Risk management takes real skills, developed over time, with tools to formulate options for any series of events that may occur during the life of a project. Those options range from negative risk, where an event will harm the project, to positive risks, where an event reveals a new opportunity to pursue.
But the real challenge is when a black swan appears. Black swans are big, bad, unanticipated catastrophes that force change. Sometimes referred to a VUCA and demanded a new way of thinking and responding to risk.
Black swans aren’t restricted to weather. In finance, they present mathematical challenges that earn Nobel Prizes for those who find new ways of modeling for the risks they represent, folks like Robert Engle.
The 2008 sub-prime mortgage crisis was a black swan. Recently, the graduate school at Simon Fraser University in Burnaby Canada took a deep-dive into how black swan events affected Value at Risk (VaR) strategy and published a case study on the top four methods used to set on a 10 million student services fund it has been building since 2003.
The study, while looking at the best of the best in risk management practices, pointed to three myths about which we should be aware.
One: Things Work When We Choose a Best Practices Strategy.
- The low-risk model, HS, over-estimated Swan for one year. That means the fund didn’t take advantage of stocks that were actually in positions to increase returns.
- 73% of banks use HS – that activity holds back investments that could stimulate growth only because the model is deficient, not because the opportunity was bad.
Two: What’s Good For a Fortune 50 Company is Good For Us.
- There is inconsistency even among the biggest players who are responsible for protecting the public from financial risk.
- In a study of VAR among the “Big 5” Canadian banks, researchers Xiaoya Chen and Duo Zheng studied data from 4340 trading days, including the beginning of the black swan. During that time a total of 43 exceptions (days where losses exceed the VaR) were acceptable to regulators, but 47 exceptions were created. When they drilled down into each bank, they found larger variances with two of the banks (BNS and TD) very close to the norm and two others BMO and RBC) significantly exceeding it.
- Even among the biggest players in the same industry risk is seen differently. To hold them up as a standard for project managers to use is foolhardy.
Three: Choosing a Well Engineered Best Practice Means We Can Short-cut Analysis
In the SIAS fund, the risk management strategy was weakened by the governance process focused on individual stock volatility rather than portfolio risk. They used seven teams to make strategic decisions which would go through a voting process resulting in a slow turnover and trading frequencies. The advisors, including three from top Canadian banks, tended to review the effectiveness of the team and how well past strategies held up. Rather than deep dive into the details of the chosen VaR, the methods used were accepted as industry standard.
It wasn’t until Hsieh and El-Hourani took on a more in-depth analysis of the portfolio for their thesis that it came to light that the ratios used for individual stock evaluation were flawed when looking at the collection. The short-cuts were taken, despite using best practices and industry standards were not good enough to optimize results and the black swan event pointed out the deficiency in the strategy.