So, what was it that caused the sell-off in risky assets and sharp increase in volatility? The Fed? The Bank of Japan? The end of an AI bubble? A soft employment number? The yen carry trade unwinding? All of the above? Something else entirely? Who knows? The truth is that financial markets are a complex, chaotic and deeply intertwined beast, which makes both predictions and explanations impossibly difficult. Not that this stops us attempting both. For most investors a rationalisation of events doesn’t even matter – markets are volatile; sometimes uncomfortable and inexplicable things occur. What’s more important is what happens to us during bouts of market turbulence. This is where the real damage is done.

Here are a few things to bear in mind:

– The fact that people are scrambling around to decipher what happened in recent days should be a salutary lesson in the folly of market predictions. We can’t even give confident explanations for events after they have occurred, what makes us think we can do it before!?

– When an unpredictable event occurs it unfortunately makes us increasingly susceptible to forecasts. We feel anxious and uncertain, so become even more desperate than usual for a comforting guide to the future.

– People who didn’t predict the market sell-off will confidently foresee what is to come: “I didn’t see this coming, I cannot explain what caused it, but I am going to tell you what happens next.”

– Trading around market / economic events is unbelievably hard. We only need to look at the wildly varying expectations for Fed policy through 2024 to see how fiendishly tough it is to do well.

– Everyone will start to say that “uncertainty has increased”. This cannot be true. It makes no sense to claim that we were more certain about things before an unpredictable occurrence. Markets are always uncertain, sometimes we are complacent.

– Living through periods of market tumult is always challenging, even over short horizons. It is far easier to deal with such spells in theory than in practice.

– A new market narrative will take hold incredibly quickly and everyone will start using a fresh set of buzzwords that are consistent with the current set of events.

– We will forget all of our prior market pontifications no matter how recently made. Nobody will remember panicking about stagflation / a rebound in inflation after some hot data prints a few months’ back.

– Everything seems obvious after the event. Of course US employment was weakening, of course the Mag 7 would come under pressure, of course the yen carry trade was a tinderbox.

– What is happening right now will be the most important thing, and we will easily and quickly extrapolate into the future.

– The present value of future cash flows from Japanese companies is not changing by 10% a day.

– This might turn into something more substantial, or we might be talking about something else next month. Usually it is the latter, sometimes it is the former.

Living through periods of turbulence is taxing. It is easy to talk about the long-term, staying invested, and compounding returns when markets are going up. It is an entirely different story when the reverse is true, but these are the times when behaviour really counts.

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My first book has been published. The Intelligent Fund Investor explores the beliefs and behaviours that lead investors astray, and shows how we can make better decisions. You can get a copy here (UK) or here (US).

Hendrik Bessembinder’s latest paper asks the question – which US stock has generated the highest long-term returns?[i] The answer is Altria Group (formerly known as Philip Morris). Over 98 years the tobacco company produced a cumulative return of 265 million percent! Based on this it would be easy to write about how lucrative it can be to sell addictive products, particularly when there are negative externalities involved, but there is something more important for investors to take away from the research – the power of compounding over the passage of time.

The cumulative total return of Altria seems astonishing, yet it equates to an annualised return of ‘only’ 16.3%.  On a standalone basis the figure does not seem remarkable, it is only when you apply time to it – long periods of time – that the dramatic impact of compounding takes hold.

Investors are inevitably drawn to high short-term returns (far higher than the 16.3% per annum produced by Altria), but these are inevitably unsustainable. That’s not an opinion, it is a mathematical reality. There is an inescapable gravitational pull as both time and size drags astronomical performance back toward normality.

Most investors neglect the power of time and the monumental advantage it bestows upon those with a sufficiently long horizon. We behave as if we are attempting to generate the highest possible return in the shortest possible time. Instead of compounding solid returns, we become destined to compound a succession of poor decisions with painful long-term consequences.  

