Five Simple Behavioural Tips for Better Long-Term Investment Decision Making

Although behavioural finance has become an in-vogue topic in recent years and provided many valuable insights into how investors make decisions; it is often fiendishly difficult to put these into practice.  Whilst there are some notable exceptions (such as Save More Tomorrow in the US), much of the work in this field describes what we do, not necessarily what we can do about it. The purpose of this short piece is to highlight five ideas, influenced by behavioural science, which could lead to better long-term investment decisions:

1) Check your portfolio less frequently:  Whilst the benefits of transparency and access are significant they create a range of behavioural problems for the long-term investor.  Quite simply – the more frequently we check our portfolios, the more myopic and risk averse we are likely to become in our decision making. Viewing our portfolios on a daily basis creates an often irresistible urge to react and trade, often at the worst possible times. Although difficult, once we have a sensible investment plan in place, we should try to restrict our observations to a meaningful and realistic level – once a month / once a quarter / once a year.  A gentle nudge for private investors is to set a password for your investment account that is difficult to remember and store that password somewhere it takes a modicum of effort to retrieve. Making something that little bit more difficult, can have a dramatic impact on our behaviour.

2) Don’t make emotional decisions:  How we ‘feel’ at any given point in time can have a material influence on the manner in which we perceive risks and assess opportunities. Making an investment decision in an emotional state – such as excitement or fear – is fraught with problems. If there is any chance that emotion is overwhelming your thinking – postpone the decision. If the idea was a good one, it is still likely to be tomorrow, or next week.

3) Make doing nothing the default:  I vividly recall sitting in an investment meeting at one point in my career and debating what our reaction should be to a particular period of market tumult. Certain participants advocated taking the opportunity to increase risk, others proposed becoming more cautious – both contrasting views were considered by the group to be credible. However, my suggestion of doing nothing was treated with incredulity – something is happening, we must react.   The more we are bombarded with news, information and opinion the greater the temptation to be busy fools and justify our existence as investment managers by taking action, any action.  For a variety of reasons doing nothing is the hardest decision to make for an investor, but it is often the correct one.

4) Choose sensible reference points: Loss aversion is a well-understood concept, but the important role of reference points is probably understated.  We experience losses relative to a particular level, value or benchmark, and what that reference point is can materially impact both how we think about investment performance and the decisions we make.  Unscrupulous investment managers can attempt to exploit this phenomenon by shifting the benchmark, or trying to create a new reference point when reporting to clients: “Whilst your balanced portfolio lost 7% during the period, the NASDAQ Biotechnology index fell by 23%…”  There is no perfect solution here and the decision will be specific to each individual, but choosing a prudent, consistent reference point (or selection of reference points) at the outset of an investment portfolio can mitigate future behavioural pitfalls. An example of a reference point problem would be comparing the performance of your cautious portfolio to a broad equity index in a bull market, experiencing this as a ‘loss’ and deciding to abandon your investment discipline to assume more risk.

5) Write a pre-mortem before making an investment: An idea developed by Gary Klein whereby, prior to embarking on a course of action, you imagine a future state where this action has ended in failure, and then list the reasons why it has gone wrong. This approach can be easily applied prior to making an investment, where you envisage the future failure of the decision and attempt to identify the causes.  It can be particularly useful in a group situation as it gives individuals the freedom to play devil’s advocate.  The technique is effective as it forces us to engage with the prospect of being wrong (which is often unpalatable) and can serve to puncture the overconfidence that can often plague investment decision making.  It is also a useful learning tool as we can retrospectively review what we considered to be the primary risks at the time of making an investment.

The Asset Management Industry Must Confront Biases to Address its Diversity Problem

A recent survey on UK asset managers carried out on behalf of the Diversity Project, highlighted a dispiriting, though not unsurprising, lack of diversity in the industry. Investment management roles are dominated by White men (often privately educated); with significant variation from the broader population composition across a number of categories, including: gender, education, disability and ethnicity.  Whilst these findings would not shock anyone with direct involvement in the field; it is beneficial to have sample data rather than rely on anecdotal evidence.

It would be unfair to claim that the problem is asset management specific, rather than a societal issue; however, this does not exonerate or excuse the industry, which at best reflects the phenomenon and at worst serves to exacerbate it.  The situation is an obvious problem for the groups that suffer from restricted opportunities, but also for the asset management firms that are starved of cognitive diversity.

Although the subject and its consequences are palpable, there is no simple solution.  Many of the behaviours that contribute to the lack of diversity are caused by entrenched biases that are often either unconscious or difficult to acknowledge; a fact that has been evidenced in a range of studies across many years, and a variety of domains.

Bertrand and Mullainathan (2004) carried out a field experiment seeking to analyse the treatment of race in the job hiring process. They sent fictional applications for jobs advertised in Chicago and Boston newspapers, the CVs created were randomly given “African-American or White-sounding names” and the responses monitored. The results of the study were stark:  White-sounding names received 50% more interview requests; furthermore, the difference in response between high and low quality CVs was significant for White-sounding names (close to 30%), but markedly lower for African-American sounding names.  Whether conscious or unconscious, the differential labour market treatment based solely on race evidenced in this study was pronounced.

The issue of gender discrimination was tackled by Goldin and Rouse (2000) through an analysis of the audition process for symphony orchestras. They observed the gender diversity of eight prominent orchestras between the 1950s and 1990s, and sought to isolate the impact of blinding or screening (obscuring the identity of the player), a policy that had been adopted at different junctures by the orchestras under analysis.  The authors found that the use of screening increased by 50% the probability of women progressing from certain preliminary rounds, and accounted for “possibly 25% of the increase in the percentage female in the orchestras from 1970 to 1996” (738, 2000).  These are significant impacts from a simple procedure that obviates the potential for sex-based discrimination.

