UDC: 311
https://doi.org/10.25198/2077-7175-2019-5-39
APPLICATION OF METHODS OF STATISTICAL ANALYSIS OF NETWORK STRUCTURES TO STUDY THE DYNAMICS OF MARKET GRAPHS AND GRAPHS OF JOINT REFERENCES
V.А.Balash,1S.P.Sidorov,2Al.R.Faizliev3
Saratov State University, Russian Federation
1e-mail: vladimirbalash@yandex.ru;
2e-mail: sidorovsp@yahoo.com;
3e-mail: faizlievar1983@mail.ru
Abstract. The aim of the paper is to provide an analysis of news and financial data using their network representation. This article discusses the application of methods for analyzing network structures to study the dynamics of market graphs and graphs of joint references. The objectives of our study were, firstly, to analyze the temporal changes in the properties of the graphs of two parallel processes, and secondly, the similarities or differences in their dynamics, and thirdly, how the analysis results are stable relative to the choice of graph similarity metrics. We assume that the impact of the entire set of hidden, unobservable factors affecting pricing processes in financial markets should be reflected in changes in the structural properties of the so-called market graphs and graphs of joint mentions of companies in the news flow. The market graph describes a network of interactions between asset returns, whose vertices are companies whose shares are listed on exchanges connected by edges, if the indicator of the tightness of the relationship between stock returns over the selected period exceeds the selected threshold in absolute value. We calculated the number of co-mentions of each pair of companies and formed the corresponding adjacency matrices of co-mention graphs.
In order to analyze the variability of network structures over time, two methods were used to calculate the graphs similarity (nodes similarity based metric and network topology similarity based metric). The results of applying multidimensional scaling methods for dynamic graph lead to the conclusion that the one-factor model is able to explain a significant part of the dynamics of changes in the structure of graphs. Also QAP correlation and regression analysis were used to examine graphs similarity.
Keywords: network structures, statistical analysis of the dynamics of network structures, graph properties, social networks, market graph, graph similarity measures.
