Why Do We Make Stupid Investment Decisions?

There is an excellent conversation detailed on the Farnam Street website between Shane Parrish and Adam Robinson about stupidity[i]; in particular, why we make decisions that seemingly lack intelligence, common sense or both.  I was particularly taken with the definition used for stupidity:

“Stupidity is overlooking or dismissing conspicuously crucial information.”

This clearly has resonance when we consider investment decision making – although financial markets are awash with randomness and uncertainty, there are obvious, vital and, often simple, cues that as investors we seemingly choose to ignore or disregard.  This results in poor choices and often disappointing outcomes.

We know that buying assets or funds after unusually strong performance is typically a bad idea, yet we still do it.  We understand the challenges of short-term trading and the benefits of long-term compounding, but can rarely resist the urge to react to what is happening right now.  These issues are not hidden from our view and they are paramount to our overall investment outcomes yet we often neglect them – but why?

Robinson notes seven factors, which can create situations where stupidity can flourish.  I consider each of these from an investment perspective below, whilst adding two additional issues, which I believe can also lead us toward ‘sub-optimal’ investment decisions:

Outside circle of competence: Economists predicting equity market moves, stock picking fund managers pontificating about macro-economics, amateur investors day trading.  There are seemingly no boundaries in investment – if you are involved then you can (and must) have a view on every aspect.  Investing is difficult enough without making decisions in areas in which you have no discernible skill, or where there is no evidence of anyone exhibiting consistently high levels of skill.

Stress:  If we engage with the constantly shifting narratives and random price fluctuations of financial markets it is almost inevitable that pressure and anxiety will lead us into decisions that are detrimental to our long-term goals.

Rushing or urgency: The hyperbolic and frenetic reporting around financial news means that we often feel the urge to act immediately.  We make decisions that will make us feel good in the very short-term, but come with a significant long-term cost.

Outcome fixation: The problem of outcome bias is particularly pernicious in financial markets – this is because of the inherent level of randomness in results (particularly over short-time periods) which means that sensible decisions can often appear quite the reverse. Sometimes stupidity is rewarded.

Information overload: There is simply too much noise in investment markets.  It is a struggle to work out which information is relevant (the vast majority of it is not) or how we should use it.  Given the sheer volume of data, our tendency is to react to it in an unpredictable fashion – considering information to be pertinent based on its salience, prominence, or availability.

Group / social cohesion: We often make investment decisions in a group context, and what other people are doing matters greatly to us.  Even if their judgements are seemingly irrational we will often seek to conform.

Presence of authority (expertise): Perhaps in no other field do we behold such an array of experts.  Each offers confident forecasts and compelling trade ideas – they are intelligent and confident, surely we should follow them?

Overconfidence / Ego: We are often aware of the crucial information, but do not believe it applies to us.  Even where the odds are stacked against us, we feel we have an uncanny ability to overcome them.

External justification: For professionals to justify their role and fees we must be seen to act frequently, being a busy fool is often more highly valued than ‘doing nothing’.

There is possibly no more fruitful setting for stupid decisions than financial markets.  Not only does the decision making environment lure us into mistakes, but the feedback we get is erratic.  Stupid decisions sometimes work and work enough to keep us coming back (like a slot machine giving you enough small wins to keep you interested). Furthermore, for every sensible investment rule there are inevitable exceptions – survivorship bias and tiny samples (n=1)  make us believe that either the evidence is erroneous or that we are the exception. We are not.

[i] https://fs.blog/2019/01/how-not-to-be-stupid/

Owning Quant Funds is Not Easy

2018 was a horrendous year for many quantitative funds and their investors (I speak from personal experience).  Although I do not wish to add to the commentary on the drivers of this particularly difficult period, it has brought into sharp contrast how different owning a systematic strategy is to holding a fund with a more traditional, human-led investment approach. Whilst both sets are often rightly grouped under the active banner, this definition belies the specific behavioural challenges investors face when holding a quant strategy – particularly when performance is poor:

Nobody Else to Blame – I have written previously about active fund investors suffering from a form of reverse disposition effect, that is a propensity to run winners and cut losers (unlike individual stock pickers).  This is because fund selectors benefit from an attractive form of optionality – if the fund we have chosen delivers outperformance then it is due to our superior selection skills, whereas if it struggles we can claim that the underlying fund manager is behaving in a manner that is inconsistent with our expectations (a healthy dose of outcome bias is also at play here).  This argument, however, does not hold for quant funds – in most cases we are investing in a defined system or process, if the strategy fails then it is far more difficult to apportion responsibility elsewhere – the process hasn’t changed, you picked it and it didn’t work.  Unlike qualitatively driven funds, there is no get out of jail free card.