It is not surprising that investors act in this fashion. We are wired to worry about and act on short-term risks and opportunities – it is a great strategy for evolutionary survival, just a terrible one for long-term investing. But it is more than that. The entire industry wants us to be impatient – whether it be selling the next great product or attracting our attention with the next alarming article.

Everything within us and around us seems designed to interrupt the positive force of compounding.

Investors who understand their time horizon, build a sensible portfolio and rarely make changes will be far better off than most. The trick is understanding ourselves and our environment well enough so that we avoid the temptation to veer from that course.  

Despite it being the best strategy for most investors, doing nothing (or at least very little) has a very bad reputation, so maybe it needs a rebrand. Instead, from now on, let’s call it: ‘Letting compounding do its work’.

[i] Bessembinder, H. (2024). Which US Stocks Generated the Highest Long-Term Returns?. Available at SSRN.

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My first book has been published. The Intelligent Fund Investor explores the beliefs and behaviours that lead investors astray, and shows how we can make better decisions. You can get a copy here (UK) or here (US)

Investors love talking about ‘skin in the game’. It has become something of a truism that a fund manager with substantial sums of their own money invested in their strategy will make better decisions. Not only is this a dubious generalisation but it also overly simplifies what can be quite a messy incentive problem. Skin in the game is an important idea but also one we can get wrong by misjudging where it exists, what it is telling us and when it might be a problem.

Incentives drive behaviour. If we could only know one piece of information to predict how someone would behave in a given situation, it would be their incentives. The idea of having skin in the game is a form of incentive alignment, it means that people directly experience the consequence (or risks) of their actions, not simply enjoy the benefits.

The decisions that we make will be heavily influenced by the distribution of potential outcomes that we face. An individual who bears all of the upside but none of the downside in a given situation, will make different choices to someone who faces the reverse.

It is too simplistic to say that having skin in the game leads people to make better decisions, but rather that the shape of incentive structures can profoundly impact our behaviour.   

Skin in the game is a critical concept, but one which investors can easily misjudge. Here are three examples:

Our skin in their game – The most obvious and frustrating scenario is where we believe that our interests are aligned with an investor that we are allocating money to, when in fact the structure is horribly asymmetric. Here we bear the majority of the downside risk, but the fund manager captures a disproportionate amount of the upside. The classic case of this is traditional hedge fund performance fees, where client capital is put at risk and large performance fees can be generated (and crystallised) for fleeting periods of outperformance.

The worst aspect of these fee structures is that they are often framed as better aligning incentives – “we have skin in the game – when our performance is poor, our profits suffer”, but this is a sleight of hand that ignores the inherent asymmetry. If things go badly wrong who bears the majority of the painful costs? If things go right who can generate transformational wealth? The answer to these questions should be the same, and it is not.

From a utility maximising, risk / reward perspective asset managers will always want to structure fees and incentives in ways such as this (this is not just a hedge fund issue, hello private equity), but it is a terrible structure for clients and not ‘skin in the game’ in any beneficial way.

Skin in the game as a negative signal – Now for an unpopular view. What if a fund manager investing heavily in their own strategy was a sign that they were not a good investor, but rather an overconfident and imprudent risk taker? What if having skin in the game was a useful signal for which fund managers to avoid?

This is an exaggeration for effect here, but it is not clear to me that a fund manager holding a significant portion of their net worth in their own strategy is always a positive, nor likely to encourage better decisions.

I am quite keen on investors who are humble, understand probabilities and are aware of the prudence of diversification. Such investors may be less likely to invest most of their wealth into their own investment strategy – the same one on which their career is reliant upon.

Aside from this issue there are other questions, such as: How does a fund manager having a large portion of their wealth invested in a strategy impact the choices they make? Are their objectives and risk tolerance aligned with our own? Given that fund managers have been known to be infected with a slight dose of hubris – should we be emboldened by their own (over)confidence in their strategy, or worried by it?

