The quants weren't exactly out on the trading floor, however. The best of them still spent their days writing papers, crunching numbers, applying their academic expertise to the world of business. Li had come to New York to work for a consultancy called the RiskMetrics Group, which had been spun out of JP Morgan, but he was still thinking about life, death and love. In 2000, he published a paper in the prestigious Journal of Fixed Income that gained some serious attention. In it, Li performed a most elegant trick. Borrowing from his work in actuarial science and insurance and his knowledge of the broken-heart syndrome, he attempted to solve one of Wall Street quants' most intractable problems: default correlation.

Markets do not function in laboratory-like isolation. They are linked, correlated. It isn't enough for any quant to try and know the probability of each individual company in his bank's portfolio going bust; he has to know how the bankruptcy of one company – or several – might increase (or decrease) the likelihood that other companies will default. Suppose, for example, that a bank loans money to two outfits – a dairy farm and a dairy. The farm, according to ratings agencies, has a 10 per cent chance of going bust and the dairy a 5 per cent chance. But if the farm does go under, the chances that the dairy will follow will rise above 5 per cent – quickly and steeply – if the farm was its main milk supplier.

And it gets more complicated from there. How correlated are the default probabilities on bonds issued by our Irish dairy farm and those issued by a software company in Malaysia? Not at all, you might think: the businesses not only provide totally different products and services, they're also geographically remote from each other. Suppose, though, that both companies have been lent money by the same troubled bank that is now calling in its loans.