The farther backwards you can look, the farther forward you are likely to see – Winston Churchill
During the ERM crisis in 1992 I was a still a relatively young trader and had the good fortune to witness some of the best risk takers in the world – the Susquehanna group – who had a joint venture with my employer, the Chase Manhattan Bank. I learned more during that ERM crisis in 1992 than I have in the rest of my career.
The main lesson I learned is that being short gamma can wipe you out in a hurry. During the ERM crisis, Swedish interest rates touched 500% USD-Deutschmark was moving 10-15 figures in a matter of hours. Everyone was trying to make sense as the uncertainty saw market volatility spinning out of control.
Why is this relevant? Well partly because, despite the 2008 crash, few traders of today really understand risk and risk management. They persist in believing that “Value at risk” – or VaR – offers a true picture of the amount of risk exposure in the market – manage your VaR and you are OK. But times like 1992, the 2000, 2008 – and maybe even 2012 – show us that why VaR doesn’t work. That’s because VaR doesn’t properly quantify or describe the “tail risk”, that small percentage of the time when markets do what the statistical models don’t account for: go crazy.
In crude terms, VaR explains to you the risk of the volatility on any given day with 95 per cent certainty. But what about the remaining 5 per cent? That’s where the VaR model quickly breaks down, because at times when markets run into a truly volatile patch, pricing becomes downright discontinuous as liquidity dries up – the market moves in astounding gaps rather than in the normal step-wise fashion of more normal times.
As the prices jump around, the correlations upon which 90 per cent of VaR is built simply collapse. And if you are caught the wrong way – there is no market and there is no hedge as everything moves quickly and in the same direction.
The kind of tail even described above is the ultimate risk of our current zero interest rate policy (ZIRP) and quantitative easing (QE) environment. The banks are full of deposits and have “free money” from the central banks that they can use to chase what appear to be risk free trades. As these build and build, there are no signs of volatility because past market behaviour shows none. But while all appears quiet, leverage is building and building and the returns are shrinking and shrinking while volatility appears to fall and fall. Ironically, the very VaR measures that show ever more moderate risk are failing to pick up the systemic risk that is building in such a system. But the grey haired traders know that common sense is sometimes worth a lot more than a fancy statistical model.
The FED and the ECB have increased the systemic risk as banks have vastly increased their exposures to illiquid markets over the last couple of years – not decreased them. In a tragic replay of the kinds of things we saw in 2007 and 2008, the trades are now starting to blow up.
I will not make any specific comments on JPM and their loss, as the situation is rather opaque, but these kinds of trade loss revelations are symptomatic of the early phases of the dynamic I describe above. These kinds of losses cropping up yet again can be put down to a lack of grey hair and common sense.
The old fashioned macro trader who has both lost big on a trade, but then recovered it by respecting the fact that you need to have something left in reserve if you want to trade tomorrow, is no longer part of the top management at banks, central banks or most hedge funds.
Nowadays, it seems that it is all about being able to write sophisticated algorithms and pumping up the high frequency trading machines to push for maximum yield at all times with weak statistical arguments for the true level of risk actually involved. In this push-it-to-the-limit game, nearly everyone comes to the same conclusion and pursues the same strategy, which inevitably leads to a sudden and dire loss when the market simply disappears. My grey hair is telling me we are reaching a point of no return.
The old saying goes that being short gamma is like picking up dimes in front of a steam-roller, it appears to create such nice, consistent modest returns over time, but what happens that day when you slip and fall and can’t get out of the way in time?