People seem to confuse it being ‘right’ that a fund manager invests in their own strategy (which it may be), with it necessarily being a positive indicator. In some circumstances it might be, in others perhaps not. It is a complex and nuanced area, not a useful heuristic.

Skin in different games – The final area is one where we tend to ignore issues around skin in the game and incentive structures: group decision making. Somewhat bizarrely little attention is paid to how groups of people make judgements – the behavioural literature is focused on the individual – despite most of our choices being made as part of a collective.

One of the primary reasons that boards and committees are so often dysfunctional is because they suffer from profound incentive misalignment problems. There is no meaningful, unified skin in the game because everyone is playing entirely different games. Often everyone around the room will have different incentive structures, time horizons and metrics that they are measured against, which will dominate their behaviour.

The CEO worried about share price performance, CIO focused on investment returns, the CFO trained on controlling costs and the independent Non-Executive hoping nothing blows up in their tenure. This is not a recipe for aligned, high quality decision making, but individuals with their risk and rewards attached to very different things. It shouldn’t be surprising that group decisions are defined by frustration, procrastination and uneasy compromise. Internal politics are generally about trade-offs between individuals with divergent incentives.

This is not just true of boards, most group structures face this problem, but never realise or acknowledge it – they just assume that everyone has a consistent set of objectives. Our assumption should always be that a group of people put together to make a decision do not have alignment of incentives or share skin in the game, unless an express effort is made to make it so.

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Incentives are almost certainly the most important driver of human behaviour and sometimes they are incredibly easy to observe, but, as the notion of skin in the game shows, they can be a little more complex than they might first appear.  

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My first book has been published. The Intelligent Fund Investor explores the beliefs and behaviours that lead investors astray, and shows how we can make better decisions. You can get a copy here (UK) or here (US).

Humans are prediction machines. We have to be. Every decision we make is based on predicting something. Whether it is the sun rising tomorrow morning, our car slowing down when we press on the brake pedal or the bank we use remaining solvent. Every choice we make is built on assumptions about the future. Despite this, I spend plenty of time annoying people by talking about how pointless (or worse) most financial market predictions are. So, are they essential or worthless? Well, it depends.

It depends because the types of prediction that investors make are wildly different – some are fiendishly complex and dynamic, whilst others are simple and stable. Before comparing some examples, let’s think about the factors that are likely to moderate the challenge posed by an investment forecast.

Our basic approach to any prediction should be Bayesian. This means that we have a set of potential outcomes that we apply probabilities to based on some starting assumptions or prior beliefs. Crucially, when we receive new and relevant information we update our priors and probabilities.

Let’s take a simplified example. I believe that there is a 70% chance that US equities will outperform European equities over the next twelve months because of stronger earnings growth (this is not true, I have no idea). Now, if US company earnings are surprisingly weak in the next quarter, I may revise down my probability.

Sounds simple, but there is a problem. While a Bayesian method is the best way to approach this scenario, it doesn’t mean it leads to good or helpful answers from an investment perspective. This is due to the forecast itself being just too difficult.

What makes a forecast hard? There are three key questions:

1) Can we define the variables that matter to our forecast? We need to be able to identify the factors that will influence the outcome of the thing we are forecasting.

The list of variables that could impact the relative performance of US equities and European equities over the next twelve months is huge and includes things that we know (such as earnings) and things that we don’t (unexpected events).

2) Is the group of variables that matter stable? The more the factors that matter change, the harder it is to make good predictions.

It is not just that the list of variables that matter is long and unknowable, but the relative importance of them is not constant. Maybe earnings will matter this year, maybe a pandemic the next.

3) How predictable are those variables? It is one thing identifying what the variables of importance are, but we still need to be able to predict them with some level of accuracy.

We don’t just need to define the factors that will influence the relative performance, we need to be able to predict them. Even if earnings growth was the most important variable in any given year, we would still need to forecast it well.

This type of forecasting is exceptionally tough, even if we take a sensible, measured approach.

