From an investor’s perspective, one of the primary challenges in dealing with events such as those unfolding in the Middle East is that, in times of stress and uncertainty, we quickly default to our most human instincts. These instincts are almost always at odds with sound investment decision-making. We stop doing the things we know work and get lured back into doing the things we know don’t.

The things we don’t know:

• How the situation in the Middle East will develop.
  
• What the short and long-term geopolitical and economic implications will be.
  
• How actions in the Middle East will interact with a multitude of other relevant dynamics in the months ahead.
  
• How financial markets will respond to any of these developments.
  
• Which issue might be the focus of investor attention next month.

The things we do know:

• Even those with considerable expertise cannot hope to forecast the unfolding consequences of geopolitical events.
  
• Predicting the first, second, and third-order financial market impact is even harder.
  
• Short-term volatility in markets is unlikely to have a predictable impact on long-run outcomes.
  
• High real returns for holding equities over the long term are compensation for bearing short‑term volatility.
  
• At some point in the future, equity markets will decline sharply because of some unforeseeable negative occurrence.
  
• Humans often hugely overweight high-profile and salient risks.
  
• Humans make poor decisions when emotions are heightened.
  
• Diversification is the best protection against an uncertainty.

Managing our behaviour as investors is about subduing some of our most human urges – urges that are useful in many contexts but typically disastrous for long‑term investment decision-making. Yet in conditions of uncertainty and anxiety, the compulsion to take action, to predict the unpredictable, and to focus solely on the immediate future often becomes overwhelming.

When we most need to remember what we know, we tend to forget it.

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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).

All opinions are my own, not that of my employer or anybody else. I am often wrong, and my future self will disagree with my present self at some point. Not investment advice.

Financial market commentators face a similar challenge to psychics. They are expected to be able to predict the future, but as that is an impossible task they instead have to develop strategies that make it appear as if they can.

In 1948, Bertram Forer carried out a psychology test for a group of his students. They were told that they would be given personalised feedback based on the results. Instead, all of the participants received the same feedback, which was taken from an astrology book. Despite providing the students with generic nonsense, they rated it 4.3 out of 5 for accuracy.

This was the first test of what became known as the ‘Barnum effect’. This was named after American showman P.T. Barnum, who was renowned for designing his shows so they felt tailored to each individual spectator. He also, perhaps apocryphally, is often credited with saying: “there is a sucker born every minute.”

Effective financial market commentary is dependent on successfully employing ‘Barnum statements’, which feature several important characteristics including:

– Statements have to be suitably vague or universally true:

“Fundamentals will start to matter again”.

– Statements should suggest a level of expertise with jargon replacing specificity:

“High yield credit is facing a looming maturity wall”

– Statements incorporate contradictory elements, making the commentator correct in any event:

“We expect bouts of volatility, but that will create opportunities”.

The best type of Barnum statements suggest authority, are impossible to prove wrong and can be used to prove you were right in the future.

Like a talented magician cold reading an awestruck mark, skilled market commentators can seem prescient, knowledgeable and accurate without ever saying anything meaningful.

It is easy to be critical of this behaviour, but it is an inescapable feature of the financial market machine. Everyone wants predictions about an impossibly complex and chaotic future, and there are not many ways in which to meet that expectation. Here are the options available:

Refuse to comment on imponderable things: This is almost always taken for a lack of knowledge, and it might be the last we hear from you. 

Tell the truth – that making forecasts about the short-term is impossible and does not really matter for long-term investors: Although this is the right answer, it will quickly get boring. You won’t be asked to comment again.

Make bold predictions about financial markets: This is generally a bad idea because you will be wrong a lot, but for a certain select few individuals – generally those that are wrong with charisma and gusto – it can be a lucrative path to pursue.

Use Barnum statements and say a lot of nothing: This is the safest route. You can sound sufficiently smart without ever being caught uttering something that you can be held accountable for. If you do it really well, it will look like you are right a lot of the time.

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People visit psychics to gain some comfort from the profound uncertainty of the future. The same is true of financial markets. The more unpredictable something is, the stronger our desire is to listen to someone who sounds like they can predict it. The amount of generic and vague financial market commentary is probably more a reflection on us than those who provide it.

