Fierce stock market fluctuation disrupts scalefree distribution

Recently, in the finance discipline, cross correlations of stock price return time series have been increasingly used in the study of the internal structure of stock markets. The data obtained from calculating the cross correlations of stocks’ times series forms a correlation matrix which provides information about the interdependence of the stocks. From a network viewpoint, the stocks form a complex network that describes how the individual stocks are related. Some proposed models for studying stock networks include the Minimal Spanning Tree (MST) (Mantegna 1999), the Planar Maximally Filtered Graph (PMFG) (Tumminello et al. 2005) and the asset graph (Onnela et al. 2004). These structures have proved useful in the study of the static properties of stock markets. In this paper, we employ a network model similar to the asset graph to study the correlation between the time series of stock prices and the time series of stock price returns. Data used in this study are from the Standard and Poor’s 500 (S&P50