All our investment decisions are a type of forecast – does this mean they are all equally problematic? No, they are not. Let’s take another example that seems similar at face value, but is an entirely different proposition.

Imagine we have thirty years to retirement and invest the majority of our long-term savings into equities. We are making a forecast here – that investing in the stock market is the best way to grow our wealth over time. What assumptions are we making in this instance?

– That economies will grow in real terms.

– That corporate earnings growth will be closely linked to economic fundamentals.

– That shareholder rights will be upheld.

Now, we might want to expand this list a little or be more nuanced, but in basic terms these are the elements that will impact our forecast. Over the long-run these are likely to be the aspects that matter, they are unlikely to change and we can predict them with reasonable confidence.

There are, of course, no guarantees. There is by no means a 100% probability that equities are the right place to be even over thirty-years – there are all sorts of remote but not impossible adverse scenarios – but the likelihood we should attach to this being accurate is far, far higher than our one-year market conjecture.

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As much as I dislike admitting in, we are constantly making forecasts about financial markets – it is inescapable. That doesn’t mean, however, that we cannot differentiate between predictions that are necessary and reasonable, and those that are impossibly difficult and almost certainly damaging.

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My first book has been published. The Intelligent Fund Investor explores the beliefs and behaviours that lead investors astray, and shows how we can make better decisions. You can get a copy here (UK) or here (US).

Although I am averse to making financial market forecasts, I can say with some level of confidence that over any long-run horizon most investors will have to encounter painful periods of losses in equity markets. Some seem unaware of this (or at least behave as if they are) while others spend most of their time attempting to predict when such phases will occur. Neither of these will lead to good outcomes.

If I am confident that severe declines will happen, do I have anything to say on when they will arrive? No. I have little idea. The next one might begin tomorrow, or in ten years’ time. They have transpired in the past and will happen at some unpredictable point in the future.

The difficulty of experiencing and living through tumultuous times mean that many, many investors dedicate themselves to reading the runes of financial markets. Seeking that ever elusive goal of capturing the higher returns available, while avoiding the downside risk that comes as part of the bargain.

This is a fool’s errand.

The cost of consistently attempting to predict the next equity market drawdown – and often being wrong – will be pernicious and permanent. The compound impact of these poor decisions will likely do far more lasting damage than the next bear market we experience.

If we are not busy predicting the gyrations of equity markets, the other major risk is that we are not expecting such drawdowns to occur at all.  While we should always be surprised at the cause and timing of a bear market (because they are difficult to predict), we should not be shocked when they arrive. All investors must have their eyes wide open – they are a feature of equity investing, and they will feel awful.

To have a chance of benefitting from the compound impact of long-run investing, it is not enough to tell investors to focus on the distant horizon and everything will be okay. We must acknowledge that to get to that point we will have to live through some difficult months and maybe years.

When equity markets have performed well it becomes particularly easy to be complacent about the potential for future losses. This is because we are prone to extrapolate – if things are good now, we struggle to see anything else in the future and will often be entirely unprepared for experiencing a very different world.  

So, if we cannot predict torrid market conditions but equally should not be surprised by them, what should we do? We cannot simply say – equities could fall by 40% – that is an anodyne statement which is easily dismissed. Instead, we need to create some vivid expectations about what the landscape might be like. We won’t know precisely what will happen but there are patterns of behaviour that are likely be a feature:

– Economic news will be terrible.

– Financial market performance will be prominent on the general news.

– Everyone will become an expert on ‘the thing’ that has caused it.

– Investor behaviour in the run up to the bear market will appear wholly irrational and naïve.

– There will be constant images of red screens and traders with their hands on their heads.

– Certain styles of investing will be declared dead.

– Investing for the long-run will be professed as an outdated concept of a bygone era.

– Some forecasters will be claiming that this was inevitable having been predicting such an occurrence for 14 years.

– Some market forecasters will be predicting the end of the financial system / world as we know it.

