The disposition effect – that is the propensity for investors to relinquish winning positions and maintain losing holdings – is one of the most prominent findings of behavioural finance, and has been widely studied and corroborated (for example – Frazzini 2006, Shefrin & Statman 1985, Weber & Camerer 1998).  However, this description of investor behaviour often seems in sharp contrast to the activity of mutual fund investors, where the leaning appears towards the opposite – abandoning underperforming holdings and persisting with those delivering excess returns. A study by Chang, Solomon and Westerfield (2014), confirms this view and contends that fund investors evidence a reverse disposition effect.  But why does fund investing provoke such a different behavioural response?

First, it is important to understand the existence of classic disposition theory.  Although there are a range of competing explanations, the most compelling is that of cognitive dissonance (Festinger, 1962), which relates to our desire to find uniformity in our beliefs and values; avoiding situations where there are conflicts or inconsistency.   If we make an investment that subsequently falls in value, or underperforms, we face the prospect of cognitive dissonance – we believe we are a skilful and diligent investor, yet the performance of the security jars with this view, creating a significant disconnect. Selling the position and crystallising a loss would only serve to confirm this contradiction, thus our tendency is to maintain the position and hold the opinion that we are right – just not quite yet.

Fund investors are not immune to cognitive dissonance, but they have an alternative means of relieving the stress caused by its occurrence – the ability to delegate accountability.  Faced with the same dichotomy of believing in your own investment abilities, whilst witnessing a poorly performing investment choice, a resolution can be found by placing blame with the underlying fund manager and selling the investment.

This type of delegated investment authority has been referred to as a psychological call option (or indeed a protective put), which is a reasonable analogy – with a fund investment one can claim credit for the upside, whilst capping the (psychological) cost of disappointment.  Outperformance is the result of superior fund selection, underperformance the consequence of problems with the fund manager.

Whilst this behaviour supports the desire for internal consistency, it also serves to protect our ego in the public domain. After diligently researching a fund and then stridently advocating it to your team / peers / clients; witnessing it struggle, even over brief and irrelevant time periods, can be emotionally taxing and perceived as damaging to your reputation.  A decision to sell the fund is therefore far more easily rationalised by believing that things (out of your control) have changed, rather than acknowledging a mistake.

The inclination to sell losing funds is compounded by our bias towards outcomes and desire to construct coherent narratives. A proclivity to judge the quality of a decision or an activity by its results alone, leads us to identify problems with underperforming funds and become complacent about outperformers (despite performance alone providing minimal insight into the quality of an investment approach).

When a fund is underperforming, the urge to develop a persuasive story accounting for the returns is often overwhelming.  Disappointing outcomes ‘must’ be related to some fragility in the investment approach, thus we seek to forge links between process issues (for example, capacity, team changes, style drift) and the performance delivered, even if the connections are erroneous.  These patterns are exacerbated by the preference to expend more time studying struggling funds in order to understand and explain performance.  Carrying out extensive research on a fund only to conclude that the underwhelming return is primarily due to random market noise, is unlikely to prove satisfying, even where accurate.

Confronted with an underperforming fund, an investor has three potential courses of action (this is a simplification):

i)                    Retain confidence in the holding as there has been no marked alteration to the philosophy and process, and the performance is consistent with expectations given the market backdrop. Maintain the fund.

ii)                  Acknowledge that although nothing material has changed, a mistake was made in the recommendation. Sell the fund.

iii)                Identify a problem with the fund stemming from some kind of change or unwanted / unexpected development, which can be linked to performance.  Sell the fund.

The first two options are by far the most behaviourally exacting.  Maintaining confidence in a fund holding despite underperformance falls foul of our strong desire to link outcomes directly to process, and does nothing to relieve the aforementioned cognitive dissonance.  Admitting an error serves only to crystallise the dissonance and tarnishes our ego.  Contrastingly, the third option is behaviourally compelling.  It enables us to relieve our dissonance by allocating responsibility elsewhere and sates our want to consistently align process and outcome. Given these features, the tendency of fund investors to sell losing positions is, perhaps, unsurprising.

