Correlation Financial Networks of an Unstable Stock Market: Empirical Study

Sidorov, Sergei Faizliev, Alexey Balash, Vladimir Melnichuk, Dmitriy Grigoriev, AlexeyCorrelation networks are a popular way to display financial information due to their simplicity and ease of interpretation. However, the assets returns for two companies that share a common cause may be spuriously correlated. To avoid this, it is suggested to use a partial correlation. This paper is devoted to the analysis of the dynamics of the Pearson correlation network and the partial correlation network based on the Russian stock market asset returns and their comparison. The Russian financial market was chosen as the object of study in our work for the following reason: from 2012 to 2022, the Russian economic system was affected by numerous negative factors and shocks (while during this period the economies of most other countries showed stable growth after the 2008 crisis). The main research question of this paper is as follows: do the behavior patterns of market networks for fairly stable financial systems differ from the behavior patterns of networks for volatile systems that are experiencing multiple shocks?