Is There a Behavioural Explanation for the Quality Factor in Equities?

From a behavioural perspective the notion that there is some form of premium attached to investing in higher quality companies is something of a puzzle.  If anything, one would expect loss-averse investors to overpay for securities with perceived stability and downside protection, and bear a cost in terms of lower risk-adjusted returns.  Research, however, suggests that the reverse is true[i].  I have written previously about the potential behavioural explanations for value and momentum factors, but for the quality factor developing such an account is more challenging.

Compared to value and momentum, quality suffers from a somewhat amorphous definition, with a vast range of often distinct metrics employed to describe it.  Some combination of earnings stability, low financial leverage and high profitability appear to be the most consistently applied characteristics.  There is also debate around under what conditions the quality factor becomes apparent (delivers superior risk adjusted returns); often this is when applied in a long-short structure (long high quality / short low quality).  It is also often effective when held as a complement to another factor (such as value or size), rather than on a standalone basis.

It is certainly possible that quality might not be a genuine factor.  There are many who argue that excess returns to quality are a consequence of a market regime defined by a prolonged decline in interest rates – leading to a sustained re-rating for stocks with ‘bond-like’ qualities*.  Furthermore, the aforementioned definitional uncertainty also leads to a potential data mining problem – if you test enough ‘quality’ metrics, some are likely to prove significant.  The purpose of this post, however, is not to debate whether the quality factor is robust, but rather if it is – can there be a behavioural explanation?

It is important to make a distinction between the legitimacy of a quality equity factor and whether investing in quality companies can be an effective investment strategy.  If you can select companies with quality characteristics that are able to ‘beat the fade’ embedded in their valuation you are likely to be successful.  This, however, is reliant on having the skill to selectively identify these names in advance.  By contrast, the existence of a quality factor suggests that there is a return advantage to systematically filtering companies by a certain set of defined criteria.

Of course, the quality factor does not require a behavioural explanation to exist. One of the main problems with factor premiums is that there is no certainty about what causes an anomaly and we are forced instead to speculate.  This inability to truly understand the drivers of a factor means that we can never observe when something changes and the premium expected from a previously robust factor is extinguished.

In the case of the quality factor, a premium might be caused by a structural issue such as that highlighted by Frazzini and Pedersen[ii], who argue that constrained investors (who cannot utilise leverage) instead allocate to higher beta assets to boost a portfolio’s overall market sensitivity, leading to lower risk adjusted returns from higher beta assets.  This argument can also be extended to tracking error and beta restricted active equity strategies that have limitations on holding significant amounts of higher quality stocks.   Whilst there are behavioural elements embedded in this argument, these are more structural explanations**.

However, let’s assume that some form of quality premium exists in equity markets because of behavioural issues.  What could they be?

Incentives: As always, incentives matter.  If we assume that the richest rewards come to professional investors who either: a) Generate abnormally strong performance and raise a large amount of assets, or b) Generate strong returns by levying performance fees, then they may be inclined to embrace / overpay for volatile stocks with the potential for the highest payoffs[iii].

Present bias: We have a tendency to overweight near-term rewards.  Quality stocks deliver a long-term payoff (through the compounding of high returns on capital), whereas lower quality stocks provide the possibility of a high near term payoff.  If this is the case, we are likely to overvalue the potential short-term benefits of low quality companies (with an option like payoff), and undervalue the long-term benefits of quality companies.

Overconfidence: As investors we have an exaggerated belief in our own abilities and therefore may be reticent to invest in higher quality, stable companies and instead feel that our expertise is best rewarded by selecting companies with higher leverage, more variable earnings and greater earnings upside potential.

Focus:  The myopic nature of financial markets may simply mean that investors focus on the wrong things – obsessing over short-term earnings announcements, corporate news flow and macro-economic issues – rather than long-term profitability.

As with all equity factors, attempts at identifying behavioural explanations for the existence of a premium for high quality stocks is a somewhat futile exercise – we will never know the answer.  There is, however, some credibility to the notion that incentive structures, perceived pay-off profiles and temporal valuation issues could lead to a sustained mispricing in this area***, which could be systematically exploited.  Yet given the oceans of behavioural research conducted in recent years, it is possible to create mildly plausible explanations to justify virtually any equity risk factor.

* Valuation matters. Even if there is a structural premium for a certain equity factor, if it performs very well and becomes expensive, then you are unlikely to be enjoying that premium in the future (momentum will be an exception to this given the fluctuating composition).

** I acknowledge that a high quality equity strategy is not analogous to a low volatility or low beta equity approach; however, I would expect in most scenarios higher quality stocks to exhibit a lower beta and lower volatility than lower quality stocks.

*** It is certainly possible to argue that some of the behavioural explanations I give for the existence of the quality factor would seem to contradict the value factor (which is, I think, more robust than quality).

[i] https://www.nbim.no/contentassets/0660d8c611f94980ab0d33930cb2534e/nbim_discussionnotes_3-15.pdf

 

[ii] Frazzini, A., & Pedersen, L. H. (2014). Betting against beta. Journal of Financial Economics111(1), 1-25.