Curse of Consistency – Somewhat ironically, the majority of quant funds possess characteristics that are consistent with what most fund selectors say they seek in traditional active managers – a clear philosophy and a disciplined investment process / decision making structure that will be applied diligently through varying market conditions. Unfortunately, whilst prudent on paper, the stated preferences of most fund selectors do not really hold under stress. When active funds suffer marked underperformance the reaction of investors is typically not: ‘I’m a glad you are remaining faithful to your process through this difficult time’, but rather: ‘things are going wrong, show me what you are doing about it’. This attitude is a major problem for quant funds as in most circumstances their reaction to poor performance should be to consistently apply the process on the basis that it will deliver over the long run. A strategy doing the same thing when it is not working for a sustained period is often unpalatable for investors, even if it is the right approach to adopt.

Does the Factor Still Work? Perhaps the most significant problem for investors in quant funds pertains to factor based strategies, which are seeking to exploit market anomalies to deliver a risk premium.  Owning such strategies requires a belief that the underlying factors exist (are robust) and will persist. It is this latter point that is the most challenging. Given that we can never have certainty why a particular factor has delivered a premium (we can only opine), we can equally never be sure as to whether it will continue to work. Perfectly valid factors can struggle for long spells and it is difficult / impossible to decipher whether these are the result of a structural shift extinguishing the factor premium, or a ‘temporary’ phenomenon. This uncertainty makes the task of myopic investors persisting with such strategies particularly difficult. Even if we pick the right factors we will have to sit through long periods when everybody is telling us they are broken.

Good Decision / Bad Outcome – Most quant funds are structured based on decision rules / algorithms that deliver on average, when applied over the long-term.  By definition, this means that there will be phases when they do not and, with a liberal dose of leverage applied, these can be painful.  Even a strategy with a high Sharpe Ratio, investing in proven factors, is prone to experience drawdowns that can be multiples of the long-term expected volatility.  Averages hide a multitude of sins, and sensible decisions can come to look anything but.

Black Box Stigma:  Quant funds unquestionably carry a stigma. They are blamed for a variety of ills, including (simultaneously) subdued market volatility and extreme bouts of volatility (apparently severe short-term market declines only began occurring with the onset of algorithmic trading). Of course, we should never invest in something we don’t understand – but this applies to all types of strategies.  How much do we really know about the genuine drivers of decision making in a human-led investment process? Is the behaviour of a systematic trend following strategy more opaque than a discretionary global macro manager?

Discussing quantitative funds into one homogenous group is not particularly helpful and obscures the sheer array of approaches that can be broadly classified in this cohort.  Each strategy should be assessed on its own merits – there are bad quant strategies as there are poor qualitative strategies.  Investors, however, need to be acutely aware of the distinct behavioural challenges that arise from owning systematic strategies and be prepared to manage them if they are to successfully invest in such approaches.

 

Can More Information Lead to Worse Investment Decisions?

It is without question that investors now have easy access to more information than ever to guide decision making; optically, this surfeit of data appears to be a positive – who doesn’t want more ‘evidence’ to inform their judgements? Yet there are a number of potential drawbacks, most notably the challenge of disentangling signals from a blizzard of noise in order to make consistent decisions.  For this post, I want to specifically address the potential consequences of information growth and its impact on our precision and confidence levels.  Whilst we often believe that more information can improve our accuracy (the number of correct decisions we make), in certain situations all it may be doing is increasing our (unfounded) confidence.

