How maths theories can destroy markets – FT中文网

Lecturing Birds on Flying

Can Mathematical Theories Destroy the Financial Markets?

By Pablo Triana

Wiley $29.95/£19.99

Should the Nobel Prize for economics be abolished? That is one of the suggestions in Pablo Triana’s provocative book Lecturing Birds on Flying. Triana, formerly a derivatives trader and academic at the University of Madrid, makes a simple assertion. Financial models, such as value at risk (VaR) and the famous Black-Scholes-Merton (BSM) model, which won its founders a Nobel, have done more harm than good. “Make no mistake, quantitative finance had a very large hand in what could well be the worst financial crisis in the history of mankind,” he writes.

His book is a critique bordering on an assault on mathematical – or quantitative – finance. From the opening chapter, “Playing God”, Triana maintains that the fundamental assumptions on which mathematical finance theory are based are wrong. Yet the theory continues to hold sway.

The biggest villain of the piece is the financial academic establishment. Much of its work, he says, has been unnecessary. Before mathematical finance, traders had working models for things such as option pricing. By and large, these models were effective and accurate. Then came BSM, which Triana claims does not work and was also largely responsible for the 1987 stock market crash. What is more, he maintains, most traders know it does not work and only pretend to use it because finance theory is fashionable and criticising BSM is a heresy.

BSM is not the only case. The Gaussian copula model, which was intended to measure default probability, failed to identify toxic structured securities and led to massive errors in valuation and credit ratings, says Triana. Likewise VaR “failed to measure risks even half- accurately and, worse, decisively encouraged and sanctioned the wild risk-taking that brought Wall Street (and consequently the world) down”.

Old-fashioned commonsense methods were replaced by theoretical models based on mathematics, developed by people who had no practical knowledge of markets yet decided they knew better than the traders how markets operated. Hence the “lecturing birds on flying” title (one of the kinder metaphors; elsewhere, Triana compares finance academics to virgins making porn films). And, he says, everyone falls for this – including the traders themselves. Finance academics continue “churning out quantitative hodgepodge” and Wall Street and others continue to use it.

Triana devotes a chapter to the “quants”, the mathematicians and physicists who became influential in many big finance houses and imported academic models with them. For a time, employing quants was trendy: it showed the firm was using science to beat the market.

But the market had its revenge. “Markets can’t be tamed with equations,” says Triana. “Maverick, unlawful human action rules the markets, unexpected and unimaginable monstrous events shape the markets.” But in the end, he wonders if people will ever come to terms with this. In one chapter, “An Unhealthy Yearning for Precision”, Triana argues that our “fear of the unknown and our desire for certainty lead us to throw ourselves into the arms of perceived ‘experts‘ . . . We trust quantitatively flavoured constructs to escort us away from the gloomy reality of unmeasurable uncertainty”. But they are leading us in the wrong direction. As Nassim Nicholas Taleb says in his witty introduction to the book, giving someone the wrong map is worse than giving them no map at all.

On the whole, this is a good read. Some may find the elaborate prose – closer to Cervantes than to, say, (Nobel prizewinner) Robert Merton – annoying. But perhaps Cervantes is the right writer to emulate when tilting at windmills. For it seems likely that, no matter how hard observers such as Triana and Taleb try to demolish it, mathematical finance is not going away.

via How maths theories can destroy markets – FT中文网.

Very interesting and I find myself agreeing with many if not most points of the book. The must cite for my work!

The better way out is to complement rather than replacing the existing scientific models, and this is why ecological research is so important: it allows a space of existence for scientific research

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