–

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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).

All opinions are my own, not that of my employer or anybody else. I am often wrong, and my future self will disagree with my present self at some point. Not investment advice.

When the Seattle Seahawks won Super Bowl LX, Aden Durde became the first British coach to achieve the feat. As Defensive Coordinator he shared responsibility for marshalling the fearsome defense that was the central pillar of the Seahawks’ accomplishment. Following the game Durde was asked to account for the team’s success and he said: “we keep each other accountable and we have a common goal.” 

While this is a very simple explanation that belies a huge amount of work, it does get to the heart of what a team needs to be successful – and is certainly a necessary but not sufficient condition for a high calibre investment team.

Held to Account

In simple terms we can think of accountability as about an individual being responsible for their actions, but from a team perspective it is more about shared trust.

Think of the NFL Defensive Coordinator, alongside the Head Coach, they define a philosophy, design a scheme and call plays. They expect and trust players to operate within that framework.

Players have to trust both the guidance of their coordinator and coaches, but also their teammates. The success of any individual is heavily reliant on other people doing their job well.

Everyone in the team is accountable for outcomes, but also their individual success is incredibly dependent on everyone else within that team. If you trust the other people in the team then you are happy being accountable; if you don’t then accountability feels like an unfair burden.

Cultures within teams are typically defined by the level of trust. If people don’t trust each other, you can forget having a productive culture.

A Trust Deficit

A recent article written by Adam Butler, which I would recommend reading, argues that trust is an incredibly valuable (and largely invisible) common good that tends to be destroyed by market forces – as it is replaced with systems, controls and metrics, which both serve to erode trust and monetise its absence.

The removal of trust and its replacement with measurement is an undoubted problem. Butler tells the story of a nurse whose care and compassion looks like inefficiency and non-compliance on her hospital’s productivity dashboard.

The inviolable pattern is that information becomes a metric which becomes a control which becomes a behaviour. This always happens. 

We see this dynamic in all domains of life – when a footballer (soccer player) is tracked on the distance they run during a game, they will run about a lot – whether or not it is the right thing to do in the context of winning the game.

Controls also always grow and never contract – the system becomes defined by an absence of trust and builds on itself – each breach needing a new control. This can be maddening but is also extremely rational – trust is ephemeral, and controls and metrics are tangible. If something goes wrong, you need to show where the control is.

Atul Gawande’s compelling ‘Checklist Manifesto’ quickly degrades into reams and reams of checks and constraints – more than defeating his noble initial purpose.

This problem matters a lot for investment teams. Both because trust is integral to a high functioning team, and because financial markets are so incredibly noisy – some metrics and measures are required and useful, but vastly more are wildly ineffective. Not only does that mean that behaviour is driven by flawed measures, but the most valuable aspects of an investment approach are lost because they are unquantifiable in any reasonable way.

If you want to understand how an investment team behaves, you really want to know what it measures, how and why.

Of course, nothing is binary. There is a balance to strike – people can be incredibly vulnerable if they rely entirely on trust without appropriate controls in place, but the extension of that is not removing trust from the equation entirely. Without trust, you don’t have much.

Shared Goals

Alongside trust and accountability, perhaps the defining feature of any effective team is that each member of it is attempting to achieve the same thing. The ideal team structure is one which combines distinctive expertise and skills with a shared goal. Too often teams achieve the first part and fail at the second.

If people in a team do not have the same objectives then it becomes virtually impossible to create an environment of trust and accountability. How can I trust the other individuals in my team, if they are attempting to achieve something different to me? This is not a malign or malevolent mistrust, simply one borne from people following different incentives in an entirely rational fashion.

If you are disagreeing with something I say, is it because of your expertise or your incentives? Without shared goals, there is no real way of telling. (Although it is almost always about incentives.)

Imagine an extreme example where an investment team has portfolio managers incentivised only by outperformance, and a risk team incentivised to limit losses. This would be a crazy arrangement, which entirely ignores the trade-offs involved in any risk/reward decision. Although this might seem extreme, it is probably not far off where many end up.

