As the real estate industry looks to learn from the fallout of covid-19, one issue which should be at the top of the list is to recognise the glaring mathematical limitations in the traditional performance measurement models. Engineering a solution is important; as with high value thresholds and illiquidity, investment decisions cannot be easily changed when we experience an extreme risk event – unlike completing marketable liquid asset classes.

Currently, the performance of commercial property is principally measured by recognised mathematical models of return (mean) and risk (standard deviation). These statistical approaches provide the backbone for many in the investment community to compare performance across asset classes, and importantly the foundation for leading investment strategies: risk-adjusted returns, capital asset pricing models and modern portfolio theory.

There is increasing evidence (see Nassim Taleb’s work) that while the application of the standard deviation model works well under stable conditions, the formula fails when stable assumptions cease to hold and extreme volatility occurs, as demonstrated by the recent severe pricing swings associated with the global financial crisis (GFC) and now as we begin to see the impact of covid-19.