This post is not designed to argue that we should blindly hold poorly performing funds, nor that there are never process problems or changes causing poor outcomes, rather it seeks to explain why the behaviour of fund investors appears to contradict the long established disposition effect.  The decision making dynamics of fund selection differ markedly from individual securities, and lead to an apparent reversal of the phenomenon. This should not be viewed as either a positive or negative, simply a distinct behavioural challenge for investors in active funds to address.

—

Key Reading:

Chang, T. Y., Solomon, D. H., & Westerfield, M. M. (2016). Looking for someone to blame: Delegation, cognitive dissonance, and the disposition effect. The Journal of Finance, 71(1), 267-302.

Festinger, L. (1962). A theory of cognitive dissonance (Vol. 2). Stanford University Press.

Frazzini, A. (2006). The disposition effect and underreaction to news. The Journal of Finance, 61(4), 2017-2046.

Shefrin, H., & Statman, M. (1985). The disposition to sell winners too early and ride losers too long: Theory and evidence. The Journal of finance, 40(3), 777-790.

Weber, M., & Camerer, C. F. (1998). The disposition effect in securities trading: An experimental analysis. Journal of Economic Behavior & Organization, 33(2), 167-184.

 

In the classical model of decision making we identify our preferences through systematically valuing each available alternative by multiplying its probability with its ‘utility’.  Such a hyper-rational approach is clearly unrealistic and fails to provide a descriptive account of how we actually behave.  Whilst most of our judgements must, either implicitly or explicitly, combine some assessment of potential outcomes and probabilities, our perception of these is dominated by our behavioural biases.

Of particular interest for this post is our handling of probability. This encompasses both how we ascertain a level of probability for a given occurrence and how we use that probability to inform our decision making.  In most scenarios the choices we make are in a state of uncertainty – meaning that we are never aware of the true probability properties of a given decision; thus our views are highly subjective and context dependent.

A number of anomalies have been identified in our treatment of probability; most prominent is Tverksy and Kahneman’s Cumulative Prospect Theory (1992), which posits that individuals tend to overweight low probability events with extreme outcomes.  This behaviour has been displayed in a number of fields such as lotteries (Clotfelter & Cook, 1990) and horse racing (Snowberg & Wolfers, 2010), where the favourite is ‘underbet’ and the longshot ‘overbet’.

Whilst there is evidence to support an inclination to overweight low probability, extreme events; research on insurance somewhat contradicts this notion.  Kunreuther & Pauly (2004) showed that individuals often failed to protect themselves from the consequences of catastrophic loss, even in situations where the cost is subsidised and the policy is undervalued (Camerer & Kunreuther, 1989).  Thus, in certain circumstances, rather than overstate the probability of an extreme event, there is a tendency to disregard it completely.

McClelland, Schulze and Coursey (1993) studied insurance behaviour in a laboratory setting and found that insurance against low probability risks possessed a bimodal distribution – that is participants were prone to either dismiss or exaggerate the risk presented.  Slovic, Fischoff, Lichtenstien, Corrigan & Combs (1977) reported that individuals were reticent to purchase insurance when the probability fell below some threshold – a threshold that was seemingly specific to each individual.

That there appears to be bimodal treatment of low probabilities, suggests that there is a probability threshold inherent in decision making, wherein the presumed probability of an occurrence must be above a particular level for it to be deemed worthy of consideration.  In the context of disaster insurance, Kunreuther & Pauly (2004) state that individuals need to be sure that the probability of an occurrence is above a threshold level before they even begin to search for detailed information on the value of protection.

The existence of a probability threshold might be considered an effective adaption allowing us to filter ‘noise’, limit worry and focus our attention on areas we deem pertinent. Furthermore, given that it is often difficult to evaluate the probability of an event, a simple ‘relevance heuristic’ that allows us to discard risks seems prudent and efficient.  However, this behaviour is highly problematic – not only is it injudicious to entirely reject certain high consequence risks, our ability to accurately gauge probabilities is severely limited and impacted by a swathe of behavioural biases including availability, recency and salience (we will cover these in more detail in later posts). Thus, we may be ignoring a particular risk that we subjectively perceive to carry a low probability, when in reality the likelihood is significantly greater.

