Financial Times, 20 March 2009
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Markets + maths = mayhem. That equation sums up an erroneous view of the role played by mathematics in the banking crisis, which is gaining currency in financial and regulatory circles. For example, this week’s report by Lord Turner, chairman of the UK Financial Services Authority, blamed “misplaced reliance on sophisticated maths” for lulling banks’ top managers into a false sense of security about the risks they were taking. Terms such as quant, geek and rocket scientist, once used in affectionate respect, now have darker connotations.

Mathematicians tend to be shy and retiring, compared with other professional groups, and they have not leapt up to defend themselves in public. In private, however, they are seething – understandably so, since the problem was not the maths itself but the way banks used it.

Contrary to Lord Turner’s assertion, the banks’ sums were not sophisticated enough. They over-simplified, and assumed away the limitations and caveats of their models. They did this to convey an illusion of accuracy and precision, and so convince the market that they had everything under control.

The standard risk measure used by the industry from the mid 1990s, known as value-at-risk or Var, was criticised by mathematicians almost from the start for the way it drew inferences about forward-looking risk from past patterns of price movements. As a result, the risk of extreme bank-shattering events was greatly underestimated.

Essentially, financial institutions told their “quants” to build mathematical models that fitted market prices – and never mind if those prices were way out of line, on any fundamental analysis. As a result, mispricing was supported by a spurious veneer of scientific respectability. And the industry was caught in a “positive feedback loop” from which no one dared walk away.

For the future we need more – and better – maths to underpin individual banks and the enhanced regulatory regime that will oversee them. Some of the expertise required is already out there, in universities, waiting to be put to use.

But financial mathematics has been underfunded, given its economic importance, and both private and public sectors must commission more research in the field. For instance, we need to know more about the way human psychology affects market models – and about the scenarios in which models break down.

At the same time, senior bankers must become better informed about the mathematical basis of their industry. Total ignorance of the “black box” trading systems used by their companies is not an acceptable excuse for failure.

Finally, mathematicians should abandon their traditional reticence and fight strongly for their discipline. Then the financial world will appreciate the true equation: markets minus maths mean mayhem.

Copyright The Financial Times Limited 2009