to diversify.

Extrapolation is simple.  If something has worked well in the past you don’t have to expend any energy explaining why it will work in the future – the evidence is in front of you.  It is easy to convince yourself and it is easy to sell to other people (try marketing an investment strategy that hasn’t worked for the last five years).  As investors we use it persistently; whether it is thinking about asset class returns, building a portfolio or selecting active managers.

Extrapolation can be effective.  Performance trends in markets can and do persist for prolonged periods.  Yet exploiting these trends is more about understanding the behaviour of other investors (the Keynesian beauty contest), than it is ‘knowing’ the fundamental drivers of market performance (past or future) or telling an accurate story.

The central problem with our tendency to extrapolate is that when we do so we are implicitly making unjustifiable assumptions about financial markets: that they are predictable, that there are simple explanations and that things won’t change.  Holding such beliefs rarely ends well.   Yet despite the pitfalls when performance and narrative align it is hard to imagine that the prevailing trend will ever cease.

Investment Risk is about the Extreme and the Unseen

When an event such as the coronavirus pandemic hits markets, investor attention is inevitably drawn to the damage that can be wrought by high impact, unpredictable episodes. This is understandable as such occurrences can have disastrous financial consequences.  I touched upon managing the risk of ruin in my post on ergodicity[i], and Morgan Housel recently addressed the tail-end consequences of risk in typically eloquent fashion[ii].  Yet whilst it is important for investors to prepare ourselves as best we can for such scenarios; we should not focus solely on the extreme, arresting, outlier happenings.  There are investment risks that we face that are small, slow and creeping – often going unnoticed –  but compound to result in unnecessarily poor outcomes.

The tail risks investors face are problematic both because of the scale of their impact and their unpredictability.  We know that they are inevitable but we are never entirely certain what form they will take.  Most of us prepare for the next ‘extreme’ market event by taking steps that would have protected us from the previous one.   Whilst incredibly painful when they occur, a combination of appropriate time horizons, sensible investment disciplines and measured behaviour means that investors can withstand most extreme events.

At the opposite end of the spectrum from these conspicuous, striking risks are those risks that cause harm through time because we are prone to ignore their deleterious impact.  This can be because they are small and incremental; taking time to grow into something material – if we ever realise, it is too late.  Or they can be risks where we are making a temporal trade-off.  We carry out actions that make us feel better now, but increase the risks faced by our future self.

Risks that we don’t notice:  The most obvious example of an often unseen risk is high investment fees. In any given day, month or year high fees are likely to seem inconsequential, if they are noticed at all.  Yet the compound impact over a lifetime of investing can be staggering.  This is far from a dramatic, extreme event but more like a slow water torture.  The risk here is that we fail to meet our investment objectives, or are materially worse off than we could have otherwise have been.  It is not dramatic, or eye-catching, and many will not perceive it as a risk during or even after its realisation.  This does not mean that it cannot be profound.

Risks that make us feel good in the present, but at a great future cost:  There is a vast array of investment activities that can fall within this category.  Perhaps the most material is a failure to begin our long-term savings early enough.  Here we are liable to make our lives better now (by having more disposable income), but worse in the future because we diminish the influence of compounding.  This risk of undersaving in our younger years is one which we may either not realise at all or fail to appreciate its magnitude.  It is particularly pernicious because assuming the risk (either knowingly or unknowingly) makes our life more enjoyable in the present.

Another prominent ‘feel good today / repent later’ risk is overtrading.  Whenever we trade in our portfolios it is likely to make us feel better; very few investors are comfortable transacting in a way that causes immediate discomfort (value investors being a notable exception).  Whether we are chasing the latest momentum trade, switching to a flavour of the month active manager or raising cash in a period of market turmoil; we are probably doing things we feel good about in that specific moment.  Yet if we work on the safe assumption that most of us are terrible traders; the aggregate impact of all those trades is likely to leave us materially worse off.  Of course, we don’t perceive this to be a risk to our long-term outcomes because with each trade we think we are improving our situation (otherwise we wouldn’t be doing it).  The risk here is not about a single large trade blowing up our portfolios (which falls into the extreme category), but the compound impact of the performance chasing, the market timing and the costs incurred.  How many of us will look back and say: “I would have been better off if I had just left it alone”?

