Game, Stress & Match

I took the morning off to watch Andy Murray’s semi-final in Australia before heading to the Centre for the Study of Financial Innovation for a discussion on risk modelling. Intriguingly, it was the guys sponsored by RBS who outshone at both events.

At the CSFI, it was widely agreed that risk management hasn’t been effective. Value at Risk came in for a lot of criticism. No surprises there. Stress testing got an honourable mention.

But two contributions stole the day for me. One has been featured widely in news coverage. The other needs to be. After several games hitting too short and getting knocked all over the court, Murray’s amazing retrieval at break point in the second set turned the match around and relieved the stress (on both sides of the camera).

At the CSFI, Riccardo Rebonato of RBS got rather less acclaim for a point that is just as much of a game-changer. It’s all very well knowing the probabilities of a given level of loss. But, without an understanding of the mechanism that delivers those losses, the probabilities can’t tell you what to do. This thesis was dismissed by those who gave the example of the dot-com bubble. It was widely understood, they said, but few dared to stop buying during the boom for fear of losing their job.

I came away from the event with a three point breakdown of the issue. First are the amounts at risk and the associated probabilities. Second are the scenarios that deliver those outcomes. Third is a willingness to believe that the scenarios could actually unfold. We may not have found the solution for the third step – incentives, someone? – but it is a huge mistake to think the second step isn’t crucial.

What does this tell us for the future? It’s been 74 years since a Brit won a Grand Slam event. But I am willing to believe Andy Murray can win Sunday’s final. He certainly knows a scenario for achieving it – Murray is actually 6-4 ahead in matches against Federer. Do the probabilities (or the prize money) really matter?