There have been a number of studies in this area, the majority of which reach similar conclusions.  Tsai, Klayman and Hastie (2008)[i], tested the impact of additional information on an individual’s ability to predict the results of college football games and their confidence in doing so correctly.  Participants in the study had to forecast a winner for a number of games based on anonymised statistical information.  The information came in blocks of 6 (so for the first round of predictions the participant had 6 pieces of data) and after each round of predictions they were given another block of information, up to 5 blocks (or 30 data points), and had to update their views.  Participants were asked to predict both the winner and their confidence in their judgement between 50% and 100%. The aim of the experiment was to understand how increased information impacted both accuracy and confidence.  Here are the results (taken directly from the study):

confidence

The contrasting impact of the additional information is stark – the accuracy of decision making is flat, decisions were little better with 30 statistics than just 6, however, participant confidence that they could select the winner increased materially and consistently.  When we come into possession of more, seemingly relevant, information our belief that we are making the right decision can be emboldened even if there is no justification for this shift in confidence levels.

For this research, the blocks of information were provided at random and the participants were amateurs – would the same relationship hold for professionals who were able to select the information they believed to be most pertinent?  An unpublished 1973 study by Paul Slovic (cited by the CIA[ii]), takes a similar approach but in this case with experienced horse race handicappers. Unlike in the college football study, the handicappers were allowed to rank the available information by perceived importance (from a list of 88 variables) and then had to predict the winner of an anonymised race when in possession of 5 pieces of information, then 10, 20 and 40 (by order of their specified preference / validity).  The results obtained were consistent with the aforementioned football study – accuracy was consistent despite more information becoming available, but confidence increased as the number of available statistics rose.

There are two important issues for investors to consider when looking at this type of outcome: i) There are probably less relevant pieces of information than we think, ii) There are a number of negatives around the accumulation of too much information – one of which is overconfidence.

More information does not necessarily lead to better decisions: In the investment industry it can often feel as if it is the amount of information or evidence that matters, rather than its validity.  Provided a research report is long enough, the conclusion must be sound.  I would contend, however, that for many investment decisions there are only a handful of information points that are relevant, distinct, and materially impact the probability of a positive outcome.  If this is the case, why is there such a desire for more and more information?

– We don’t know what that relevant information is, therefore we include everything we can find.

– We struggle to realise that many pieces of information are telling us the same thing.

– In random markets, noise can be mistaken for relevant information.

– If a decision goes wrong, we at least want to show that we did a lot of research to support it.

– It is difficult to sell our investment wares if we simplify our decision making to a select few variables.

– It we make simple decisions based on a narrow range of information we can look lazy, inept and unsophisticated.

– We feel more comfortable / confident in a decision if it is ‘supported’ by more evidence.

– It is possible that information that was once relevant ceases to be so because of some ‘regime shift’.

This combination of factors (and others I have failed to mention) means that it is incredibly difficult not to focus more on the accumulation of information rather than seek to identify the information that matters.

More information can lead to overconfidence: It is not simply the case that more information might not result in greater decision making accuracy, but that it can lead to us becoming more overconfident and poorly calibrated in our judgements.  Whilst we often believe that ‘new’ information bolsters the case supporting our choices, on many occasions this additional evidence may simply be a repetition of prior information (merely in a different guise) or be erroneous with no predictive power (a major problem in an environment marked by uncertainty and randomness where things that look like they matter, actually do not).  As we receive more information, therefore, we are prone to believe that we are more accurate in our decisions, when there is often no justification for this. This can create an anomalous situation where behaviour consistent with being diligent and thorough, actually results in worse investment decisions being made.

Judging the balance between carrying out sufficient research and becoming overly confident by collecting reams of superfluous data is fraught with difficultly, however, all investors should think more about what is the most relevant information, rather than concentrate simply on the accumulation of more.  For professional investors, a simple idea is to decide which pieces of information they would use if there was a restriction (of say only 5 or 10 items) and then monitor the outcomes of decisions made utilising only these select variables.  Such an approach forces us to think about what evidence really matters to us, whether it is effective and what value we might add over and above such a basic method.

[i] Tsai, C. I., Klayman, J., & Hastie, R. (2008). Effects of amount of information on judgment accuracy and confidence. Organizational Behavior and Human Decision Processes107(2), 97-105.