– Everyone selling equities and holding cash will look incredibly smart in the short-term.

– It will be stressful and anxiety inducing.

– We will be checking markets and portfolios constantly.

– There will be stresses over liquidity in certain asset classes.

– It will feel like things are getting worse every day.

– Some hedge fund managers will become incredibly high profile for being so sagacious.

– Weeks will feel like years.

– All valuation metrics will be considered worthless because none will consider quite how bad it will get.

– Nobody at all will be thinking about the long-term.

– It will be difficult to envisage things getting better.

– Getting out of risky assets will probably prove irresistible.

Making smart decisions during these times is extremely difficult and simply talking about what it might be like will not make us immune from the psychological challenges. If, however, we set expectations that events like this are likely to unfold over the life of our investments (even if we cannot forecast the cause) it does make it somewhat easier to cope with them and, hopefully, follow the plans that we have in place.

It is also reasonable to assume that we are more vulnerable than ever to damaging choices in such environments. Not only have equity returns been unusually strong in recent years but we have more access to information, are more connected through social media and can trade more frequently. Fear and anxiety are more readily stimulated, and we can remove it with a couple of taps on our smartphone. It is easier than ever to make choices that feel good in the short-term but come with a long-term cost.  

Investors in equities win over the long-term by being optimistic, but that alone is not enough. We also need to be sufficiently realistic to understand that the long-term will include some torrid periods that will present the most exacting behavioural tests. If we don’t plan for those short-term challenges, we are unlikely to reach our long-run goals.

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My first book has been published. The Intelligent Fund Investor explores the beliefs and behaviours that lead investors astray, and shows how we can make better decisions. You can get a copy here (UK) or here (US).

Paul Richards and I were having a conversation recently about whether AI technology was making it easier to spot lies and deception. He asked me how I thought a ‘truth machine’ would impact the asset management industry and I responded (with tongue somewhat in-cheek): “it would destroy it”. This was the inspiration for our latest Decision Nerds episode where we discuss lies, mistruths and obfuscation.

In the episode we cover:

– A top five countdown of our favour asset manager ‘fibs’.

– Research that shows that while investment analysts think they are good at knowing when they are being lied to, they really aren’t.

– Whether AI is really better than humans at detecting lies.

– Why industry norms are likely to penalise the most open and transparent asset managers.

– How would a ‘truth machine’ impact investors and asset managers.

And lots more.

You can play the pod via the link below, or access at your favourite pod places.

Decision Nerds – Lying

When an online poker firm published analysis of 120 million starting hands (hold ’em) played through its website, its analysis showed that of the 169 non-equivalent beginning combinations only 40 were found to be profitable. Furthermore, half of all profits were attributable to five hands (AA, KK, QQ, JJ, AK-suited). Given this skewed distribution of outcomes a winning strategy seems immediately obvious, but all is not quite what it seems. Why is this the case, and what does it mean for investors?

An initial glance at the data might lead us to believe that the optimal approach is simply to avoid making large bets until we are dealt a hand with a disproportionately high probability of success. The problem of course is that in a game of poker we do not make decisions in isolation – other players will observe and react to our behaviour.

If we were only placing bets of consequence when we had extremely strong hands, it would be incredibly easy for most players to spot this. Our seemingly optimal strategy would quickly become the obverse.

Similar to poker, there are not likely to be that many investment situations where the odds of a positive outcome are firmly on our side, but unlike poker most of us don’t have to worry about other investors directly anticipating our behaviour and compromising our returns. Does that mean investors are free to wait for those the most attractive of setups – the proverbial ‘fat pitch’?

Unfortunately, it is not that straightforward. There are three reasons why:

– We are not sure what a strong hand is: Identifying circumstances where the probability of superior performance is elevated is not simple. In poker it is evident when we have a strong hand, but in investing there is inherently more uncertainty and variability through time. (Somewhat ironically, the most attractive situations are likely to arise at times of valuation extremes – the exact point where we are likely to believe that the odds of a positive outcome are poor).

