Targeted Return  

Are advisers measuring investment risk accurately?

  • Understand what is meant by risk and the difference between risk and volatility.
  • Learn about the different types of investment risk models and how they are applied.
  • Consider the impact on clients and whether absolute return risk can be measured by advisers.
CPD
Approx.30min
Are advisers measuring investment risk accurately?

What is risk? In simple terms, risk is the chance that your investment didn’t do what you had hoped. 

However, understanding risk and presenting its impact to clients can become very nuanced, very quickly.

Like most people, advisers and clients alike are susceptible to behavioural biases that can cloud judgement.

Studies have shown that most individuals are susceptible to loss aversion and have a poor understanding of probability – for example, consider the average person who is under-prepared for retirement but also a frequent player in the national lottery.

Clients need guidance so they can understand their biases and plan for the future.

Understanding and accepting risk is a key part of this.

Some questions that a client might raise are whether there are different types of investment risk. How can we measure this risk? What can we use to control risk? What time horizon are we looking at?

Despite risk being a difficult concept to understand, risk control and financial theory have advanced over the past half century or so.

Some of this theory is now commonplace enough that advisers can access sophisticated models as part of their planning process.

Does volatility = risk?

The most common measure of risk used today by advisers is volatility. Volatility is calculated using investment returns, their standard deviation, which is then annualised so the annual volatility is comparable between investments.

Volatility does have some criticisms, namely that investors should really only be concerned with volatility that stems from losses (downside deviation), rather than volatility from positive returns.

Volatility assumes a symmetric, normal return distribution, whereas in reality there are fat tails and extreme market events that occur more often than the normal distribution predicts.

However, volatility is still a useful tool. The main reason for this is that volatility works well in mathematics for portfolio construction. 

By breaking down an investment into underlying asset class exposures, and using estimates of correlations, returns and volatilities of these asset classes, it is possible to calculate the future volatility for the entire investment.

Using volatility, the maths is relatively simple and tidy – at least as simple as undergraduate Maths degree level. 

This may sound beyond the level of non-mathematicians, however, advisers use these concepts on an almost daily basis when they assess the risk suitability of a multi-asset fund for a client.

Most likely an adviser will use an online tool and all of the maths is hidden under the bonnet. These tools use a volatility forecast to show a range of potential outcomes to the client.

The client can then grasp an idea of best and worst case scenarios, and can plan accordingly.

Advisers will likely have heard of these as ‘stochastic volatility projections,’ or ‘monte carlo simulations’.