Tools for Assessing the Potential Aggressiveness of Energy Companies' Market Strategies by Using Selective Indicators from Their Financial Statements

One of the consequences of the negative impact of political turbulence in the energy sector and on the global hydrocarbon market is changes in established strategies and behavior of participants, including the desire for inorganic growth at the expense of competitors. This highlights the urgency of revising indicators and applied predictive models for identifying market threats. The purpose of the study is to create a toolkit for assessing the aggressiveness potential of a company's market strategy (an applied indicative model of market threats) based on selective indicators of corporate financial reporting. The hypothesis assumes that the potential for aggressiveness of a company's market strategy is characterized by the values of a stable set of reporting indicators, the targeted change of which affects the assessment of the potential ability and readiness of a business to act as a source of market threats. The methodological framework includes regression and multivariate analysis using nonparametric testing, including single-factor analysis of variance (ANOVA) by rank. Based on the results of testing the empirical model based on primary data collected by the author from 20 leading public companies in the energy sector of four economies, reporting indicators with confirmed indicative properties were identified. The results obtained indicate that for a reliable gradation of participants in the market environment according to the degree of their potential danger to other companies, three reporting indicators are sufficient: the intensity of use of fixed assets, market activity and the enterprise value. The indicative model of market threats formed on their basis has been successfully tested. The results of the study equip managers with a stable set of reporting indicators, determined by the study of potential aggressiveness indicators of the company's market strategy; the proposed methodological approaches have the ability to adapt to solving the problems of increasing the stability and efficiency of corporate risk management systems without significant additional costs and can be used in the future for developing machine learning protocols. In addition, the results of this study may be useful for analysts and auditors when evaluating corporate market strategies and market risk management systems.