The implications of this phenomenon are important for all investors – encompassing individual stock decisions to macroeconomic postulations – as our ability to understand probabilities and appropriately consider risks to paramount in the evaluations we make.  There is no simple solution to this issue, but there are a number of partial remedies:

–  Give specific probabilities to risks: We should be more willing to ascribe probabilities to risk factors.  This is not with any expectation of our estimation being right, we will almost certainly be wrong; but rather it allows us to be open and explicit about our thinking, and compare it to how our portfolios are positioned.  If we are running scenario analysis we should not simply look at the potential magnitude, but be explicit about the perceived likelihood of such an event. Formally assigning probabilities to risks also allows us to actively engage with our views, track how these evolve and react to new information.

–  Source opinions from across a team: Our perspectives on probabilities are highly subjective and will often vary significantly between individuals, comparing and combining probability expectations may serve to offset or counter some of our individual biases.

–  Take an external view: The caveat to the above is that the cognitive diversity within a team can often be limited.  Obtaining perspectives from people remote from your group, and with no vested interest in giving a particular view, should enhance the breadth of thought.

Such activities are, of course, no panacea; we are poor at forecasting and often risks will arise that were never previously considered, let alone discarded (black swans, unknown unknowns…).  Furthermore, our commitment to our own beliefs are often so resolute as to be unshakeable, thus the impact of the above approaches may be limited. These factors notwithstanding, the existence of a probability threshold and our propensity to ignore risks has profound ramifications for our investment decision making, and even small changes to our behaviour could garner material benefits.

Key reading:

Camerer, C. F., & Kunreuther, H. (1989). Decision processes for low probability events: Policy implications. Journal of Policy Analysis and Management, 8(4), 565-592.

Clotfelter, C. T., & Cook, P. J. (1990). On the economics of state lotteries. The Journal of Economic Perspectives, 4(4), 105-119.

Kunreuther, H., & Pauly, M. (2004). Neglecting disaster: Why don’t people insure against large losses?. Journal of Risk and Uncertainty, 28(1), 5-21.

McClelland, G. H., Schulze, W. D., & Coursey, D. L. (1993). Insurance for low-probability hazards: A bimodal response to unlikely events. In Making Decisions About Liability And Insurance (pp. 95-116). Springer Netherlands.

Slovic, P., Fischhoff, B., Lichtenstein, S., Corrigan, B., & Combs, B. (1977). Preference for insuring against probable small losses: Insurance implications. Journal of Risk and insurance, 237-258.

Snowberg, E., & Wolfers, J. (2010). Explaining the Favorite–Long Shot Bias: Is it Risk-Love or Misperceptions?. Journal of Political Economy, 118(4), 723-746.

Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and uncertainty, 5(4), 297-323.

 

 

 

A behaviour gap can be defined as a divergence between an individual’s actions and what may be considered a rational or optimal path.  In the field of investment, such a discrepancy is often highlighted by detailing the differential between time weighted and money weighted returns; with the latter being impacted by the timing and magnitude of investor cash flows.  Both Morningstar and DALBAR have produced research attempting to calculate the tangible investment cost of our behaviour.

Whilst it is impossible to precisely attribute disappointing investor results to a particular set of behaviours, there is certainly sufficient evidence to suggest that investment outcomes are persistently and materially impacted by our cognitive and emotional biases.  This post will focus specifically on the influence of myopic loss aversion and consider how this phenomenon may be exacerbated by developments in the investment industry.

The existence of myopic loss aversion was first posited by Benartzi and Thaler (1995) in their explanation of the equity risk premium.  The idea combines the concept of prospect theory with the propensity of individuals to make short-term / high frequency observations.  Kahneman and Tversky’s work on prospect theory has been heavily popularised, thus I will not cover this in detail, but rather reiterate the relevant aspect  – that individuals are loss averse (relative to a reference point) and a loss weighs more heavily than an equivalent gain. Thus, our behaviour will tend to direct us away from situations involving losses.

