Calculating the madness of markets

This article appeared first in the latest issue of the Market magazine, use the link to the left to view the whole magazine.

Financial crises remain one of the hardest catastrophe scenarios to model, not least because it comes down to the most unpredictable element of all – people.

When sir isaac newton was caught out after speculating in the South Sea Bubble fiasco of 1720, he wrote: “I can calculate the motions of heavenly bodies, but not the madness of people.” One of the greatest minds in history was rueing his defeat by the sheer craziness of an investment boom that – inevitably – went horribly wrong.

The South Sea Bubble was neither the first nor the last time huge numbers of people lost huge amounts of money in a financial crisis. A glance at the bookshelves demonstrates the need to understand what went wrong: a search on Amazon.com for books matching ‘credit crunch’ returns more than 1,500 results. But is there anything that we can learn from previous crises? Who are the oracles with the wisdom that will let us enjoy the next boom and avoid its bust?

Insurers are well equipped with models that help them predict risk. In the property classes they can help insurers prepare for windstorm and earthquake risks. This is particularly important in today’s world, where global warming, and
the resulting change in climate, is causing natural disasters to occur more frequently.

On the face of it, there has been plenty of financial crises but each have different characteristics. Conditions are different, regulators close loopholes and sometimes people only remember the last big bust. It adds up to the past not
being a particularly good guide to the future, which is the premise on which models are traditionally based.

The curved ball of the future
Paul Nunn, Head of Exposure Management at Lloyd’s, says that insurers need models in order to be confident they have allocated enough capital to deal with shocks to the expected situations. Lloyd’s uses realistic disaster scenarios to test the effects of various calamities. The scenarios include natural disasters and liability questions but not financial meltdown scenarios, because they do not produce useful information.

He says: “We know there’s a correlation between recession and claims activity but quantifying that impact is difficult. It’s not that we wish to ignore it, it’s just very challenging.”

A bust, by its nature, is something that has already beaten everyone. Nunn says: “Most people try to learn lessons from the past but the curved ball of the future will always be something different.”

There are other techniques besides trying to predict the future. Reinsurance broker Guy Carpenter and modelling consultants Arium Risk Architecture are working together on modelling liability risks.

George Carrington, Managing Director of Guy Carpenter, says: “While we cannot predict the exact perils that might give rise to a liability catastrophe, we can identify which portfolios might be more vulnerable to an event.”

For example, a portfolio might cover industries related by a supply chain such as farmers, food manufacturers, food distributors and food retailers, or it might cover a number of insureds that engage in similar higher-risk activities, such as chemical manufacturing. Carrington describes the prototype model they have developed as an underwriting tool to help manage and mitigate vulnerabilities.

Talk about the weather
But what about the holy grail – a model to predict the next big bust? Professor David Hand, a statistics specialist and Director of the Quantitative Financial Risk Management Centre at Imperial College London, says that financial markets are a bit like the weather: huge and complex, but following reasonably well-understood principles – until a stochastic jump comes along. These are the unpredictable influences that throw everything off course and are the forecaster’s bane. An example would be a terrorist attack that sends people seeking security in gold, perhaps, and withdrawing from equities.

In the case of the credit crunch, Hand says: “In the current circumstances, I think it was a problem of people getting carried away. The risk assessment instruments were there and people were using them, but they essentially ignored them.

“We’ve got good models and we’ll go on refining them, but my view is that the problem isn’t the model but the people making the decisions based on them. And this is why you get something like the dotcom crash. It’s terrible when it happens but people gradually recover and forget.”

Asked to predict the future of predicting the future, he foresees models integrating psychology, ideas of motivation and why people behave the way they do. Maybe then we will be able to calculate, as Newton could not, the madness of people.