The first MiFID (Market in Financial Instruments) directive, approved in 2004 and implemented in 2007, already made it possible to measure the profile of individual investors. This point is contained in the MIF 2 directive, implemented in France in January 2017. However, these two European directives, as well as the recommendations issued by the Financial Markets Authority (AMF) and the Authority for Prudential Control and Resolution (ACPR) in 2013, ultimately leave a lot of room for maneuver space in terms of putting it into practice.
Each financial intermediary therefore has its own questionnaire. If you’ve set up a securities account, you’ve already filled it out, probably without paying much attention.
But what can these questionnaires measure? Do they all give the same results? Is it really that easy to gauge an investor’s profile?
Objective points to consider…
When trying to establish an investor profile, we must take into account variables related to the socio-demographic profile (financial situation, family situation, age, etc.) that are easily measurable.
Investment horizons and return targets must also be established – for example income supplementation or retirement capital.
But above all subjective!
Until then, the task is “relatively” easy.
Things get much more complicated when it comes to measuring the financial skills and knowledge of individual clients. These are mostly questions based on experience with financial investments that are asked. But are experience and knowledge or skills really synonymous?
In 2012, at a joint academic conference between the Financial Markets Authority and the Prudential Scrutiny and Resolution Authority, André de Palma and Nathalie Picard emphasized that a more subjective approach to measuring knowledge in finance should also be considered. It is likely the work of these two researchers that led the AMF and ACPR to issue a recommendation along these lines in 2013.
But the root of the problem is the client’s individual tolerance for risk, which the financial intermediary must measure. We have to start by realizing that we don’t know exactly how to define what risk is. In general, we often talk about the “variability” of returns. However, there are potentially other indicators to consider, such as asymmetry of returns or so-called extreme risks.
In fact, measuring something that does not have a perfect definition is very difficult. Not surprisingly, different measurement methods will give different results. In questionnaires aimed at defining the investor profile, we see relatively low correlations between one questionnaire and another, less than 40% (De Palma and Picard, 2010).
Even worse, with the same method and a few weeks apart, we will not get exactly the same score when we try to measure the coefficient of risk aversion. The correlation is strong (around 70%), but still far from perfect. Why such differences? Simply because our mood can change and we sometimes feel more enterprising and able to take risks. Things as far removed from traditional finance as the level of certain hormones in our blood (such as testosterone or cortisol) can affect our tolerance for risk.
It is therefore not surprising that banks and other players in the financial sector find it difficult to agree when it comes to measuring risk tolerance.
Behavioral finance, for better measurement?
But how can we better measure individuals’ tolerance for risk?
In economics and behavioral finance, prospect theory continues to gain traction because it has demonstrated its superiority in the laboratory over classical theories for measuring risk aversion. This theory frees itself from the assumptions of classical rationality and tries to describe human behavior. It was formulated by two psychologists, Amos Tversky and Daniel Kahneman, the latter received the Nobel Prize in 2002 (Amos Tversky, already deceased, could not receive the prize posthumously). In particular, this theory assumes that individuals are loss averse (a loss of €100 is approximately twice as painful as a gain of €100 is pleasant) and that they outweigh the probability of rare events occurring.
This theory has proven to better describe the risk attitudes of students and farmers and has also been successfully tested on representative samples of the general population. He has proven his superiority to many, at least as far as individuals are concerned. This is also what De Palma and Picard recommend in their report.
Thus, it seems that financial intermediaries can draw inspiration from this theory to better understand the risk tolerance of individual clients. If they haven’t gotten to that point yet, it’s probably because this somewhat more complex theory doesn’t directly allow individuals to be classified by risk tolerance category. However, there is at least software on the market that enables the measurement of the risk profile using this approach.
So in the coming years, we could finally see the emergence of more behavioral finance to classify individual customers. This could appear either at the initiative of the financial intermediaries themselves or at the initiative of the regulator, be it the next version of MiFID or the AMF/ACPR recommendations.