When we are assessing the strength of an investment team, it is easy to assume that the goals are the same – they all want to generate strong returns, surely? Yet it is so easy, and common, for team members to have skin in different games – someone will live and die by performance, someone who needs to sell, someone who needs to avoid anything blowing up. All rational choices for individuals, but a mess for a coherent team.

One of the key challenges for larger investment teams (and an advantage for boutique firms) is that it is far easier to have goal alignment when there are fewer people involved.

Of course, shared goals are not necessarily a good thing in themselves. They are the best way to encourage aligned and complementary behaviour, but that behaviour can be good or bad depending on what the objective is.

When assessing an investment team it is critical to ask – what are the goals of the team (including anyone who has influence on how it makes decisions) and how are team members aligned with achieving this?

Teams need to pull together and in the right direction.

–

There is a lot that goes into building a defence capable of winning a Super Bowl; Aden Durde’s comment on accountability and common goals speak to the foundation that any effective team needs. We should think about these before anything else. 

—

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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).

All opinions are my own, not that of my employer or anybody else. I am often wrong, and my future self will disagree with my present self at some point. Not investment advice.

There have been some quite significant moves in asset prices in recent times. The dramatic increase in the price of gold over the past year has probably not escaped your attention, but it is not the rise in the yellow metal that is most interesting to me, rather the behavioural implications. How does extreme positive performance from any asset class or fund make us think and act, and why?

The behavioural drivers

Availability: The availability heuristic exerts a huge influence. This is the mental shortcut where we judge something not based on the weight of evidence, but by how prominent and frequent it is. When an asset class keeps hitting new highs, we conflate the volume of ‘evidence’ with its strength. There might be lots of articles, but if they are all saying the same thing, they are far from independent reasons for us to believe the performance will continue. In these situations, availability also leads us to understate risks – because we are not seeing the downside risks, we are likely to severely neglect them.

Stories: Humans understand the world through stories, and when an asset class is on an unprecedented run of good performance, plenty of stories will be told. We will treat these stories not just as explanations as to why something has occurred, but as a prediction of its persistence. We are inherently uncomfortable with things happening without a clear explanation, so to escape this dissonance we look for convincing explanations so that the world makes sense.

Extrapolation: The combination of high-profile performance and persuasive stories inevitably leads to extrapolation – the trenchant belief that what has been happening will persist into the future. The stronger and more sustained the high returns of an asset class, the more we struggle to see anything to stop it.

Fear of Missing Out: We are relative creatures. Our feelings about most things are framed by how it compares to something else (often other people). Two things happen in this regard when an asset is producing strong, high-profile performance. Those of us that don’t have exposure to the asset class will envy those that do, and those of us that do will wish they held more.

Feedback loops

This combination of behavioural factors creates powerful self-reinforcing feedback loops that can serve to further boost an asset’s performance. It works something like this:

Stage One: High returns from an asset class receive significant attention.

Stage Two: Stories are formed to explain the performance; these stories are prominent and convincing because performance is strong.

Stage Three: The combination of high returns and compelling justifications increase the belief that the trends will persist.

Stage Four: More investors are drawn into the asset class.

Stage Five: Returns are boosted by increasing investor appetite.

And so it goes on, until it doesn’t.

These feedback loops are driven by changes in investor behaviour and sentiment, and impact all asset classes over the short-run. For assets that generate cash flows, over time the phenomenon will be outweighed by the gravitational pull of valuations and fundamentals (at some point someone might say “maybe 100x earnings is a little too rich”). This doesn’t occur for ‘belief assets‘ that are not tethered to fundamentals (such as gold or crypto), which makes the range of potential outcomes incredibly wide.

Thresholds

Another fascinating aspect of what happens when the price of an asset rises substantially is at what point do different types of investors become involved (and when might they withdraw). This is clearly a complex topic, but the best model probably comes from Sociology and the work of Mark Granovetter. He explored the subject of crowd psychology and, in particular, how people in a group will have different thresholds for engaging in collective action.

