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You have an aversion to what? Is it risk or ambiguity?

‘Risk aversion’ and ‘ambiguity aversion’ sound like similar, albeit complex, terms. But they are distinctly different and can potentially, in combination, explain lots of the investment behaviours we observe in practice. They are also useful concepts for industry to become more engaged with.

By defining the two terms it becomes easy to understand the difference. Both forms of aversion exist in everyday life decisions but in this article we focus more on aversion associated with financial decisions.

Risk aversion is a measure of a person’s reluctance to take a financial risk when the characteristics of the payoff profile are known exactly. A common way to estimate a person’s risk aversion is to offer them a scenario when the odds are known. For instance: you are offered the opportunity to randomly pick out a ball from an urn which you know contains 50 red balls and 50 blue balls. If you select a red ball you get paid $2 and you lose whatever you paid to play if you select a blue ball. How much would you pay to play? Most people would say some amount less than $1 (the rate at which one would expect to break even) because they express some degree of risk aversion. The lower the amount they would pay to play the higher their level of risk aversion. If they offered to pay more than $1 they would be risk seekers. It is a regulatory requirement that financial planners assess the risk tolerance of their clients. Here ‘risk tolerance’ has a similar meaning to the level of ‘risk aversion’ but also takes into account the client’s financial capacity to take risk. In practice financial planners typically estimate risk tolerance through questionnaires rather than measure it through pay-off type experiments.

Ambiguity aversion is less known and not well understood. It refers to the preparedness to take a risk where the characteristics of the scenario are unknown. To illustrate we once again take our urn which contains 100 balls. The payoff amounts remain the same ($2 if a red ball is drawn and the loss of whatever you paid to play if a blue ball is drawn). The difference is that we do not know how many red balls and how many blue balls are in the urn. For me this sounds a strange risk to take but each of us would have a price at which we would be prepared to take a draw. For anyone interested in exploring further this is known as Knightian Uncertainty and is based on what is known as the Ellsberg Paradox.

Risk and ambiguity aversion have a degree of similarity (indeed the research has shown that the two measures have a moderate positive correlation) but it is important to understand the difference. Most of us are risk averse. The alternative is risk seekers who place more value on a positive payoff than they do on the risk of loss. From here we can all be further distinguished by our degree of ambiguity aversion. Some of us will be more prepared than others to take a risk that we don’t fully understand, but I expect that for most of us our ambiguity aversion would be higher than our risk aversion. If I self-assess my own position I would expect that I have moderate risk aversion but high ambiguity aversion: I’m quite prepared to take risk provided I understand the characteristics of the risk I am taking.

It needs to be noted that the concept of ambiguity aversion is currently assessed via simple odds-based experiments like the one outlined above. However this may unfairly generalise the concept of ambiguity itself: people may have different personal benchmarks for what represents an understanding of risk. Some may want to know all the details of an investment while others may feel knowledgeable once they have attained a broad understanding.

There are interesting ramifications for portfolio preferences when we characterise individuals as having unique characteristics regarding risk aversion and ambiguity aversion. For instance:

  • A more risk averse individual may select a lower risk portfolio than a less risk averse individual because they have a greater degree of ambiguity aversion and are unfamiliar with the characteristics of the underlying investments
  • Two individuals with the same levels of risk aversion and ambiguity aversion may prefer different portfolios because they have different levels of knowledge about the characteristics of the underlying investments (asset classes and investment strategies).

The relevance of these points is higher when we account for the poor levels of basic financial literacy in Australia (see Cuffelinks article November 29, 2013).

For industry practitioners, ambiguity aversion may explain why some new investment products take a while to gain acceptance even though they are a low risk product.

For an outsider the world of finance must appear very complex, making them ambivalent towards the many investment options available to them. And if anything complexity is on the rise. For instance, MySuper has created a broader range of default funds (balanced and lifecycle funds) which are difficult to compare, whilst the post-retirement space into which many are entering is arguably more complex than the accumulation environment.

