The failure of bank risk models was inevitable. Worse, it was predictable. In grave danger of sounding incredibly immodest, I, and others, predicted it a few years back in a series of articles and lectures including Banks put themselves at risk in Basel, Financial Times, October 17, 2002, The Folly of Value at Risk, Gresham Lecture, December 2, 2002, and the Jacques de Larosiere Prize essay, Sending the herd off the cliff edge: the disturbing interaction between market-sensitive risk models and investor herding, published by the IIF in September 2000. Of course, I am not normally allowed to point this out without being considered an ?uppity Indian?. With a few exceptions, western intelligentsia rejects the notion that an Indian, working outside the US, could have foretold the failure of the financial economics coming out of the eastern sea board of the US, but the record is there for all to see.
The problem with the risk models had nothing to do with fashionable explanations like ?Black Swans?. Nor will the problem be solved by statisticians, fattening their tails, or in layman?s language, considering that random, extreme events, are more common than previously thought. The latest fashion for network economics may have more useful potential, but you didn?t need it to predict the failure of risk models. There are two reasons why the models failed and had to do so: one narrow and technical, the other, broader and bordering on the philosophical. Neither is complex. But regulators and central bankers chose to ignore these explanations in the past, which is why they are now running for cover by entertaining new-fangled ideas that they can say weren?t around at the time. It is far better for a policymaker to be wrong for new reasons than to be wrong for old reasons.
The technical explanation is that the market-sensitive risk models used by thousands of market participants work on the assumption that each user is the only person using them. This sounds too silly to be true but remember that this was not a bad approximation in 1952, when the intellectual underpinnings of these models were being developed at the Rand Corporation by Harry Markovitz and George Dantzig. Messers Markovitz and Dantzig were the only ones using them, and even after the dissemination of their ideas, the scarcity of computing power and data meant that you could safely assume you were the only one using a mean-variance optimiser.
Remember that this was also a time of capital controls between countries and the segmentation of domestic financial markets. Back then you didn?t need to worry about foreign arbitragers, insurance companies acting like hedge funds or foreign investors boasting larger computers. To get the historical frame right, it was the time of the Morris Minor with its top speed of 59mph, available in any colour, as long as it was in the surplus green paint left over from the war.
In today?s flat world, market participants from Argentina to New Zealand have the same data on the risk, returns and correlation of financial instruments, and use standard optimisation models, which throw up the same portfolios to be favoured and those not to be.
Market participants don?t stare, helplessly, at these results. They respond. They move into the favoured markets and out of the unfavoured. Enormous cross-border capital flows are unleashed. Under the weight of the herd, favoured instruments cannot remain undervalued, uncorrelated and low-risk. They are transformed into the precise opposite.
Back in 1995, for example, the five year correlation matrices almost all large investors had access to suggested that the most favourable place on the risk-return tradeoff, a place with high returns, low volatility and low correlation, was Asian equities?and so the herd piled in, pumping up an unsustainable boom. This strategic behaviour?which the models assumed did not exist?set up the problem. The problem hit when a spark of volatility flew and all market participants who had herded into favourable sectors tried to reduce their exposure to risk by selling the same instruments at the same time.
A vicious cycle would then ensue. The weight of selling led to vertical price falls which shot up recorded risk, prompting the sale of other assets. These other assets were also in favourable sectors that everybody owned and so alongside vertical price drops and high volatility came rising correlation, which prompted the risk models to go into hyper-drive, requiring investors to sell assets across the board, pushing correlations to 1 as all prices gapped lower, no buyers could be found and everyone wanted cash. Liquidity vanished down a black hole. The degree to which this occurs has less to do with the precise financial instruments. It is not about credit default swaps or OTC, but the depth of diversity of investor behaviour. If all investors are following the same model and behaving the same way, systemic collapse is total and inevitable. More generally, the observation of areas of safety in risk models paradoxically creates risks, and the observation of risk creates safety. Quantum physicists will note a parallel with Heisenberg?s uncertainty principle.
This brings us to the philosophical problem of the reliance of supervisors on market-based, bank risk models. The reason we regulate markets over and above normal corporate law is that from time to time markets fail and these failings have devastating consequences. If the purpose of regulation is to avoid market failures, we cannot use, as the instruments of financial regulation, risk models that rely on market prices, or any other instrument derived from market prices such as mark-to-market accounting. Market prices cannot save us from market failures. Yet, this is the thrust of modern financial regulation, which calls for more transparency on prices, more price-sensitive risk models and more price-sensitive prudential controls. These tools are like seat belts that stop working whenever you press hard on the accelerator.
The reliance on risk models to protect us from crisis was always foolhardy. In terms of solutions, there is only space to observe that if we rely on market prices in our risk models and in value accounting, we must do so on the understanding that in rowdy times central banks will have to become buyers of last resort of distressed assets to avoid systemic collapse. This is the approach upon which we have stumbled. It is called TARP in the US and the Asset Protection Scheme in the UK. In Europe, the ECB has been forced to buy large quantities of paper it would not previously have considered strong enough collateral. But the asymmetry of being a buyer of last resort, without also being a seller of last resort during the unsustainable boom will only condemn us to cycles of instability.
The alternative is to try to avoid booms and crashes through regulatory and fiscal mechanisms designed to work against the incentives?fed through risk models, bonus payments and the economic cycle?for traders and investors to double up or more into something that the markets currently believe is a sure bet. This sounds fraught and policymakers are not as ambitious as they once were. We no longer walk on the moon. Of course, President Kennedy?s 1961 ambition to get to the moon within the decade was partly driven by a fear of the Soviets getting there first. Fear is an even stronger motivator than greed. Regulatory ambition should be set now, while the fear from the current crisis is fresh and not when the crisis is over and the seat belts appear to be working again.
?The author is an international economist, chairman of the Warwick Commission; member of the UN Commission of Experts; external member of the UK Treasury?s Audit and Risk Committee and chairman of Intelligence Capital Limited