For example, in a group of protestors, there might be some individuals who have an incredibly low threshold for engaging in disorder, whereas others have an incredibly high threshold. Those in the latter group won’t start throwing bricks until almost everybody else has. Granovetter’s argument is that the composition of a group and how behaviour cascades through it will be critical to how it acts.

In a financial market context, we have a huge group of potential investors all with different thresholds for participating in the ascent of an asset class. Day traders, momentum traders, macro hedge funds, all the way to long-term valuation-driven investors. The first group have a very low threshold for engagement, whereas the latter group might only invest when the pressure not to becomes too great (perhaps their job depends on it). The longer strong performance persists, the greater the chance that those high-threshold investors get drawn in.

This threshold model also matters for the reversal of extremely strong performance trends – the key question becoming the reverse: what is the threshold for investors to exit an asset class if returns start to deteriorate? This is what is typically meant when people talk of the dangers of speculative or ‘tourist’ money. Money with a low threshold for exit can create sharp and severe downside risks.

Although the overarching behavioural patterns of investors are similar, their motivations and strategies will be different, and that matters.

–

Extremely positive performance from an asset class can be caused by and encourage extreme behaviour. The more prominent the unusually high returns are, the more important it is to reflect on what might be driving our own decision making.

—–

---

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).

All opinions are my own, not that of my employer or anybody else. I am often wrong, and my future self will disagree with my present self at some point. Not investment advice.

It is hard to argue against the idea that geopolitical tensions are rising, and this type of backdrop can be incredibly difficult to navigate for investors. When the news is filled with discussions of war and conflict, it is natural to lose sight of our long-term investment objectives, and instead become focused on short-term, financial market worries. Yet, contrary to how these environments are likely to make us feel, a 2024 study showed that future equity market returns tend to be higher when coverage of war is more prominent in the media.

In a paper titled: “War Discourse and Disaster Premium: 160 Years of Evidence from the Stock Market“, a group of academics analysed 7 million New York Times articles spanning nearly 160 years and identified how much coverage was dedicated to a set of specific topics each month. They then linked the strength of this coverage to subsequent equity market returns from periods of one month to 36 months.

They found that of the topics considered, ‘war’ was the strongest predictor. Between 1871 and 2019, a 1 standard deviation increase in the intensity of war coverage in the New York Times predicts a 3.8% increase in annualised monthly returns. Over three years, the same rise in war coverage predicts 2.3% higher returns over the next 36 months.

In simple terms, the more that war was a focus of the articles in the New York Times, the higher subsequent returns were all the way up to three years out.

Why might war be good for equity market returns?

Although these results run counter to our behavioural instincts – not many of us treat war or rising geopolitical risk as a buy signal – that is probably the exact reason why this relationship appears to exist. For me, there are two plausible explanations for the phenomenon described in the paper:

• Heightened coverage of war and geopolitical risk leads investors to overstate the potential impact on financial markets and unduly mark down equity prices. This leads to lower valuations and higher future returns.
  
• Increased war coverage is an indicator of rising risk of economic and market catastrophe (what we might call disaster risk) and therefore equities are prudently priced lower. The expected return is greater because risks are also now more pronounced.

We can think of these explanations as being irrational (in the first case) and rational (in the second case). The consequences of both are the same – higher expected returns because equity markets have sold off and valuations are lower. In truth, both factors are probably at play.

Does geopolitical risk create buying opportunities?

Not so fast. There are some significant limitations with the study.

The first is the spectre of survivorship bias. While the data may show that future equity market returns rise alongside war coverage because investors overstate the risk of economic disaster, this is only true because there has been no such catastrophe. The world has to survive for us to see the results – so we cannot easily tell whether a pricing anomaly actually exists.

Equity market returns are predicted to be higher following periods of increased war coverage, provided the world doesn’t end!

(It may be reasonable to argue that if the world does end, we won’t be that worried about the returns from our equity portfolio).

The paper also does not advocate investing in specific countries that are the focus of increased geopolitical risks. It deliberately looks at general coverage of war and its impact on US equity markets. If instead it observed the impact on equity market returns of a country directly involved in a conflict, the results might be somewhat different.

