In portfolio construction, the two most important elements are the expected return of an investment and the risk taken to achieve it. While expected return tells us what we may hope to earn, risk indicates how much the actual outcome may deviate from that expectation. This distinction is crucial in equity selection: a stock with a high expected return but very volatile outcomes may ultimately perform worse than a stock offering lower expected returns with more stable results. Hence, understanding risk in equity selection is at least as important as understanding expected return, if not more so.
In its broadest sense, when investing in equities, volatility is commonly used as a proxy for total risk. However, total risk can be decomposed into different components, each operating at a different level and requiring a different analytical approach.
Risk at Different Levels
Using a top-down perspective, the first type of risk an equity investor is exposed to is systemic risk, often associated with extreme “black swan” events. This refers to the risk of a collapse of the financial system itself. Such events are typically classified as Low Probability, High Impact (LPHI) risks: they occur infrequently, but when they do, they can generate severe losses across markets. Because of their nature, systemic risks are largely unpredictable and difficult to model using traditional financial metrics.
Moving one level down, investors are exposed to systematic risk, which represents the risk inherent in being exposed to a specific market. For example, a portfolio invested in UK equities is exposed to the risk of movements in the FTSE 100. This form of risk is measurable and can be evaluated with considerable precision using its standard proxy: beta. By its very nature, systematic risk cannot be diversified away, as it affects all securities within the same market.
Finally, narrowing the focus further, we encounter unsystematic risk, which is the risk associated with individual securities. This includes company-specific events such as management decisions, earnings surprises, or sector-specific shocks. The key characteristic of unsystematic risk is that it can be mitigated through diversification. Setting up a broadly diversified portfolio of stocks with a low level of correlation can consistently reduce unsystematic risk, making it increasingly negligible as the number of holdings grows.
Risk in Practice
Both systematic and unsystematic risk are captured within the Value at Risk (VaR) framework. VaR is a statistical measure of total portfolio risk that answers a simple but powerful question: how much can an investor reasonably be prepared to lose over a given time horizon, at a given confidence level? The answer is expressed as a percentage or monetary value and reflects the combined effect of all underlying risk sources. However, while VaR captures total risk, it does not distinguish between its systematic and unsystematic components.
Using Risk Measures to Evaluate Equities
Risk measures are also used directly in equity selection. One commonly applied metric is the Coefficient of Variation, which expresses risk per unit of expected return. It answers a practical question: how much risk am I taking for each 1% of expected return? When comparing securities, a lower coefficient of variation indicates a more attractive risk–return trade-off.
A related concept is the principle of dominance, according to which one investment dominates another if it offers a higher expected return for the same level of risk, or the same expected return with lower risk. These tools allow investors to move beyond headline returns and make more informed, risk-aware equity selection decisions.
Ultimately, equity portfolio construction is not about maximising returns in isolation, but about understanding and deliberately choosing the risks taken to achieve them.
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