Unveiling the directional network behind the financial statements data using volatility constraint correlation.

Financial data, such as financial statements, stores valuable and critical information to potentially assist stakeholders and investors optimize their capital so that it maximizes overall economic growth. Since there are many variables in financial statements, it is important to determine the causal relationships, that is, the directional influence between them in a structural way, as well as to understand the related accounting mechanisms. However, the analysis of variable-to-variable relationships in financial information by using the standard correlation functions is not sufficient to unveil directionality. Here, we use the volatility constrained correlation (VC correlation) method that enables us to predict the directional relationship between the two variables. To be precise, we apply the VC correlation method to five major financial information variables (revenue, net income, operating income, own capital and market capitalization) of 2321 firms in 28 years from 1990 to 2018 listed on Tokyo Stock Exchange in order to identify which variables are influential and which are susceptible variables. Our findings show that operating income is the most influential variable and market capital and revenue are the most susceptible variables among the five major accounting variables. Surprisingly, the results are different from the existing intuitive understanding suggested by widely used investment strategy indicators known as PER and PBR, which report that net income and own capital are the most influential variable on market capital. Taken together, the presented analysis may assist managers, stakeholders and investors to improve performance of financial management as well as optimize financial strategies for firms in future operations.