During the early days of the Latin American debt crisis, the renowned scientific hub created by the legacy of research institutions such as Los Alamos and Sandia National Laboratories and the Santa Fe Institute, was called in to lend a few financial insights.
Caught off guard by the crisis and losing billions, leading bankers flocked to Northern New Mexico seeking new, out-of-the-box ideas and solutions that would help prevent future losses.
It seemed to make sense. Could the scientists and researchers who study and understand the complex and seemingly unpredictable patterns in data capitalize on the same science to predict financial markets?
Until our own glossary is ready, you can find definitions of some aspects of Complexity Science at
Exploratorium CompLexicon
and at
ISAAC.
Yes.
This science is now commonly, and popularly, labeled Complexity Science.
In today’s information-based economy, Complexity Science explains the significant impact that vast amounts of data and information flows have on market structures and productive processes. Complexity Science has led to data mining techniques and algorithms that identify trading opportunities from current and historic stock price data. These methods have now been successfully applied to equities and futures markets.