– We will misjudge when we have a strong hand: Our conviction will almost inescapably be driven by what has performed well in the recent past, particularly if it is supported by a persuasive narrative. This will create the perverse scenario where our confidence increases as the likelihood of a good result decreases. Unfortunately, we are more likely to bet big on a bad hand.

– We will play too many hands:  In poker we need to play more hands than might seem ideal to keep other players from predicting our behaviour; whereas in investing we trade more than we should because there is an expectation that we need to be constantly active. The investment industry rewards heat not light. Markets are noisy and chaotic, perpetually generating new stories and discarding old ones. Each month or quarter the focus will be on a shiny new topic, and we are expected to react. There is a bizarre value attached to being a busy fool, with very few investors afforded the luxury of time and patience.

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The inherent unpredictability of financial markets allied to our own behavioural foibles means that investors are vulnerable not only to playing far too many hands but also increasing our stake as the odds deteriorate. Although this is a path to poor returns it does give us plenty to talk about while we get there.

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My first book has been published. The Intelligent Fund Investor explores the beliefs and behaviours that lead investors astray, and shows how we can make better decisions. You can get a copy here (UK) or here (US).

A topic I have changed my mind on during my career is concentration in funds. I used to be strongly of the view that it was only worth taking active investment positions if they came with high conviction – usually in the form of concentrated positioning – otherwise, what’s the point? Although I came to realise I was wrong about this, I am aware that many people far smarter than me remain advocates of this type of approach. Why do I think it is a problem when they don’t?

Fund concentration is not the easiest concept to define. There are obvious examples such as very focused equity portfolios with large weightings in individual companies, but there is more to it than that. Concentration doesn’t have to be about position sizes in stocks, it can come through an extreme sensitivity to a certain theme, concept or risk factor. It is about our exposure to specific and singular points of failure.  Could one thing go wrong and lead to disaster?

The key concept to consider when thinking about the risk of concentrated funds is ergodicity. This is a horribly impenetrable term, but at its core is the idea that there can be a difference between the average result produced by a group of people carrying out an activity, and the average result of an individual doing the same thing through time.

Let’s use some simple examples.

Rolling a dice 20 times is an example of an ergodic system. It doesn’t matter if 20 people roll the dice once each, or an individual rolls the dice 20 times. The expected average result of both approaches is identical.   

Conversely, home insurance is a non-ergodic system. At a group level the expected average value for buyers of home insurance is negative (insurance companies should make money from writing policies). So, why do we bother purchasing it? Because, if we do not, we expose ourselves to the potential for catastrophic losses. The experience of certain individuals through time will be dramatically different to the small loss expected at the average group level.

Investing is non-ergodic. Our focus should therefore be on our individual experience across time (not the average of a group); this means being aware of how wide the potential range of outcomes are and the risk of ruin.

In concentrated funds, the prospect of suffering irrecoverable losses at some point in the future is too often unnecessarily high.

‘Risk is not knowing what you are invested in’

One of the most common arguments made by advocates of running very concentrated equity portfolios is that it is an inherently lower risk pursuit because we can know far more about a narrow list of companies than a long list. If we have a 10 stock portfolio we can grasp the companies in a level of detail that is just not possible if we hold 100 stocks, and this depth of understanding means that our risk is reduced. The first part of this is right, the second part is wrong.

The problem, I think, stems from the fact that there are two types of uncertainty – epistemic and aleatoric. Epistemic uncertainty is the type that can be reduced by the acquisition of more data and knowledge. Here the idea of portfolio concentration lowering risk makes sense. Conversely, aleatoric uncertainty is inherent in the system; it is the randomness and unpredictability that cannot be reduced. It doesn’t matter how well we know a company or an investment, we are inescapably exposed to this. The more concentrated we are, the more vulnerable we are to unforeseeable events.

