From risk systems for advisors to algorithms used by firms like Wealthfront, quant risk management has gone mainstream. These systems have gone from being housed on supercomputers at large institutions to cloud-based systems with calculations that cost almost nothing. However, as cheap risk modeling revolutionizes the way everyone invests, it is important to keep in mind one crucial two-word question: "So what?"
Quantitative risk estimation on Wall Street has always been about attempting to hit the right risk level. In a world of wealth management, this is equivalent to hitting the proper risk tolerance for the investor.
So as robo-advisors and human advisors are adopting risk management systems they seem to be focused on the risk tolerance aspect of risk system implementation. But risk tolerance is only one of the aspects of the answer to the 'So what?' question. The other one must be the reason that an investor wants to take the risk in the first place.
After all, nobody really wants any risk; in an ideal world we would get return with no risk (and as advisors know, some investors seem to demand that). Risk taking is our sacrifice in order to achieve our goals. So a risk system that doesn't directly address the impact on the goals of the investors is leaving out the most important piece of value it could deliver.
I like to use car shopping as an analogy to the investing process. When we buy a car we are after certain things like performance, handling etc. In order to obtain things that we desire, we must incur risks. For cars, those are usually measured as crash test ratings from the Insurance Institute of Highway Safety. Let's imagine what it would it be like to buy a car with a view only to targeting our tolerance for risk and forgetting why we are tolerating risk.
Car Shopper: "I am considering these two cars, can you explain to me the difference between them?
