Physics (Internal)

Statistically-Validated Networks

This event is part of the Preliminary Oral Exam.

Examining Committee:

Gene Stanley Irena Vodenska Shyam Erramilli Robert Carey

Abstract:

Methods from statistical physics and network science have been applied with varying degrees of success to the study of financial markets. Analyses of correlation-based networks of equity returns have been particularly fruitful. Such studies have revealed a nested structure in financial markets, in which stock returns are organized in groups of like economic activity—such as technology, services, utilities, or energy—that exhibit higher values of average pair correlation. Although much attention has been devoted to the study of synchronous correlation networks, comparatively few results have been obtained for networks of lagged correlations. This is in part because the various methods of constructing synchronous correlation networks do not readily extend to lagged correlation networks. We introduce a numerical method to statistically validate links in correlation-based networks, and employ our method to study lagged correlation networks of equity returns in financial markets. In an analysis of intraday transaction data from the periods 2002--2003 and 2011--2012, we find a striking growth in the networks as we increase the frequency with which we sample returns. We compute how the number of validated links and the magnitude of correlations change with increasing sampling frequency, and compare the results between the two data sets. Finally, we compare topological properties of the directed correlation-based networks from the two periods using the in-degree and out-degree distributions and an analysis of three-node motifs. Our analysis suggests a growth in both the efficiency and instability of financial markets over the past decade.