Heuristics, or what we might call ‘rules of thumb’, have become somewhat maligned as a method of decision making in recent years. They are often erroneously conflated with cognitive biases and suffer their negative connotations.  Furthermore, the scepticism regarding the effectiveness of heuristics has been exacerbated by the ubiquitous system one (fast) / system two (slow) thinking construct (popularised by Daniel Kahneman), which can frame system one as the domain of rash, unthinking errors and system two the home of cool, rational and correct calculation.  System one and system two is frequently used as shorthand for ‘bad’ and ‘good’ thinking respectively, with the mental shortcuts that define heuristics firmly in the former grouping.

Even without exploring the limitations of the ‘two systems’ theory (see Osman, 2004); it is clear that heuristics do not fit within such a binary framework.  They can be either instinctive or deliberate, and often deliver results that are more robust than more complex methods of judgement.  For example, see Serwe and Frings (2006) on predicting the result of Wimbledon tennis matches, and McCammon and Hageli (2007) on avalanche risk.  Andrew Haldane’s speech around this topic is also excellent.

Unsurprisingly, the best definition of heuristics comes from Gerd Gigerenzer, who has been the pre-eminent voice on this subject, and the most vocal critic of the work of Kahneman.  He defines the heuristic approach as such:

“A strategy that ignores part of the information, with the goal of making decisions more quickly, frugally, and/or accurately than more complex methods” (Gigerenzer & Gaissmaier, 2011).

Although heuristics do feature in the world of investment there is an undoubted preference for complexity.  This is understandable – financial markets are intricate, unpredictable and often unfathomable; therefore we struggle to believe that simple solutions can be effective – a complex problem must be untangled by a complex process.  Furthermore, it is difficult to justify fees (and our own existence in the industry) by recommending quick and easy solutions.

This is not to suggest that everything in investment can be improved through simplification; rather we should not pour scorn on approaches that seek to streamline decision making in the midst of high uncertainty or difficulty. Sensible heuristics should be viewed as a valuable tool for investors, and below I have suggested five simple rules.

– Jam Yesterday Heuristic:  If an investment has produced strong returns in the recent past, reduce your expectations for future performance.

Whilst this is self-explanatory, it often seems to run contrary to the behaviour of most investors. The gains registered by an investment before you decided to purchase, are returns you will not be enjoying in the future!

– Upside Down Heuristic:  If an investment has outperformed its benchmark by a significant margin on the upside, it can also do so on the downside by a similar magnitude. If this is not acceptable, do not invest.

The lure of funds that have generated material excess returns can be irresistible, but if they have taken sufficient active risk for their performance to diverge markedly on the upside, they could generate similarly divergent returns in a less favourable fashion. Whilst index +20% is attractive over three years, only invest if you are willing to withstand the reverse 

– Keep it Simple Heuristic:  If presented with similar investment choices that differ in terms of complexity, select the simpler option.  

Simple investments are certainly no panacea, nor should they always be the preferred choice.  However, in situations where it is difficult to differentiate between alternatives in terms of quality, the preference should be towards that which is most easily understood.  Having clear and well-calibrated expectations is crucial for any investor.  If an investment strategy is straightforward, it is less likely to deliver negative surprises and you are more likely to stay invested for the long-term.

– Hedge Your Bets Heuristic: If you have any uncertainty over the timing of an investment, phase it into the market in equal tranches.

Phasing investment decisions is an effective behavioural trick, not only does it reduce the potential reference point impact of a single price on entry or exit; it also allows for the positive framing of your decision. If the price of your targeted asset rises as you stagger your investment you can feel content that you initiated the purchase when you did, whereas if it falls you can be glad that you decided not to invest in one hit.

– Double for Drawdown Heuristic:  Your absolute minimum expectation for drawdown in any diversified investment (outside of cash) should be double its expected long-term volatility.  If this is not palatable, do no further work.

This rule is not a comment on the appropriateness on volatility as a measure of risk, nor the expected distribution of asset class returns (which are often skewed); rather it seeks to translate the most commonly employed investment risk metric (volatility) into a simple yes / no decision based on a willingness to bear (temporary) losses.  Of course, volatility is a woefully inadequate measure of risk for illiquid investments with artificially low volatility, and both undiversified or ‘penny in front of steamroller’ strategies, which suffer from sharp tail risks.

None of these heuristics is likely to be revelatory, but amidst the myriad options that investors face as they seek to meet their financial objectives, it is easy to lose sight of crucial principles that can lead to improved investment behaviour and better long-term outcomes.  Although lacking the intellectual cachet of more sophisticated approaches; easy to remember, simple to apply rules of thumb can be remarkably effective way to navigate a complex investment landscape.

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Key Reading:

Gigerenzer, G., Todd, P. M., & ABC Research Group, T. (1999). Simple heuristics that make us smart. Oxford University Press.

Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual review of psychology, 62, 451-482.

McCammon, I., & Hägeli, P. (2007). An evaluation of rule-based decision tools for travel in avalanche terrain. Cold Regions Science and Technology, 47(1-2), 193-206.

Osman, M. (2004). An evaluation of dual-process theories of reasoning. Psychonomic bulletin & review, 11(6), 988-1010.

Serwe, S., & Frings, C. (2006). Who will win Wimbledon? The recognition heuristic in predicting sports events. Journal of Behavioral Decision Making, 19(4), 321-332.