Like the famous King Midas, popularly remembered in Greek mythology for his ability to turn everything he touched with his hand into gold, the wealth of data generated by modern technologies, with widespread presence of computers, users and media connected by Internet, is a goldmine for tackling a variety of problems in the financial domain. Nowadays, people’s interactions with technological systems provide us with gargantuan amounts of data documenting collective behavior in a previously unimaginable fashion. Recent research has shown that by properly modeling and analyzing these massive datasets, for instance representing them as network structures, it is possible to gain useful insights into the evolution of the systems considered (i.e., trading, disease spreading, political elections). Investigating the impact of data arising from today’s application domains on financial decisions may be of paramount importance. Knowledge extracted from data can help gather critical information for trading decisions, reveal early signs of impactful events (such as stock market moves), or anticipate catastrophic events (e.g., financial crises) that result from a combination of actions, and affect humans worldwide.
MIDAS 2016: The 1st Workshop on MIning DAta for financial applicationS
Caldarelli G;Squartini T
2016-01-01
Abstract
Like the famous King Midas, popularly remembered in Greek mythology for his ability to turn everything he touched with his hand into gold, the wealth of data generated by modern technologies, with widespread presence of computers, users and media connected by Internet, is a goldmine for tackling a variety of problems in the financial domain. Nowadays, people’s interactions with technological systems provide us with gargantuan amounts of data documenting collective behavior in a previously unimaginable fashion. Recent research has shown that by properly modeling and analyzing these massive datasets, for instance representing them as network structures, it is possible to gain useful insights into the evolution of the systems considered (i.e., trading, disease spreading, political elections). Investigating the impact of data arising from today’s application domains on financial decisions may be of paramount importance. Knowledge extracted from data can help gather critical information for trading decisions, reveal early signs of impactful events (such as stock market moves), or anticipate catastrophic events (e.g., financial crises) that result from a combination of actions, and affect humans worldwide.File | Dimensione | Formato | |
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