[ii] https://www.cia.gov/library/center-for-the-study-of-intelligence/csi-publications/books-and-monographs/psychology-of-intelligence-analysis/art8.html

50 Reasons Why We Don’t Invest for the Long-Term

Investment is a long-term endeavour designed to meet our long-term financial objectives, so why do we spend so much of our time obsessing about the short-term and almost inevitably taking decisions that make us worse off?  Well, here are 50 reasons to start with:

1: Because it is boring.

2: Because markets are random and it’s difficult to accept.

3: Because of short-term benchmark comparisons.

4: Because we are remunerated based on annual performance.

5: Because of quarterly risk and performance reviews.

6: Because there is always something / somebody performing better.

7: Because we watch financial news.

8: Because we think we can time markets.

9: Because even good long-term investment decisions can have disappointing outcomes.

10: Because the fund we manage charges performance fees.

11: Because short-term losses are painful.

12: Because we forget about compounding.

13: Because we are obsessed with what is happening right now.

14: Because we are poor at discounting the future.

15: Because we will be in a different job in three years’ time.

16: Because we extrapolate recent trends.

17: Because we check our portfolios every day.

18: Because it is so easy to trade our portfolios.

19: Because we think poor short-term outcomes means that something is wrong.

20: Because we make decisions when we are emotional.

21: Because we think we can forecast economic developments.

22: Because we think that we know how markets will react to economic developments.

23: Because we compare our returns to the wrong things.

24: Because it is hard to do nothing.

25: Because regulations require that we must be notified after our investment falls by 10%.

26: Because it feels good to buy things that have been performing well.

27: Because there is too much information.

28: Because we don’t know what information matters.

29: Because we don’t want to lose our job.

30: Because nobody else is.

31: Because we need to justify our existence.

32: Because we think we are more skilful than we are.

33: Because we work for a listed company.

34: Because we don’t want to lose clients.

35: Because we think one year is long-term.

36: Because assets with high long-term return potential can be disappointing in the short term.

37: Because we think performance consistency is a real thing.

38: Because we don’t want to spend much of our time looking ‘wrong’.

39: Because the latest fad is alluring.

40: Because there is a new paradigm.

41: Because we vividly remember that short-term call we got right.

42: Because we can’t tell clients we haven’t been doing much.

43: Because we think we are better than other people.

44: Because we have to justify fees.

45: Because we don’t want to be invested through the next bear market.

46: Because we think short-term news is relevant to long-term returns.

47: Because short-term investing can be exciting.

48: Because we have to have an opinion.

49: Because there are so many experts and they are all so convincing.

50: Because it seems too simple.

Adopting a genuinely long-term approach to investment is one of the few genuine edges or advantages any investor can hope to exploit.  Unfortunately, it can feel as if everything is conspiring against our attempts to benefit from it – but that does not mean we should not try.

 

Is There A Behavioural Premium for Illiquid Investments?

I would like to make clear at the outset that this post is not about the attractiveness of illiquid asset classes – I will leave others to debate the merits (and drawbacks) of private equity and its counterparts – rather I am interested in the behavioural implications of illiquidity. I was reminded of the idea about there being some form of behavioural premium for illiquid investments whilst listening to this discussion between Cliff Asness and Patrick O’Shaughnessy; I also briefly mentioned this notion in my post questioning whether volatility equated to risk.

What do I mean by a behavioural premium? Let’s assume there are two identical assets, but one offers daily liquidity and is market priced, and the other is appraisal priced / valued and provides liquidity on an annual basis. I would contend that, on average, investors are likely to be better off (from a return perspective) in the less liquid structure over the long-term because of the implications for our behaviour.

Most of the behavioural problems that plague investors stem from our reaction to the fluctuations in price of an asset allied to our ability to freely trade it. It is almost certain that many of the benefits investors have witnessed in recent years in terms of greater control and transparency have come with a behavioural cost[i].  Of course, these issues relate primarily to liquid, regularly traded, market priced assets; illiquid investments have different features – two of which are particularly important when considering the implications for our investment decision making.

