October 7, 2020
A simple real-world definition of risk is the chance and consequences of being wrong. In Fairlight’s business as an investment manager, being wrong implies that we fail to meet our stated investment objective of outperforming the broader global small and mid cap market over the medium to long term. There are three distinct sources of risk that each contribute towards the total risk of the Fairlight portfolio:
1. Idiosyncratic Risk
Idiosyncratic (also called stock specific) risk is the risk that the businesses we own fail to meet our expectations or that we pay too much for these expectations. Fairlight runs a concentrated portfolio of 30-40 holdings with an active share that has ranged over time between 97-99%. Consequently, in most market environments, the predominant source of risk in the Fairlight portfolio is idiosyncratic risk. Prior to COVID-19 Fairlight’s risk model attributed roughly 70% of total portfolio risk to idiosyncratic risk with the remainder being factor or macroeconomic in nature. During the most turbulent months of the pandemic this ratio inverted with idiosyncratic risk accounting for just 30% of total portfolio risk while macroeconomic risk dominated.
Complete mitigation of idiosyncratic risk is undesirable as it is the primary source of excess returns for successful stock pickers. Instead it is the role of the Fairlight investment team to ensure that all stock-specific risk is consistent with the firm’s investment philosophy and on balance, expected to generate returns consistent with the investment objective. This is an entirely qualitative process and is dependent on the quality of the investment team and associated processes.
Fairlight uses a checklist methodology to ensure that all investment ideas are thoroughly tested for risk during the research phase. This process is used to establish whether the business model of the candidate company is of an unusually high quality and is expected to remain so in the future. By focusing exclusively on high quality companies Fairlight is less exposed to the negative surprises more common in cyclical and asset heavy industries. All else equal, a higher assessment of business risk results in a lower stock valuation.
The primary tool available to the Fairlight portfolio managers for managing idiosyncratic risk is position sizing. Where a portfolio holding is deemed to have a relatively higher level of business or valuation risk, the position size is kept smaller.
2. Style/Factor Risk
Style and factor risks are primarily managed by quantitative methods. Risk models are developed from statistical techniques that identify the covariance (co-movement) of securities with a range of investment factors. These factors can be investment styles (value, growth etc), industries, geographies, and economic variables. Risk models work best on large portfolios (over 100 securities) with low active share which is the inverse of the Fairlight portfolio. As a result, while risk models provide the Fairlight portfolio managers with important information, an appreciation that the results include a significant amount of statistical noise is essential to any interpretation.
As of September 2020, the Fairlight fund is effectively neutral versus the market on growth, momentum, and size and modestly underweight value. The most significant overweight risk exposure is to the quality factor - a deliberate exposure that is in keeping with the Fairlight investment philosophy. Over time quality investing has beaten the market with lower risk and so we consider this exposure to quality to be favourable and a permanent feature of the fund.
3. Macroeconomic Risk
Macroeconomic risk is managed by a combination of quantitative and qualitative methods. Scenario testing can be run against a battery of historic environments to simulate the performance of the portfolio during these events. The qualitative contribution comes from the creativity of the team to envision macroeconomic environments that have not yet happened and test for the performance of the portfolio in these possible states of the world. Managing macroeconomic risk is about trade-offs as no portfolio will outperform in all states of the world. Instead the Fairlight portfolio managers must shape the portfolio such that no individual scenario produces an unacceptable outcome.
Figure 1 shows the performance of the Fairlight portfolio and the benchmark in a range of macroeconomic scenarios. The portfolio is expected to relatively outperform in significant market sell-offs and on balance this macroeconomic risk profile is in keeping with the objectives of the Fairlight fund.
The Fairlight View
Managing risk in a concentrated portfolio requires the application of equal parts of qualitative insight and quantitative modelling. Since inception the Fairlight portfolio has outperformed despite consistently maintaining a lower risk profile than the benchmark