 

[iii] Bali, T. G., Cakici, N., & Whitelaw, R. F. (2011). Maxing out: Stocks as lotteries and the cross-section of expected returns. Journal of Financial Economics99(2), 427-446.

Most Investors Should Be Satisficers not Maximisers

Rational choice theory dictates that our decision making process should involve assessing all available options and then selecting the best possible one, or ‘maximising utility’.  This model is an example of a sound concept that fails when it encounters the real world.  A major critique of this approach came in the 1950’s when Herbert Simon suggested that rather than attempt to make the optimal choice, cognitive and environmental limitations mean that we often ‘satisfice’ – that is  make a decision when we find an option that is ‘good enough’ and meets some minimum threshold criteria.

The friction between satisficing and maximising behaviour is interesting when we consider investment decision making.  Our natural reaction is perhaps to assume that we should be maximisers and exhaustively seek the best possible outcomes, and there is perhaps a stigma attached to selecting something that is simply ‘good enough’. But should this really the case? I would contend that for many investors attempts to maximise are not only close to impossible, but the constant search for the best option can actually lead to very poor outcomes. There are a number of features about investment choices that make maximising behaviour particularly problematic.

Too Many Options: Maximisation may prove effective if there is a narrow and well-defined set of options, but in investment it is impossible to perform an exhaustive search across all available choices.  The opportunity set is enormous and fluid, and any attempt to ensure that we have selected the best possible option will be ongoing and fruitless.

– Vague Criteria:  Successful maximisation is also reliant on their being known and objective quality criteria – is it possible to easily differentiate between different options based on the most important factors?  In investment it is incredibly difficult to confidently isolate these criteria and distinguish between distinct choices.

– Wrong Criteria:  In the absence of a certain set of meaningful criteria through which we can judge quality, we tend to focus on one woefully inadequate comparative measure – historic performance.  We rely on past returns from an asset or investment fund to gauge its quality. This approach is worse than simply ineffective; attempting to select the very best option based on what has been the strongest performer in the past can lead to deeply sub-optimal selections.

– Shifting Criteria:  In addition to past performance being the most frequently used but damaging criteria for investment / asset selection, it also suffers from a lack of stability. Not only is it a weak metric for maximisation at any single point in time, but it is also changeable.  The random and uncertain movement of markets mean that if we rely on past performance to compare options, our view on what is the best possible choice will be highly variable.

– Switching is Easy: One of the most problematic features of attempting to maximise in an investment context is the ability to switch between options in a relatively ‘frictionless’ and simple fashion.  If we allow past performance to dictate our view on what is the ‘best possible option’ we are likely change our mind frequently and act on this by regularly shifting between investments*.  Whilst the optical switching costs may be reasonably low, the total cost of lurching between different investments is exorbitant.

For these reasons, the attempt to maximise in investment decision making is highly problematic yet unfortunately common. Performance chasing in asset classes, stocks and mutual funds, alongside egregious overtrading and short termism are symptomatic of investors consistently and unproductively seeking to ‘maximise’ their choices. Maximisation is another of the many investment behaviours that ‘feels’ conceptually right – of course we should be seeking the best possible option – but has severely deleterious consequences.

In addition to the problems of maximisation specific to investment decision making, it has been argued that there are other negative ramifications. Research has suggested that individuals who maximise are likely to suffer lower optimism, life satisfaction and self-esteem[i].   Barry Schwartz also notes that as the range of options expands people’s threshold for an acceptable outcome becomes too high and they are more likely to blame themselves for disappointing results rather than circumstance or environment[ii]  – there are so many options available why couldn’t you pick a good one?

If we are always seeking the very best outcome among a multitude of choices, discontent will follow as there is likely to be consistent regret from failing to select the best option[iii].  The randomness of outcomes allied to the sheer range of options in investment means that there will always be new shiny objects to attract us.

For certain types of investor some form of maximisation is inherent in what they do and the service they offer, but these are the exceptions. For most of us attempting to maximise our investment decision making simply leads to value destruction as we chase yesterday’s winners, trade too frequently and live in constant regret that the investments we don’t own are performing better than those we do .  Instead of this, we should be content to satisfice.  Find an investment plan that is good enough – based on sound principles (around issues like fees, rebalancing, diversification and compounding) and suited to our objectives.  Then stick with it.

[i] Peng, S. (2013). Maximizing and satisficing in decision-making dyads.

[ii] Schwartz, B. (2000). Self-determination: The tyranny of freedom. American psychologist55(1), 79.

[iii] Roets, A., Schwartz, B., & Guan, Y. (2012). The tyranny of choice: A cross-cultural investigation of maximizing-satisficing effects on well-being. Judgment and Decision Making7(6), 689.

* There is also evidence of maximising behaviour leading to choice paralysis.  For example, in the famous jam example where more choice led to less purchase decisions, or in pension plans where so many options are offered individuals are reluctant to participate at all because they are unsure of the best choice.