– Price volatility is reduced: Illiquid assets are typically valued on some form of appraisal basis, rather through than market pricing. This does not remove price volatility entirely but should lead to a significantly smoother return profile. Although we can argue about whether volatility is an adequate measure of risk, it seems irrefutable that the variability in the price of an investment influences our behaviour.

Whilst the underlying risk of an asset is not altered by the manner or frequency with which it is valued, volatility does matter. Not only does it provoke our behavioural biases (such as myopic loss aversion[ii]); but volatility is the fuel that feeds the fire of narratives that dominate our investment decision making. If we observe or experience reduced volatility, we are less likely to act because of volatility.

– Ability to trade is removed or restricted:  It is simply more difficult (by definition) to trade illiquid assets. With a liquid, market priced asset there is the ability to react immediately – this can be costly, particularly if our decision making is emotion-laden[iii].

For most investors a few sensible decisions are all that is required to have solid long-term investment outcomes, however, daily liquidity and easy access to our investments means that we are forced to make investment decisions perpetually – is my asset allocation correct? What about the recent fall in value of my portfolio? Should I reduce my equity exposure as there might be a recession ahead? Market movements incite an often overwhelming temptation to act, which technology and liquidity facilitate, increasing the potential for behavioural mistakes. Illiquidity (indirectly) forces us to make fewer decisions, potentially reducing the behaviour gap.

Of course, the idea of a behavioural premium for illiquidity is something of an abstraction – liquid and illiquid assets are distinct and we cannot perfectly isolate the behavioural impact of investments with different liquidity profiles.  Furthermore, an investment should never be selected on the basis of its liquidity or pricing methodology.

Investors, however, don’t have to invest in illiquid assets to capture such a behavioural premium; rather we can create a similar benefit with liquid investments simply by taking steps to reduce evaluation and decision making frequency – through making it harder to trade (limiting investment decisions) and checking portfolios less regularly (to reduce our ‘experienced’ volatility).  In an era of improved technology and access such actions can feel at best simplistic and at worst retrograde, but are crucial in making and sticking with sensible long-term investment plans.

[i] Hardin, A. M., & Looney, C. A. (2012). Myopic loss aversion: Demystifying the key factors influencing decision problem framing. Organizational Behavior and Human Decision Processes117(2), 311-331.

[ii] Benartzi, S., & Thaler, R. H. (1995). Myopic loss aversion and the equity premium puzzle. The quarterly journal of Economics110(1), 73-92.

[iii] Loewenstein, G., & Lerner, J. S. (2003). The role of affect in decision making. Handbook of affective science619(642), 3.

What Can Investors Do About Overconfidence?

Overconfidence can have a profound impact on our decision making, but can be difficult to acknowledge and even harder to rectify.  It also seems likely that overconfidence is a particularly pernicious bias in the investment industry, for the following reasons:

– Selection bias: There is probably a selection bias into front office investment management roles – that is overconfident individuals are more likely to ‘ascend’ to such positions.

Overvaluing overconfidence: Related to the prior point – overconfidence tends to be an effective career strategy. Against an uncertain backdrop we seem to value those who take bold and singular views, whilst being scornful of pragmatism, nuance and probabilities.

Overconfidence is easy: When operating in an environment marked by randomness and uncertainty it doesn’t take a great deal to make an overconfident decision.

The potential implications of overconfidence are significant and include: overtrading, lack of diversification, attribution error and a tendency to take positions with unfavourable odds – to name but a few.  Although there is no perfect remedy for overconfident decision making, there are certainly simple steps we can take to mitigate it.  These are my preferred measures:

1) Take the outside view:  This concept has risen to prominence in recent years, mainly thanks to Michael Mauboussin and Daniel Kahneman.  Taking the inside view relates to being reliant on your own individual experience and specific circumstance, whilst the outside view is based on evidence from a relevant reference group – what is the general experience from similar situations?

For example, assume you were considering investing in an active manager.  The inside view would be the great meeting that you held with manager, their impressive track record and pedigree of the team. The outside view would be that only 10% of active managers in the asset class have outperformed over the past decade. Absent the outside view, you would be liable to neglect the unfavourable odds of investing in the active manager and the level of overconfidence you may be exhibiting by doing so.