Don’t compound geopolitical risks

The authors refer to the results of their study as a ‘war return premium’, which suggests it is something to exploit and potentially benefit from. However, I would frame the findings somewhat differently. When risks are prominent and emotive, we are liable to allow them to overwhelm our judgement, and prone to overstate the likelihood of worst case scenarios. We should guard against this.

If a ‘war return premium’ exists, it does so because of how investors react to the increased intensity of war coverage in the media. I think we should be less concerned about collecting the premium and more focused on not being the investor who pays it by making poor decisions in stressed geopolitical environments. The evidence suggests that our instincts during such times are likely to serve us poorly.

—

—

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).

All opinions are my own, not that of my employer or anybody else. I am often wrong, and my future self will disagree with my present self at some point. Not investment advice.

In 2025, I ran a prediction game for finance professionals. This year, to keep pace with current trends, I decided instead to pose ten questions about markets in 2026 to several AI large language models (LLMs). Will they do any better than humans, and will they agree with each other?

I used three AI LLMs for this task: ChatGPT (5.2), Gemini (3), and Claude (Sonnet 4.5). Here are the questions and responses:

1) Where will the S&P 500 finish 2026?
ChatGPT: 7,700
Gemini: 7,555
Claude: 6,800

2) Where will the FTSE 100 finish 2026?
ChatGPT: 10,600
Gemini: 10,750
Claude: 9,200

3) What will the ten-year Treasury yield be at the end of 2026?
ChatGPT: 4.5%
Gemini: 3.75%
Claude: 4.50%

4) Where will the GBP/USD spot rate be at the end of 2026?
ChatGPT: 1.28
Gemini: 1.38
Claude: 1.28

5) What will the dollar price of Brent crude oil be at the end of 2026?
ChatGPT: $57
Gemini: $55
Claude: $66

6) Will there be a 20% decline in the S&P 500 in 2026?
ChatGPT: No
Gemini: No
Claude: No

7) What will the dollar price of Bitcoin be at the end of 2026?
ChatGPT: $130,000
Gemini: $135,000
Claude: $78,000

8) Will the Russell 2000 outperform the S&P 500 in 2026?
ChatGPT: No
Gemini: No
Claude: No

9) What will the Federal Funds Target Rate (upper bound) be at the end of 2026?
ChatGPT: 3.25%
Gemini: 3.25%
Claude: 3.50%

10) What will the dollar price of gold be at the end of 2026?
ChatGPT: $4,500
Gemini: $4,900
Claude: $3,100

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It was reassuring that when I initially asked the AI models to make these predictions, they were reluctant and would only offer heavily caveated ranges – suggesting they may be better calibrated than humans. I had to persuade them to produce point forecasts!

Of course, the models were right to be reticent. No LLM will be capable of making accurate and specific predictions about a system as complex as financial markets. Still, there were some other aspects I wanted to explore.

Were the predictions consistent across models?

Absolutely not. While there was some consistency between ChatGPT and Gemini, Claude made several very bold calls (gold at $3,100, for example). Interestingly, Claude’s rationale was often the most “convincing.” It behaved like a particular type of market strategist – frequently wrong, but articulate and provocative – and therefore attracting the most attention.

Were the predictions internally consistent?

This is an important and difficult question to answer. The models could certainly sound internally consistent when asked to justify their views, but some combinations looked odd. For example, Claude was the most bullish on oil while also being the most bearish on UK equities – a scenario that could happen, but feels like an unlikely pairing (given the resource heavy nature of the UK market).

Are they better than human predictions?

I was asking the models to predict outcomes that, in my view, are impossible for either humans or LLMs to forecast with any real accuracy. Can they do this as well as a human? Almost certainly. Does that make it useful? Outside of marketing copy, probably not.

There are definitely more important things to spend tokens on!

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* Thank you to my colleague Duncan for suggesting this post.

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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).

All opinions are my own, not that of my employer or anybody else. I am often wrong, and my future self will disagree with my present self at some point. Not investment advice.

Having already written a piece on the similarities between how contestants in the TV game show The Traitors behave and our futile attempts to time financial markets, I thought I was finished with the subject. After indulging in the fourth UK series of the show, however, I realised there are so many excellent examples of human folly and perplexing decision-making that it felt worthy of a sequel.