The short-termism of myopic loss aversion is a form of mental accounting wherein gains and losses are appraised over brief time horizons, even if the overarching investment objective is long-term.  The influence of observation frequency was further evidenced in a study by Thaler, Tversky, Kahneman and Schwartz (1997) where, in a hypothetical portfolio management task, participants in the group receiving monthly performance feedback (relative to yearly or five yearly) finished the five year period with the most risk averse portfolio allocations.

The study of myopic loss aversion was furthered by Hardin and Looney (2012), and their review of the relevant literature found three vital variables impacting myopia:

Information Horizons:  The timespan over which prospective returns and risk are presented is an important factor influencing behaviour.  There has been evidence from a number of studies that extending the information horizon leads to a greater appetite for risk taking due to the broader framing.   For example, the potential for recording an absolute loss in an equity fund is greater over a three-month horizon, than a five year horizon (other things being equal), thus our timeframe is central to how we perceive losses.

Evaluation Frequency: How often an investor reviews investment outcomes is also crucial to decision making.  The more readily we monitor performance, the more risk averse we are likely to be.  This is an intuitive concept – higher risk investments are more likely to generate negative returns over short time periods and the more frequently we interact with return information, the greater the opportunity for myopic loss aversion to exert an influence.

Decision Frequency:  The type of investment decisions we make can also be materially impacted by how often we make decisions.  Restricting investment decision making tends to reduce risk aversion, as investors are less likely to encounter, and therefore trade on, short-term losses.

The literature suggests that behaviour consistent with myopic loss aversion is stimulated by focusing on short-term performance information (historically and prospectively), regularly reviewing investment outcomes and making frequent investment decisions.  In isolation, or combination, these factors can promote risk aversion, lead to conservative investment choices and, potentially, substandard long-term returns.  This could be through either cautious initial portfolio allocations or the reduction of risk during periods of short-term stress (or loss).

The impact of myopic loss aversion may also be observable in the preponderance of low tracking error, ‘quasi active’ mutual funds available.  Whilst there are a range of factors that may discourage investors from owning distinctive, high active share funds (despite the evidence supporting such approaches), it is possible that myopic loss aversion is a central driver.   High conviction, differentiated strategies are likely to deliver greater short-term performance variability and periods of relative loss.  Indeed, such approaches are somewhat trapped in a vicious circle where higher levels of relative risk result in meticulous monitoring by investors, potentially promoting behaviour consistent with myopic loss aversion.

The challenge that all investors have to confront is that our vulnerability to myopic loss aversion has increased due to a number of industry developments (particularly technological), which mean that our ability to monitor and control investments has improved markedly.  This visibility and flexibility, coupled with incessant emotional and informational stimulus, makes it increasingly difficult to make, and persist with, prudent long-term investment decisions.

That is not to suggest that increased transparency and control for investors are negative developments – they are an undoubted positive.  It is, however, crucial that as the investment landscape evolves, we are cognisant of the behavioural implications. If not, then any benefits accrued may be offset by the behavioural costs.

—

Key Reading:

Benartzi, S., & Thaler, R. H. (1995). Myopic loss aversion and the equity premium puzzle. The quarterly journal of Economics, 110(1), 73-92.

Gneezy, U., & Potters, J. (1997). An experiment on risk taking and evaluation periods. The Quarterly Journal of Economics, 112(2), 631-645.

Hardin, A. M., & Looney, C. A. (2012). Myopic loss aversion: Demystifying the key factors influencing decision problem framing. Organizational Behavior and Human Decision Processes, 117(2), 311-331.

Thaler, R. H., Tversky, A., Kahneman, D., & Schwartz, A. (1997). The effect of myopia and loss aversion on risk taking: An experimental test. The Quarterly Journal of Economics, 112(2), 647-661.