Evidence from the US Commercial property market suggests periods of extended stable performance are generally followed by large concentrated price fluctuations. This extreme volatility may not be fully reflected in traditional risk (standard deviation) calculations. This research studies 38 years of NCREIF commercial property market performance data for normal distribution features and signs of extreme downside risk. Methodology covers the recognised Z Test and the fractal geometry, Cubic Power Law instrument. For the reporting of annual returns on quarterly figures, the industry preferred investment performance measure, the results showed the data to be both asymmetric, and being taller and narrower than a normal bell curve distribution with fat dumb bell downside tails at the perimeter. In highlighting the challenges to measuring commercial property market performance, the research revealed a better analysis of extreme downside risk is by a Cubic Power Law distribution model, being a robust method to identify the performance of an investment to the vulnerabilities of serve risk. Modelling techniques for estimating measures of tail risk provide challenges and have shown to be beyond current risk management practices, being too narrow and constraining approach.