And with this the responsibilities of super funds and financial planners to educate their members and clients can actually contribute to better retirement outcomes. Improved education, or even increased confidence in those managing their money and making investment recommendations, decreases ambiguity and gets investors taking a level of risk more in line with their risk aversion. Over time we expect this risk to be rewarded and so members and clients would be expected to experience better retirement outcomes.

I find this a fascinating topic. Even without knowledge of the ambiguity aversion of financial advice clients and super fund members it is easy to identify that improved education will make a client or fund member more comfortable to adopt a level of investment risk which is consistent with their level of risk aversion.

 

David Bell’s independent advisory business is St Davids Rd Advisory. In July 2014, David will cease consulting and become the Chief Investment Officer at AUSCOAL Super. He is also working towards a PhD at University of NSW.

 

2 Comments
David Bell
May 20, 2014

Hi Peter,

I always enjoy your contributions to Cuffelinks' discussion forums and this comment is well taken.

Ultimately risk and ambiguity aversion are concepts and my primary purpose for discussing them is to prompt some thought and reflection.

I agree that what I call an “outcomes engine” (a tool for projecting the likelihood of a range of outcomes) is an essential for educating a member about what is most important (their retirement outcome). However I am more cautious about saying that it is the only piece of knowledge required.

Part of the issue comes back to engagement. For a disengaged financially uneducated member then if their first educational port of call is to be provided with information that their retirement plan may or may not be on track (and the certainty of the projected outcome) then that may take care of their education requirements – which I think is what you are suggesting. However if a member is highly engaged and looking to be an active member then the education requirement would likely go beyond what a projection model may tell them. They want to understand the how and why. How hard we should push the disengaged to become engaged is a tricky issue - I explore this somewhat in Cuffelinks – “Paternalism is not a dirty word” – July, 25, 2013.

I should also add that, in my experience, no model is perfect. How many models actually accounted for the recent changes in the age pension prior to them being announced – yet they were an important risk factor to retirement outcomes? There are so many complexities – eg not all models account for uncertain lifetimes (because a fixed age of death is much easier to model)? Etc etc. We have even seen a recent example where a major financial services firm provided incorrect projections.

Finally any attempts to improve financial knowledge have much broader benefits than just super. There are many important decisions made throughout life in which a greater financial knowledge may assist. So overall I agree that an outcomes engine which produces projections and is interactive would be beneficial to super fund members. However I also believe that education, for those who desire it, should be available.

Cheers, David

Peter Vann
May 18, 2014

David

A great read, thanks. I note the line “educate … can actually contribute to better retirement outcomes”.

IMHO, the industry has been grappling with education of something that is not really necessary for most fund members. It needs to focus on the outcome; I think that most members can relate to “you are on track for a retirement income of $1,000 per week from your super” without any further education. In the defined benefit days, education was simple; the defined contribution world has yet to catch up.
Correctly translating a member’s financials to a retirement income statement is quite complex, but it has been solved (see Andrew Gale’s Cuffelinks article “A better approach to post-retirement planning “, 12 Nov 2013) and the results easily understood by members**. Only when one has a well-structured stochastic analysis of the likely range of retirement income can one successfully understand the impact of different investments, contributions, retirement age, retirement spending patterns etc, on one’s retirement outcomes. Put in this context, education is simplified and the “risk tolerance” discussion can be correctly framed. I severely doubt if many, or any, financial planners can meet the regulatory requirement of assessing a client’s risk tolerance since they are not focusing on risk associated with meeting the end goal.

When the discussion moves from account balance to the retirement outcomes, risk aversion and ambiguity aversion can be placed in the right context.

Cheers
Peter

** A member doesn't need to understand how retirement forecasts are produced just what they mean. This is like driving a car; we don’t need to understand how the car’s computers monitor driving conditions etc to manage, inter alia, fuel and air mixtures, ignition and valve timing. We simply need to know what the accelerator and brake do for us.

 

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