While I think a neglect of aleatoric uncertainty is at the heart of unnecessarily concentrated portfolios, there are other issues at play. Overconfidence is likely to be a key feature. we may be aware that the range of outcomes from a concentrated approach is wide, but that may be desirous to us because we believe that our skill skews the results towards the positive side of the ledger. Given our ability to fool ourselves and the aforementioned chaotic nature of the system, this seems to be a dangerous assumption to make.  

Unfortunately, there is also an incentive alignment problem. A wide range of potential outcomes from an investment strategy becomes very appealing if we benefit from the upside but someone else bears the downside. This asymmetry is inevitably one of the reasons why high-profile macro hedge funds so often seem to be swinging for the fence with concentrated views. The often-severe downside of the negative outcomes are borne primarily by the client (a situation no doubt exacerbated when a hedge fund manager is already exceptionally wealthy).

Running a very concentrated investment strategy places an incredibly heavy onus on being right and also leaves us acutely vulnerable to unforeseen events unfolding that can have profoundly negative consequences. Exposing ourselves to such risks wilfully seems imprudent and unnecessary.

Investors are likely to overestimate how much they know, and underestimate how much they cannot know.

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– Being wary of concentration does not mean increasing levels of diversification are always beneficial. There is a balance to strike.

– It feels important to note that the risk of concentrated strategies can be diversified by combining them, but we should still consider what the concentration levels say about the investor who is willing to adopt such an approach.

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My first book has been published. The Intelligent Fund Investor explores the beliefs and behaviours that lead investors astray, and shows how we can make better decisions. You can get a copy here (UK) or here (US).

Given how volatile and unpredictable financial markets are, thinking in probabilistic terms is an essential skill.  It allows us to acknowledge uncertainty, express our level of confidence clearly and gives us more freedom to change our mind. There is a problem, however. Expressing ourselves in probabilities doesn’t come naturally and is often actively disliked. At best it is regarded as spurious accuracy, at worst evidence of an absence of conviction. We value bold and singular predictions about the future, not caveats and caution. How do we encourage probabilistic thinking in a world that doesn’t want us to?

One idea I happened upon in Julia Galef’s excellent book “The Scout Mindset”, is the ‘equivalent bet test’, which is a decision-making tool described by Douglas Hubbard in “How to Measure Anything”. 

The concept is simple.

Let’s take a fairly generic claim that a professional investor might make. They think that the US ten-year treasury yield will rise above 5% before the end of the year. That’s great, but what does it actually mean? Are they certain that this will happen? (Given the historical accuracy of bond yield predictions, I hope not) Or are they only 51% sure? The difference matters a lot, but we have no idea. How do we find out? By creating an equivalent bet, where we are certain of the odds.

We say to our forecaster. There is now $100,000 at stake. We will give you this amount of money at the end of the year if your prediction on treasury yields is right. Alternatively, we will give you the same amount of money at the same time if you can pick a blue ball from a hat containing six blue balls and four red balls. You can only choose one of the bets – the treasury yield forecast or the drawing the balls from the hat.

If they decide to delve into the hat, then we know that their confidence in their bond yield forecast is less than 60%.

We can then adjust the ball selection bet to a point at which the forecaster is ambivalent about the two options. We then we have a reasonable guide to how confident they really are about their prognostications.

This is clearly an imperfect approach, a hypothetical $100,000 will almost certainly provide a different decision making response to a real sum of money, but it is likely to be broadly consistent and incredibly helpful.

Not only does the equivalent bet test encourage the forecaster to think about their judgment in probabilistic terms, it also provides a far greater level of clarity about both how confident an individual is and how well-calibrated (or not) they may be.

Whether we like it or not, we live in an uncertain, volatile and probabilistic world. Our decision-making approach should reflect this.

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Galef, J. (2021). The scout mindset: Why some people see things clearly and others don’t. Penguin.

Hubbard, D. W. (2014). How to measure anything: Finding the value of intangibles in business. John Wiley & Sons.

