The financial services industry is cluttered with quantitative jargon that looks to describe either how a fund has behaved or is expected to behave in the future. In the simplest form, this is achieved by comparing fund performance, either in absolute terms or relative to an appropriate benchmark –cash or to an equity index for example. However, whilst fund performance shows the returns achieved over a given time period, it does not necessarily explain the journey that was experienced on the way to delivering it, nor what journey was expected. This is where the concept of risk becomes important. However, there are many ways to describe it. 
Within the industry, the most frequently used term to describe risk is volatility which is typically quantified by using standard deviations – the larger the standard deviation, the larger the variability around the average return. However, standard deviations do not make any effort to describe the maximum fall or gain – which is often more of a concern to the end investor. Therefore, maximum drawdown or semi-deviation (deviation of the negative returns) are often adopted as a support statistic. Whilst these measures describe volatility in the absolute sense, they give no indication to proximity, or provide a sense of relativity. To overcome this, the industry has adopted beta and tracking error as its key measures to show how a fund has behaved relative to an appropriate benchmark.
To complicate things further, the statistics discussed can also be provided on an ex-post (after the event), or ex-ante (before the event) basis. Each approach has its flaws with ex-post detractors effectively saying that past performance is no guide to the future, whilst ex-ante detractors claiming witchcraft and crystal ball gazing. There’s an element of truth in both claims but when assessing the virtues of either a fund, and more specifically a portfolio, one ought to consider both.
When constructing a portfolio, the ex-ante approach usually dominates proceedings by creating a risk budget at the asset class level. Correlations of the asset classes, or how they move together, are also a consideration within this process but are notoriously difficult to forecast. Additionally, when looking to fill the asset allocations, it is important to still pay close attention to the underlying funds and to not assume that all funds will behave like their respective ex-ante assumptions. Style characteristics, liquidity profiles, interest rate sensitivities are just a few examples that can create divergences and collectively change the risk profile of the portfolio.
There are many further, and equally important qualitative risk elements that need to be considered when selecting a fund or building a portfolio. Below highlights some of these additional risks and whilst some of these can be measured quantitatively, others can only be assessed qualitatively by experienced individuals:
Compliance or regulatory risk – the risk of breaching a regulatory or client-specific guideline
Operational risk – the risk of human error through poor internal controls or governance procedures
Liquidity risk – the risk of losing the ability to trade or realise profits/prevent losses
Counterparty risk – the risk of a counterparty being unable to meet their obligations
Portfolio (investment) risk – which can be defined as the risk of not meeting a client’s expectations
There are of course further layers to the metaphoric onion that is risk, all of which ought to be considered. However, even when only considering the risks discussed here, it is vitally important to understand that no measure should be used in isolation but rather consider each as just one of the many pieces in a rather large and complicated jigsaw puzzle. Over-reliance on any one measure is likely to lead to poorer client outcomes.
Chris Fleming is investment services director at Square Mile Investment Consulting and Research. The views expressed above are his own and should not be taken as investment advice.