For those uninitiated, there is a recap of how the game works in my previous post on this subject.

Here are some traitorous observations on investor behaviour:

We like being part of the herd. In the first banishment round of the latest UK series, 16 of the 21 contestants voted to remove the same person from the game. This broad consensus was reached despite there being no meaningful evidence to speak of. Of course, despite the agreement, they were entirely wrong.

We don’t like outsiders. After the first failed banishment, one of the 16 people who voted to remove a Faithful suggested turning their attention to a contestant who had voted differently, on the basis that this made them a potential Traitor. This was despite the majority having been incorrect in their prior accusation. It does not matter whether a group is right or wrong; it is safer to be in it.

We have a narrow circle of competence. A consistent feature of the game is that people in certain professions, such as lawyers and police detectives, believe they will be good at it and are reassuringly terrible. Part of me worries that people whose jobs involve making decisions under uncertainty do not seem to spend much time thinking about how to make good decisions. Another part simply concludes that our circle of competence is far narrower than we like to admit.

We are wildly overconfident. Along similar lines, a highlight of the most recent series is a retired police detective who plays the game with great confidence while aggressively and incorrectly accusing the wrong people of being Traitors. They also decided to keep their previous career a secret from the group, until revealing it to one other contestant who was, with wonderful inevitability, a Traitor. We are not as good as we think we are.

We are in thrall to expertise. Even though participants with so-called decision-making backgrounds are wrong at least as often as everyone else, other contestants remain in awe of their supposed expertise, no matter how often it proves unreliable. This is reminiscent of investors patiently waiting for the next insight from a market strategist who is right about as often as a coin flip.

We are attracted to new things. In the game, a banishment occurs every episode or day, and there is a strange behaviour whereby one day an individual may attract a great deal of suspicion and votes, but if they survive, they are barely mentioned the following day. We are drawn to shiny new things even when the evidence has not changed at all, much like investors latching on to the topic of the month and forgetting what they were previously obsessed with.

We are terribly calibrated. One of the most enjoyable and bewildering facets of the game is how often contestants say things like, “I am 100 percent sure X is a Faithful.” This is typically based on no evidence whatsoever and would be absurd even in situations where we have good reason to be confident. Here, participants have almost nothing to go on. We are very poor judges of how confident we should be about uncertain outcomes.

We need to survive: Although the game is focused on identifying Traitors in the group this isn’t really very important until we get near to its end because banished Traitors are replaced anyway. Participants shouldn’t care that much whether they banish a Faithful or a Traitor – they just need to make sure it is not them. Survival is the most vital and underappreciated thing in both the game and investing.

We cannot read people. Whether it is identifying a Traitor or judging a fund manager, we are awful at reading people yet remain convinced we are good at assessing both honesty and intentions. In a previous season, there was a contestant who was a professional magician whose job involved reading people. He was predictably hopeless at the game.

We ignore the most important things. Given how little useful evidence there is for identifying Traitors, particularly early in the game, the most sensible approach outside of choosing someone at random would be to ask: if I were a producer of this show, who would I select as a Traitor? Either contestants do not think this way, or, if they do, it is not shown on television because it would spoil the magic. My guess is the former.

We use salience as evidence. Judgements about who is a Traitor, especially early on, seem to be driven by what or who is salient, noticeable, or different. We mistake what captures our attention for what is meaningful. The current UK series has seen players frequently banished after making themselves the centre of attention – which is baffling behaviour.

While The Traitors is a light-hearted and convoluted game, it does a great job of revealing some of our most ingrained and peculiar behaviours. When we watch it and feel frustrated by the decisions being made, it is worth remembering that the contestants are simply being human. We do many of the same things in life and certainly when investing.

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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).

All opinions are my own, not that of my employer or anybody else. I am often wrong, and my future self will disagree with my present self at some point. Not investment advice.

From a behavioural perspective, our ability to meet our long-term investment objectives is really about one thing: managing the conflict between our desire to save for the future and our craving to make ourselves feel better in the present. This has always been an incredibly exacting challenge, but it is being exacerbated by an industry that seems set on innovations aimed at exploiting our weakness for immediate satisfaction.