Exposure to catastrophic incidents is certainly a crucial consideration for all investors – whether they be the general (e.g. financial crises) or the specific (e.g. frauds) – but is not only the extremes that should concern investors.  Risks that seem small and inconsequential at any given point in time, can compound to have ramifications that are just as significant.

[i] https://behaviouralinvestment.com/2020/05/13/we-need-to-talk-about-ergodicity/

[ii] https://www.collaborativefund.com/blog/the-three-sides-of-risk/

We Need To Talk About Ergodicity

You have a gun which holds six bullets, but only has one in the chamber.  You use it to play a game of Russian roulette with a group of 19 other people.  Each of you takes one turn in spinning the chamber, holding the gun to your temple and pulling the trigger.  If you are successful you win £1m, if not, well, then you die. Whilst this may not be an appealing proposition, your chance of death is relatively low (17%), and potential for becoming a millionaire high (83%).  It is also far more attractive than an alternative version of the game where instead of playing with a group, you play on your own.  In this instance there are still 20 turns but each time the gun is directed at your head.  The odds on the outcome for you in this instance are not so favourable.

These contrasting approaches to Russian roulette are a typical example of ergodicity[i] [ii]. A system is deemed ergodic if the expected value of an activity performed by a group is the same as for an individual carrying out the same action over time.  Rolling a dice is an example of an ergodic system.  If 500 people roll a fair six-sided dice once, the expected value is the same as if I alone roll a fair six-sided dice 500 times.

The Russian roulette example is a non-ergodic system.  The expected value of the group differs sharply to the average of an individual carrying out the action through time.  In the group situation the average outcome is to live and become wealthy.  As an individual performing the activity through time – on average – I am dead.  In a non-ergodic system the group expected value is deeply misleading as it pertains to individual experience.

Although these may seem like somewhat frivolous examples, the concept of ergodicity is incredibly important.  Much of classical economics assumes about human behaviour is founded on the expected average outcome of the group (see Expected Utility Theory).  This works under the assumption that most environments or situations are ergodic, when in fact this is not the case.  The best starting point for understanding ergodicity economics is this article in Nature, by Ole Peters[iii].

Given the implications for classical economics, the idea of ergodicity is also incredibly important for behavioural economics.  Many of the ‘biases’ identified in this field are expressed as violations of the assumptions made in classical economics and therefore deemed irrational.  Yet what if the starting assumptions are incorrect in the first place? What if much of what classical economics says about decision making is based on the average outcome of a group; when my ‘rationality’ is best judged by considering my individual experience through time?

Ergodicity is not the most intuitive concept, so let’s take another example – home insurance. If we assume that insurance companies make a profit from selling us insurance on our houses, then surely it doesn’t make sense for anyone to buy insurance for their home?  The insurance company is making a profit, those buying insurance must be making a loss.  Yet this negative expected loss applies to the group average, the situation is different for the individual.  The experience of the group is irrelevant to me as an individual.  What I care about is the impact on my wealth through time – there is only one of me.  The risk of ruin from my house burning down is what matters.

The concept of ergodicity is also critical when thinking about major issues such as inequality. Let’s take the standard economic measure of economic growth – GDP – what does that tell us about individual experience? Very little[iv]. GDP is a group measure.  Therefore we have another situation where the average outcome of the group can be very different to any individual’s experience.  We could therefore enter a situation where economic growth numbers (measured by GDP) appear impressive, but they mask the fact that inequality is burgeoning – wealth is accumulating to a select, small group, whilst more individuals suffer (surely this couldn’t actually happen!?).  Focusing on extreme cases of success in non-ergodic systems can be incredibly deceptive.

Ergodicity and Behavioural Economics

Given the subject matter of this blog, it is perhaps worthwhile exploring a couple of examples of where the concept of ergodicity has implications for ideas in behavioural economics.  One of these was explored by Jason Collins.  In his blog[v] he looked at the following scenario, which draws on work from Ole Peters and colleagues:

“Suppose you have $100 and are offered a gamble involving a series of coin flips. For each flip, heads will increase your wealth by 50%. Tails will decrease it by 40%. Flip 100 times.”

