Plants and animals under stress may provide the key to better stock market predictions

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 greater.

The team also looked at human physiology including the way healthy people adapted to a change in climate conditions and the clinical signs accompanying fatal outcomes in cancer and cardiology clinics.

The report says stocks and shares showed a similar pattern during the financial crisis of mid 2008. Stocks became more interdependent and volatile as the FTSE100 decreased but by the end of the year the system became less connected and even more volatile, suggesting a crash as the financial systems failed to adapt to the changed circumstances of the market.

For more information, please contact Professor Gorban on, email [email protected]

Notes to Editors

A fuller version of this press release is available here:

The research was published in the journal Physica A, (Vol. 389, Issue 16, 2010, pp 3193-3217). A preprint is also available online:

Professor Gorban’s team also charted share price information in time intervals to gauge the chronology of crisis including. The theory is supported by analysis of these data provided by various authors:

  • Stock market data from 1000 US companies from 1994-95
  • The Istanbul Stock Exchange market 2000-2005
  • 30 largest companies in the British stock market 2006-2008
  • Three major US stock Exchanges — the American Stock Exchange (AMEX), the New York Stock Exchange (NYSE) and the National Association of Securities Dealers Automated Quotation (NASDAQ).
  • Monthly excess returns for seven countries (Germany, France, UK, Sweden, Japan, Canada and US) between 1960-1990.

The work draws on the concept of “adaptation energy” put forward by Hans Selye, the endocrinologist, in the 1930s. He claimed that living things have hidden reserves, or adaptation energy, which helps combat stress by compensating for the loss of constituents vital to health.

Selye describes adaptation energy as physiological resources that can be drawn on when an organism is under biological stress. Gorban and his colleagues say the same notion can be applied to financial systems.

Professor Gorban is Chair in Applied Mathematics, at University of Leicester, UK and Chief Scientist, at the Institute of Computational Modelling, Russian Academy of Sciences, Russia. He is best known for his work on physical and chemical kinetics and data analysis as well as more for his work on how humans adapt to hard living conditions.

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