Jan 20 2016 Posted: 09:14 GMT

NUI Galway are co-authors of an international study that finds stock market crashes can be compared to unexpected ecological disasters and natural calamities

An interdisciplinary team of scientists from NUI Galway, the Indian Institute of Science (IISc) and Ecole Normale Supérieure Cachan in France, came together to examine if market crashes exhibited the same early warning signs as natural calamities. Their investigation reveals interesting answers and suggests improved metrics for forecasting a market crash. The study was published in the open access science journal, PLOS ONE.

While financial analysts can guide you through the daily ups and downs of the stock market, accurate forecasts of an imminent crash is still difficult to predict. Just like natural calamities, stock market crashes occur frequently and often have repercussions for the global economy. Experts are now looking at natural disasters for clues to understand economic ones.

Currently volatility in stock prices is used as a basic risk indicator. However, the recent financial crisis of 2007-2008 that caused global markets to shut down temporarily, reminded experts that this is not enough to prepare for a crash. Are there any other signs that we could watch out for? Whispers of a probable answer came from an unexpected field – ecology.

Professor Vishwesha Guttal, Mathematical Ecologist at the Centre for Ecological Sciences at the Indian Institute of Science and lead author of the published study, said: “There is a lot of interest in the exchange of ideas between ecology and economics.” This study sprung from Professor Guttal’s discussions with Dr Srinivas Raghavendra, an Economist at the J.E. Cairnes School of Business & Economics at NUI Galway, looking at the behaviour of financial markets as complex systems.

Financial markets are suggested to be akin to ecological systems with complex feedback loops and sudden critical transitions, also known as ‘tipping points’. A stock market crash can be compared to unexpected natural transitions such as the onset of the Ice Age, desertification of a fertile area, and the collapse of local fisheries, are just some examples. In recent years, ecologists have been looking for behavioural clues of complex systems in these natural events.

It turns out that many complex systems in nature exhibit ‘critical slowing down’ behaviour before reaching their tipping point. This means that just before a critical transition, it takes longer for them to recover from small disturbances because their internal stabilising mechanisms become weak. Hence, the system stays ‘disturbed’ for a longer time than usual, which means that the system becomes highly correlated in the disturbed state.

To test this theory on stock market crashes, Professor Guttal and his team rigorously analysed the daily closing data of three major U.S. (Dow Jones Index (DJI), S&P 500 and NASDAQ) and two European (DAX and FTSE) markets spanning the last century. In all cases, they found that variability did increase prior to every known market crash in history. Which means the financial system does get significantly ‘disturbed’ before a crash. But curiously, there was no increase in the autocorrelation of data.

Autocorrelation indicates how similar the data is across different time samples. This means that, once markets are ‘disturbed’, market recovery happens as usual without a ‘slowing down’. This trend is consistent for all crashes across all markets studied by the team. “Many papers suggest that financial meltdowns are also transitions near tipping points, but here our research shows that they are not”, added Professor Guttal.

Then why do markets crash? Professor Guttal explains, “We suggest this is because the system is dominated by high stochasticity (randomness). Our results indicate that if random disturbances in the market grow stronger with time, they can lead to a financial meltdown even if the market is not close to a tipping point. Variability can therefore be an important statistical indicator in early warning signals (EWS) for market crashes, complementing existing indicators such as volatility.”

Could this study have policy implications? NUI Galway Economist, Dr Srinivas Raghavendra and co-author of the study says, “To build robust policies and corrective measures in the future, we need to understand the origin of randomness that drives market meltdowns. This may arise from complex interactions between financial institutions, market microstructure and individual agent behaviour, all adapting at different time scales. Deconstructing such a complex system is necessary for effective policy intervention.”

However, there are two major limitations in predictability of such indicators. They don’t indicate when a crash may happen and they only suggest a high probability of a crash. In this detailed study of Dow Jones data, 16 early warning signals emerged from the variability calculations. Of the 16, seven were false alarms. But the good news is that there were no failed alarms and the remaining nine covered every major crash in American market history.

Mr Nikunj Goel, an undergraduate physics student who worked with Professor Guttal on this study, has developed a basic web application that provides current trends in markets around the globe. It also shares analysis on historical meltdowns from their published study. The team hopes to add more features to this app and make it more user-friendly.

To read the full study in PLOS ONE visit: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0144198

Nature-India, Nature Publishing Group, carried an in-depth article on the paper here: http://www.natureasia.com/en/nindia/article/10.1038/nindia.2015.178


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