2) Think in probabilities and bets[i]:  Although we seem to have an unescapable desire for spurious precision and aggressive singular forecasts, we should resist these and instead think in terms of probabilities. Ascribing probabilities to different potential outcomes reduces the chance that we become wedded to a particular view, prevents us ignoring low likelihood risks and, crucially, leaves us free to alter our perspective when new information arrives.  Changing your position when you have made a strident, binary forecast is fraught with difficulty; adjusting probabilities is far easier.

3) Assume you are average:  A good check on any investment decision is to ask – should this decision work on average? Or, in other words, are the odds in my favour?  Try to take decisions where there is evidence that it is a sensible long-term decision – for example, favouring cheaper assets versus more expensive assets over the long-term. Taking such an approach can give an insight into how much reliant you are on your own skill for an investment view to come to fruition.

4) Think about who is making the decision:  Whilst there is an assumption that group decisions should be less impacted by overconfidence than solo decisions, this is not necessarily the case – a group comprised of similar individuals may be emboldened by the consistency of their views and display even greater overconfidence. Group composition matters. A recent study[ii] showed that diverse groups (from a gender perspective) were better calibrated than individuals and all male groups.  Although research in this area is nascent – diversity is likely to be a crucial consideration when thinking about overconfidence.

5) Carry out a pre-mortem: Pre-mortems are a simple means of dampening overconfidence[iii].  Before making an important decision, ask a group of people to imagine that you have implemented the decision and it has proved disastrous, then to list the possible reasons for the failure. This is a great way to encourage devil’s advocacy and break down hierarchical structures that may inhibit individuals from questioning the decision of their ‘superiors’.

6) Record and review decisions:  It sounds simple, but is so rarely done – make sure that you appropriately record decisions when they are made (including why you are making them) in order that you are able to assess the quality of your judgements in the future.  Rather than doing this, our tendency is to not consider past decisions at all, or review them with the benefit of hindsight and retrofit our rationale based on information we didn’t have at the time. Looking at historic decisions is difficult and shines a light on just how tough it is to operate in financial markets; but the feedback is invaluable. Always remember to review decision quality not outcome quality as unfortunately the two are not synonymous.

References:

[i] Duke, A. (2018). Thinking in Bets: Making Smarter Decisions when You Don’t Have All the Facts. Penguin.

[ii] Keck, S., & Tang, W. (2017). Gender composition and group confidence judgment: The perils of all-male groups. Management Science.

[iii] Klein, G. (2007). Performing a project premortem. Harvard Business Review85(9), 18-19.

Twelve Investment Contradictions

The investment industry is a breeding ground for contradictions; our words, beliefs and behaviours are often in conflict with each other and sometimes themselves.   The causes of such discord are countless but include our unconscious biases, noise, insufficient knowledge and skewed incentives.  Below is a list of my current favourites, which will no doubt be different by tomorrow:

‘Data mining is a major problem for most quantitative investment strategies, machine learning is the future’

‘Volatility is a poor measure of risk for illiquid assets, but have you seen the Sharpe ratio impact of adding them to our portfolios?’

‘Diversity is at the heart of our culture, it just so happens that all our leadership positions are filled by white men’

‘We only want invest in high conviction, distinctive active managers…who consistently outperform’

‘We are acutely aware of the problem of return chasing in mutual fund selection …the first stage of investment process is a performance screen.’

‘We want to find investors who consistently apply their investment process and have the courage of their convictions, unless they perform poorly, and then we want them to do something about it’.

‘I expect to be making growing pension contributions over the very long-term, but want markets to increase in the short-term’

‘I am investing for the long-term, but like to check my portfolio valuation on a daily basis’

‘I want our non-equity positions to diversify our portfolio, unless equities are going up’

‘We are long-term investors but have 23 TVs showing financial news in our office’

‘I am happy to hold higher risk / higher return assets for the long-term, unless they go down in the short-term’

‘It is crucial to accept that randomness inherent in investment markets and take a probabilistic approach to any decision you make, but enough of that, let’s review three month performance’