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My first book has been published. The Intelligent Fund Investor explores the beliefs and behaviours that lead investors astray, and shows how we can make better decisions. You can get a copy here (UK) or here (US).

Industries in which capital has become abundant and optimism unbridled often end up disappointing investors. Echoes of these capital cycle pitfalls are also evident in active fund manager selection. In the ‘alpha cycle’ a certain area of the market delivers high returns, stories then emerge not only about the compelling opportunities to be found but also about the savvy investors who are exploiting them. This intoxicating mix of unusually strong performance and seemingly irrefutable narratives draws increasingly large flows from investors who either believe the tales being woven or are compelled to chase the momentum. The more extreme this performance dynamic, the more investors are likely to mistake luck for skill, and the cyclical for the structural. Leading them to make the wrong decisions at a terrible time.*

It is a curious phenomenon that investors seem to behave as if capital flooding into a certain type of fund (whether that be investment style or market subset) is a prelude to higher returns in the future. Of course, there is the potential to capture an ongoing trend, yet from a fundamental perspective abnormally high returns are likely to be the result of assets becoming significantly more expensive.

Exceptionally positive performance now is drawing returns from the future – we are not going to make them again. We just act as if we will.
 
At the heart of this alpha cycle problem is our propensity to believe that what is cyclical is in fact a structural shift.  We are prone to see an active manager delivering strong performance in an in-vogue area of the market as someone with durable skill, rather than simply benefitting from largely unpredictable tailwinds that will at some point reverse. The most dangerous situation is when we begin to believe that there has been a permanent change in markets (XYZ is the only way to invest) and a particular active manager is the exemplification of this approach.  Here we have the glorious opportunity to be wrong twice – about both markets and skill.

As flows into a certain style of active manager increase, so too does the clamour to invest and the belief that it is the obvious thing to do (performance doesn’t lie). As our prospective future returns dwindle, our conviction increases.

At points of performance extremes, whether an active manager has skill will become irrelevant. If they are investing in part of the market enjoying euphoric sentiment and following a period of unsustainably high returns, any edge will be overwhelmed by the almost inevitable reckoning.

Selecting active fund managers who have enjoyed prodigious tailwinds comes with twin challenges. First, we are likely to grossly overstate the presence of skill (we cannot help but conflate performance with skill). Second, even if they do possess an edge, it is unlikely to matter because the odds of investing successfully in an area that already has stretched valuations and delivered exceptional performance are poor. 

We might argue that a fund manager has the ability to navigate such situations adroitly. Rotating out of areas that have delivered spectacular results and into less glamorous segments. Perhaps. Yet most managers have stylistic features or characteristics that almost inevitably leave them exposed to certain market trends. Furthermore, the type of fund managers that will attract the most attention during a particular cycle are likely to be the purest representation of whatever has been working.

The problems of the alpha cycle do present a potential opportunity. Fund managers with an out of favour approach who are investing in an unloved part of the market are likely suffering from poor performance and holding assets with far more attractive valuations. Even if they don’t have skill, the odds of a good outcome might be compelling (certainly better than investing at peak cycle).

There is a problem, however. We are very unlikely to believe managers somewhere near the trough of the alpha cycle have any skill, they are also likely to be haemorrhaging assets and they may be in danger of losing their job. It is never just a cycle remember; these are always profound structural changes at play.

I have framed the problems that stem from the cyclical nature of investment returns as an issue with active funds – it is not. These same behaviours exist across asset classes, regions and sectors. It is just that active funds have the additional danger of skill being used to justify unsustainable performance.

Investors need to adopt the mindset that unusually strong returns are a prelude to lower returns in the future and behave accordingly.

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* I use ‘alpha’ in this article in the broadest possible sense – general outperformance, rather than anything more technical.

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My first book has been published. The Intelligent Fund Investor explores the beliefs and behaviours that lead investors astray, and shows how we can make better decisions. You can get a copy here (UK) or here (US).