News
UMass Dartmouth professor helps ID stock market crash signal
Charlton College of Business' Dan Braha part of team that offers framework for early warning system so policy makers can mitigate the economic damage.
Using new statistical analysis tools of complexity theory, UMass Dartmouth Charlton College of Business Professor Dan Braha and his fellow researchers at the New England Complex Systems Institute (NECSI) have shown that stock market crashes can be predicted.
"Current indicators and traditional models used by financial institutions of countries do not provide a complete description of systemic risk,'' Braha said. "They also fail miserably to provide a reliable early warning system of financial instability. Our paper takes on the challenge of solving this precise problem by providing a framework and method (based on complex networks theory) for a useful early warning system that can measure and detect the rise of systemic risk -- early enough for policy makers to intervene, mitigate, and stop the fire."
The study was done in response to a challenge by world leaders at the G-20 meetings in Washington - in the midst of the 2008 financial crisis to create an early warning system that would provide continuous monitoring of the stock market to anticipate financial meltdowns.
It has long been thought that market crashes are triggered by panics that may or may not be justified by external news. This new research indicates that it is the internal structure of the market, not external crises, which is primarily responsible for crashes.
The number of different stocks that move up or down together is an indicator of the mimicry within the market, how much investors look to one another for cues. When the mimicry is high, many stocks follow each other's movements - a prime reason for panic to take hold.
NECSI researchers show that a dramatic increase in market mimicry occurred during the entire year before each market crash of the past 25 years, including the recent financial crisis.
"We have demonstrated mathematically that there is significant advance warning to provide a clear indicator of an impending [stock market] crash," explained Professor Yaneer Bar-Yam, president of NECSI and principal investigator on the research.
For additional information, please visit http://www.necsi.edu/research/economics/economicpanic.html
"Current indicators and traditional models used by financial institutions of countries do not provide a complete description of systemic risk,'' Braha said. "They also fail miserably to provide a reliable early warning system of financial instability. Our paper takes on the challenge of solving this precise problem by providing a framework and method (based on complex networks theory) for a useful early warning system that can measure and detect the rise of systemic risk -- early enough for policy makers to intervene, mitigate, and stop the fire."
The study was done in response to a challenge by world leaders at the G-20 meetings in Washington - in the midst of the 2008 financial crisis to create an early warning system that would provide continuous monitoring of the stock market to anticipate financial meltdowns.
It has long been thought that market crashes are triggered by panics that may or may not be justified by external news. This new research indicates that it is the internal structure of the market, not external crises, which is primarily responsible for crashes.
The number of different stocks that move up or down together is an indicator of the mimicry within the market, how much investors look to one another for cues. When the mimicry is high, many stocks follow each other's movements - a prime reason for panic to take hold.
NECSI researchers show that a dramatic increase in market mimicry occurred during the entire year before each market crash of the past 25 years, including the recent financial crisis.
"We have demonstrated mathematically that there is significant advance warning to provide a clear indicator of an impending [stock market] crash," explained Professor Yaneer Bar-Yam, president of NECSI and principal investigator on the research.
For additional information, please visit http://www.necsi.edu/research/economics/economicpanic.html