In a study of racial bias and leadership, Rosette, Phillips and Leonardelli (2008) found that “being White” was considered a typical characteristic for a business leader. The authors suggest that consistent exposure to White individuals in leadership positions and the history of White leaders in business and politics served to perpetuate “being White” as a typical feature or attribute of a business leader.  This view was supported by Gündemir, Homan, de Dreu,, & van Vugt (2014), who displayed that “race neutral” classical leadership traits were more strongly associated with White-majority group members and that “a major cause of the underrepresentation of ethnic minorities in leadership positions in the Western world is that this group does not fit the predominant image or prototype of a leader.” (2014, 1)

Whilst these studies focused on the importance of race as a means of leadership categorisation, we can assume a host of other factors (such as gender, disability, sexuality, social class) are also erroneously (and often unconsciously) used to evaluate an individual’s suitability for a particular role.  It is simple to link this type of thinking to the lack of diversity within the investment management industry – the majority of fund managers share a range of traits (white, male, middle class), which come to be viewed as archetypal, and are interwoven with other features and skills that one might associate with the profession. Thus, a vicious circle is forged where the dominance of a particular group in a role, leads to their aforementioned factors being viewed as characteristic and favourable.

These studies represent only a fragment on the research undertaken on bias and discrimination in the workplace; but serve to provide an insight into ingrained prejudicial behaviour and its potential consequences.  Whilst there is a growing awareness of the issues, there remains a great deal of uncertainty about how to effectively tackle a problem that often seems intractable.

Although businesses are increasingly keen to place diversity at the forefront of their employment practices, such simple signalling is possibly problematic; not only because these declarations do little to address the unconscious nature of many of our biases but, more importantly, it raises the spectre of moral licensing.  First detailed by Monin & Miller in 2001, moral licensing is a situation where “past moral behaviour makes people more likely to do potentially immoral things without worrying about feeling or appearing immoral” (Merrit, Effron and Monin 2010, 344).  As an example, in a study by Effron, Cameron and Monin (2009) participants that expressed support for Barack Obama (shortly prior to the 2008 US election), were more likely to make ‘pro-White’ decisions in an ensuing scenario.  The subjects’ view on Obama provided them with ‘moral credentials’, absolving them of the need to appear non-prejudicial subsequently. Although research on moral licensing is nascent and the subject complex, it is possible that proclamations of diversity are not simply insufficient, but counter-productive.

Given the behavioural hurdles of improving the level of diversity within senior roles in the asset management industry, it is apparent that bold steps need to be taken.  One example, in a different field, is The Rooney Rule in professional American Football (NFL), which requires that one minority candidate is interviewed for all head coaching positions and senior operations jobs.  The rule was designed to address the lack of opportunity for minority coaches in the NFL.  Although there remains much debate about the efficacy and desirability of such an approach, DuBois (2015) estimated that a minority head coach candidate was 19-21% more likely to acquire the role following the imposition of the Rooney Rule.  Furthermore, it has been contended that the Rooney Rule decreased discrimination by reducing “the archaic biases regarding the intellectual ability of minority candidates” (Collins 2007, 870).

In the absence of a counterfactual, it is difficult to precisely assess the impact of the Rooney Rule; however, given the potential strength of our biases it is easy to see how a policy that compels behaviour change from employers and alters the typical candidate pool could serve to both improve short-term opportunities for under-represented groups, whilst eroding harmful stereotypes and biases over the long-term.  For asset managers, an adapted version of this approach could be utilised when hiring for both senior positions and also more junior levels, such as graduate programs.

For each possible ameliorative strategy there will be imperfections and the potential for negative behavioural spillovers (where an intervention backfires and produces the opposite effect of that intended).  However, there is little doubt that the biases that impact recruitment in the asset management industry are deep-rooted and material; for meaningful change, bold thinking and actions are required.

Key Reading:

Blanken, I., van de Ven, N., & Zeelenberg, M. (2015). A meta-analytic review of moral licensing. Personality and Social Psychology Bulletin41(4), 540-558.

DuBois, C. (2015). The Impact of “Soft” Affirmative Action Policies on Minority Hiring in Executive Leadership: The Case of the NFL’s Rooney Rule. American Law and Economics Review18(1), 208-233.

Collins, B. W. (2007). Tackling unconscious bias in hiring practices: The plight of the Rooney rule. NYUL Rev.82, 870.

Claudia, and Cecilia Rouse. (2000). Orchestrating Impartiality: The Impact of “Blind” Auditions on Female Musicians. American Economic Review, 90(4): 715-741.

Effron, D. A., Cameron, J. S., & Monin, B. (2009). Endorsing Obama licenses favoring whites. Journal of experimental social psychology45(3), 590-593.

Gündemir, S., Homan, A. C., de Dreu, C. K., & van Vugt, M. (2014). Think leader, think white? Capturing and weakening an implicit pro-white leadership bias. PloS one9(1), e83915.

Lavergne, M., & Mullainathan, S. (2004). Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination. The American Economic Review94(4), 991-1013.

Merritt, A. C., Effron, D. A., & Monin, B. (2010). Moral self‐licensing: When being good frees us to be bad. Social and personality psychology compass4(5), 344-357.

Monin, B., & Miller, D. T. (2001). Moral credentials and the expression of prejudice. Journal of personality and social psychology81(1), 33.

Rosette, A. S., Leonardelli, G. J., & Phillips, K. W. (2008). The White standard: racial bias in leader categorization. Journal of Applied Psychology93(4), 758.