Back in 1997, economist David Laibson published a paper titled “Golden Eggs and Hyperbolic Discounting”. In it he contends that our long-run savings and investment goals are frequently compromised by the behaviour of our present-biased selves.

There are two key elements to this:

• We fail to save sufficiently for the future because we choose to consume more today.
  
  
• We fail to keep our savings invested for the long run because of our response to short-term volatility and temporary market losses.

Laibson argues that investors are therefore blighted by having “too much” liquidity, which gives us ample opportunity to prioritise how we feel right now over our future needs. If we know that humans have this strong tendency, then illiquidity becomes incredibly valuable – because it protects us from ourselves.

While Laibson refers to the value of illiquidity, he is not advocating a wholesale switch into private markets. What he means is the use of commitment devices: steps we can take to prevent panic selling or otherwise stop us reacting in-the-moment at the expense of our future needs.

Commitments come in many forms – the most obvious being investment vehicles holding genuinely illiquid assets with lock-up periods. Not everything has to be so punitive, however. Soft frictions, such as auto-enrolment or the Save More Tomorrow scheme in the US, can also be extremely effective. Anything that reduces impulsive behaviour can deliver value many years from now.

While tools that encourage commitment can have a dramatic impact on behaviour, there is a problem: we don’t like being asked to commit. There are several reasons for this:

• It feels like a restriction of choice and agency. Adding friction to slow our decision making or reducing our ability to act can feel like a loss of freedom. Imagine if an investment platform introduced a 24-hour “cooling-off” period for every trade. This would likely be effective at limiting hot-state behaviour, but few people would choose to use it.
  
  
• We don’t think we need them. Commitment devices are designed to counter problems caused by our present-biased selves. To value them, we must first accept that we suffer from this behavioural failing. Of course, we all do – but we are far more likely to see it in others than in ourselves.
  
  
• Commitment devices involve trade-offs. Anything that reduces liquidity or limits action for the benefit of our future self comes with a present-day cost. This may not just be frustration at our inability to act; it could also mean being unable to access funds when they are genuinely needed.

Laibson made the argument about the dangers of “too much liquidity” nearly 30 years ago, but his case feels more relevant – and more urgent – than ever. Humans remain inescapably present-biased, yet the investment landscape has evolved in ways that exacerbate (and perhaps deliberately exploit) this bias, to the detriment of our long-term savings goals. There are a host of contributing factors, but these are the most culpable:

• ‘24 hour’ trading. Financial markets are increasingly ‘always open’, providing instant liquidity at all times. There is no restriction on our ability to react in the moment. This can be framed as technology-driven liberation or, more realistically, as a behavioural disaster.
  
  
• Constant portfolio access. Not only can we trade at any time, but we can live the minute-by-minute fluctuations in our portfolio values. Nobody would argue that investors should not have access to this information, but few have seriously considered the behavioural cost.
  
  
• More news and emotional stimulus. We are bombarded by financial news and opinion, a phenomenon greatly amplified by social media. There is more news, more noise, and more negativity. Humans make poor decisions when emotional stimulus is high and friction is low – precisely the environment we now inhabit.
  
  
• The financialisation of everything. Over time, more aspects of life are becoming financialised products to buy and sell – stocks, currencies, cryptocurrencies, sports, even political events. Everything has become something to trade. The line between gambling and investing is increasingly blurred, and may soon disappear entirely.
  

All of these factors increase the likelihood that we sacrifice long-term goals for short-term fulfilment. If Laibson was worried in 1997, he should be petrified today.

We can think of the golden egg as the future consumption funded by our savings, and the goose that lays it as a sensibly diversified investment portfolio. Financial and technological innovation is making it far easier to kill the goose.

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Laibson, D. (1997). Golden eggs and hyperbolic discounting. The Quarterly Journal of Economics, 112(2), 443-478.

(Laibson frames the ‘golden egg’ in a slightly different way in this paper, but the overarching point is the same).

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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).

All opinions are my own, not that of my employer or anybody else. I am often wrong, and my future self will disagree with my present self at some point. Not investment advice.