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Plants and animals under stress may provide the key to better stock market predictions
Date:11/3/2010

Stock markets react to crisis in a similar way to plants and the human body, according to a major new study that may help to predict future financial down-turns.

An extensive analysis of biological and financial data suggests that systems under stress exhibit similar symptoms, whether they be polluted forests, cancer patients or the FTSE 100.

There is an uncanny parallel between the way that humans, animals and plants adapt to harsh living conditions and the behaviour under stress of stock market prices and the banking sector, according to a report on the study by a team of academics led by Alexander Gorban, a Professor of Applied Mathematics at the University of Leicester, and including Tatiana Tyukina from the University of Leicester and Professor Elena Smirnova from the Siberian Federal University, Russia.

Warning signs may be detected -- even before obvious symptoms occur -- by charting the interdependence and volatility of key factors, the report claims.

The team has named this "order in chaos" theory the "Anna Karenina Principle", after Leo Tolstoy's turbulent novel which opens with the words: "Happy families are all alike; every unhappy family is unhappy in its own way." Professor Gorban explains that people, plants or stock markets function in a similar way until things go wrong at which point they start to react in different ways.

Studying how systems facing stress react in terms of becoming more interdependent and volatile reveals patterns that help to predict when a crisis may occur and the likelihood of death or recovery, he says. A key finding is that as the crisis approaches, systems become more dependent on each other but at the same time more likely to react differently.

A study of Scots pine trees near a power station showed that though the average compositions of the needles was similar to those outside the polluted area, the variance and interdependence of individual components were far
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Contact: Professor Alexander Gorban
ag153@le.ac.uk
University of Leicester
Source:Eurekalert

Page: 1 2

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