  Financial data, such as financial statements, contain valuable and critical
information that may assist stakeholders and investors in optimizing their
capital to maximize overall economic growth. Since there are many variables in
financial statements, it is crucial to determine the causal relationships, that
is, the directional influence between them in a structural way, as well as to
understand the associated accounting mechanisms. However, the analysis of
variable-to-variable relationships in financial information using standard
correlation functions is not sufficient to unveil directionality. Here, we use
the volatility constrained correlation (VC correlation) method to predict the
directional relationship between two arbitrary variables. We apply the VC
correlation method to five significant financial information variables
(revenue, net income, operating income, own capital, and market capitalization)
of 2321 firms listed on the Tokyo Stock Exchange over 28 years from 1990 to
2018. This study identifies which accounting variables are influential and
which are susceptible. Our findings show that operating income is the most
influential variable while market capitalization and revenue are the most
susceptible variables. Surprisingly, the results differ from the existing
intuitive understanding suggested by widely used investment strategy
indicators, the price--earnings ratio and the price-to-book ratio, which report
that net income and own capital are the most influential variables affecting
market capitalization. This analysis may assist managers, stakeholders, and
investors to improve financial management performance and optimize firms'
financial strategies in future operations.
