Interdependencies in the financial global village

Speaker
Dror Kenett - Boston U
Date
30/11/2014 - 14:00 - 13:00Add to Calendar 2014-11-30 13:00:00 2014-11-30 14:00:00 Interdependencies in the financial global village This talk will present a new framework for quantification of the coupling and interdependences between different financial markets. The employment of ideas and techniques from complexity science and the proposed theory of coupled and interdependent networks to understand and quantify the role of connections and dependencies within a system and between different ones opens the possibility to manage the complexity, optimize the systems and reduce their vulnerability to failures. More specifically, we investigate the stock-stock correlations in individual markets as local market dynamics, and the correlation of correlations, meta-correlations, which represents global market dynamics. Furthermore, we make use of the recently introduced dependency network methodology, which enables a quantification of the influence relationships between the different markets. The methodologies presented provide the means to track the flow of information between different markets, and can be used to identify changes in correlations in strongly coupled markets. Finally, we will discuss different applications of network science in finance and economics, which demonstrate who one can use empirical financial data to construct a network that represents the financial system, and then use it to study different aspects such as structure, dynamics and stability. The world has become a global village, and this village is becoming smaller and smaller, with the continuous introduction of ways to interact and connect to other people. Thus, the methodology outlined in this talk will provide new tools and means to quantify, characterize and manage the complexity of the world’s economy. The methodologies presented here can be used as the basis for quantitative early warning tool, a “financial seismograph”, which will provide policy makers the necessary precursors for significant local and global economic events. אוניברסיטת בר-אילן - Department of Mathematics mathoffice@math.biu.ac.il Asia/Jerusalem public
Abstract

This talk will present a new framework for quantification of the coupling and interdependences between different financial markets. The employment of ideas and techniques from complexity science and the proposed theory of coupled and interdependent networks to understand and quantify the role of connections and dependencies within a system and between different ones opens the possibility to manage the complexity, optimize the systems and reduce their vulnerability to failures. More specifically, we investigate the stock-stock correlations in individual markets as local market dynamics, and the correlation of correlations, meta-correlations, which represents global market dynamics. Furthermore, we make use of the recently introduced dependency network methodology, which enables a quantification of the influence relationships between the different markets. The methodologies presented provide the means to track the flow of information between different markets, and can be used to identify changes in correlations in strongly coupled markets. Finally, we will discuss different applications of network science in finance and economics, which demonstrate who one can use empirical financial data to construct a network that represents the financial system, and then use it to study different aspects such as structure, dynamics and stability.

The world has become a global village, and this village is becoming smaller and smaller, with the continuous introduction of ways to interact and connect to other people. Thus, the methodology outlined in this talk will provide new tools and means to quantify, characterize and manage the complexity of the world’s economy. The methodologies presented here can be used as the basis for quantitative early warning tool, a “financial seismograph”, which will provide policy makers the necessary precursors for significant local and global economic events.

Last Updated Date : 17/11/2014