This type of bet is often rejected by individuals, despite the expected gain being 5% of wealth at each flip.  Declining this type of bet is often put down to risk aversion.  But is turning down a bet with a positive expected value such a bad idea?

Collins ran a simulation of 10,000 individuals flipping the coin 100 times each. Whilst the average wealth reached $16,000, the median was only 51 cents. 86% of the population saw their wealth decline.

A bet that looked good on average actually led to catastrophic outcomes for most, whilst a select, fortunate few made huge amounts of money.  Again, the average outcome of the group was meaningless to most people.  And, as Collins goes on to explain, if you increase the number of coin tosses eventually everyone will end up financially ruined.

There is inevitably a lesson here for investors about the destructive power of negative compounding. And from a behavioural economics perspective there is also a valuable insight into why seemingly irrational decisions (turning down a bet with a positive value on average) can be viewed as rational when considering the experience of a given individual over time.

Probability Weighting 

Ergodicity can also matter when we consider how we ‘weight’ probabilities when making decisions.  In a recent paper Ole Peters and colleagues[vi] explored a key tenet of cumulative prospect theory – that people overweight the probability of rare events with extreme outcomes.

The authors argue that far from being an error of judgement, a propensity to ‘exaggerate’ the likelihood of low probability extreme events is a reflection of greater uncertainty.  Individuals have less information about uncommon events (their historic frequency is low) and therefore a greater potential for error in their assumptions.  This feature allied to the risk of ruin from an extreme event means that adopting a cautious approach to such likelihoods is prudent.

The idea of increased uncertainty about probabilities for rare, ruinous events is a compelling argument as to why a seeming overstatement of probabilities may not be an error of judgement.  There are, however, other pertinent issues to consider around how individuals gauge probabilities.  Rather than simply overstate the likelihood of extreme events, there is evidence that in certain circumstances individuals ignore certain high impact risks, seemingly applying a zero probability weighting to them.  Kunreuther’s work on insurance showed that individuals often don’t buy disaster insurance until after they have experienced a loss from such an event[vii].  My contention would be that an individual’s judgement about the probability of a low likelihood, high impact event is intertwined with its salience and availability.  We are less likely to ‘overstate’ the probability of an event if we have never observed it, or if it lacks any emotive qualities.  Our perception of risk needs to be over some ‘threshold’ for us to consider it at all.  We can’t worry about everything.

What Are the Implications for Investment Decisions?

There are a range of areas where considering ergodicity could influence investment making; not least in the sizing of ‘bets’ and the potential use of the Kelly Criterion, but that will be for future posts.  A simple example of where ergodicity might be important is in portfolio construction.  Let’s assume we are allocating to ‘alternatives’ in our portfolio and have modelled them on the basis of them delivering a 4% annualized return with 7% volatility (remember this is hypothetical).  Is the average expected return of a group of hedge funds that meaningful?  Not really.  This is a non-ergodic system – we are interested in the path of returns for the individual funds that we select; the average result of the group might match our forecasts (unlikely), but we could still end up with very poor results.

Concluding Thoughts

Given that the field of behavioural economics was forged on the identification of limitations in the assumptions of classical economics; it seems reasonable that ideas central to the amorphous field of ‘behavioural economics / science / finance’ should also be held up to scrutiny.  Whilst we should always be cautious about attempting to identify ‘one big idea’ that explains everything; the concept of ergodicity is crucial lens through which we should be observing decision making.  We need to talk about it more.

[i] https://medium.com/incerto/the-logic-of-risk-taking-107bf41029d3

[ii] https://taylorpearson.me/ergodicity/

[iii] https://www.nature.com/articles/s41567-019-0732-

[iv] https://ergodicityeconomics.com/2020/02/26/democratic-domestic-product/

[v] https://jasoncollins.blog/2020/01/22/ergodicity-economics-a-primer/

[vi] https://econpapers.repec.org/paper/arxpapers/2005.00056.htm

[vii] https://publicpolicy.wharton.upenn.edu/issue-brief/v4n7.php