Measuring and managing investment risk: Part 1

By Kaavya Dijendranath

Updated on Tuesday, 28 February, 2017

Assessing the level of risk in a particular instrument and understanding its role within a client’s portfolio is key to ensuring the suitability of your investment advice. This relationship between investment risk and suitability is currently under increased focus from the FCA, as it analyses reports from over 700 firms ahead of its suitability review that is due to be published this year.  In keeping with the theme, FE conducted a survey over the Christmas period to assess Advisers’ attitude to risk with a view to better understanding how our clients identify, measure and manage investment risk.

The survey found that nearly 63% of respondents regularly relied on volatility as a measure of risk and whilst some Advisers acknowledged they use external third party models to manage volatility (find out about the FE Invest Model Portfolios’ risk management process), many rely on their own due diligence during fund selection and portfolio composition to consistently manage risk for reward.

Volatility as a measure of risk

Volatility is used as a measure of risk as it shows how widely a fund’s returns deviate from the average over a particular period. For example, if a fund had an average return of 5%, and its volatility was 15, this would mean that the range of its returns over the period had swung between +20% and -10%. Another fund with the same average return and 5% volatility would return between 10% and nothing, but there would at least be no loss. While volatility is specific to a fund’s particular mix of investments, where returns offered are similar, selecting funds with higher volatility can prove to be unnecessary.  Hence careful consideration of a variety in funds and their specific role within the portfolio becomes critical.

Below we use an interactive scatter chart to display the annualised volatility of a group of instruments. With the performance on the X axis and volatility on the Y axis it shows which funds provided the most returns with the least risk. The example below plots the Investment Association’s Japanese sector over the last year (the chart allows you to analyse up to 20 years’ worth of data).
















Particularly useful when you are trying to make a fund shortlist, you can further drill into the top left area to see the most attractive Japanese funds within the sector.












The chart shows that instrument C, has less than average volatility but has returned more than the average performance of the group of funds analysed.

FE Risk Scores

For further analysis on instrument C – the FE Risk Scores offer an intuitive measure of volatility relative to the FTSE 100. Assigning the index, a score of 100 and cash at 0, the FE Risk Scores are sensitive to market conditions, offering a robust barometer that measures relative rather than absolute risk. 









The scores can also be charted to track the pattern in an instrument’s volatility over time. The chart below plots the scores of instrument C for a period of three years and can be used for easy comparisons to other funds.










Measuring portfolio risk

The FE Risk Scores also extend to portfolios - once you have created a model or portfolio on FE Analytics, you can assess its overall risk level. Thanks to the benefits of diversification, the portfolio Risk Score is often much lower than the individual scores of its component funds.

The correlation table on FE Analytics, can help you consistently manage this diversification to ensure that funds within the portfolio are behaving as required. The green and purple slabs represent a low or positive correlation between the funds within the example portfolios.












Over reliance on volatility?

Although volatility is a common measure of risk, it comes with certain limitations when forecasting future performance or planning for worst case scenarios. To understand the true risk/return potential of an investment solution, it can be beneficial to adopt a more holistic approach to evaluating risk. In part 2 of this series we will explore how FE Analytics can help evaluate other risks including drawdown, shortfall and sequential risk and more.