The impact of digitalization on the capitalization of Russian public companies

Vollständiger Abstract

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Subject. The impact of digitalization on the market capitalization of the largest Russian public companies in 2022–2024 in the context of sanctions pressure. Objectives. Empirical analysis of the impact of digitalization on the market capitalization of the largest Russian public companies in 2022–2024 using machine learning and clustering methods, analysis based on SHAP modeling. Methods. The research methodology includes k-means cluster analysis based on three criteria (the effect of digitalization, market capitalization, and the share of import-substituted software) with the determination of the optimal number of clusters using the elbow method, the construction of an integral digitalization index based on min-max normalization of private indicators, and the evaluation of a machine learning model – a random forest – to identify market dependence. capitalization depends on digital and fundamental financial indicators. For a meaningful interpretation of nonlinear effects, the SHAP method is used, which makes it possible to estimate the relative contribution of each factor to the explanation of market valuation. The empirical base of the study includes data from 29 of the largest Russian public companies for 2022-2024 (87 observations "company – year"). Results. Based on the random forest model, the dependence of market capitalization on digital and fundamental financial indicators has been revealed. Digital indicators – the share of software import substitution, the absolute effect of digitalization, and R&D costs – play an important role in shaping market valuation, especially through non-linear threshold effects. Conclusions. 4The results obtained are interpreted in terms of the costs of the transition phase of digital transformation and the dual channel of digitalization's influence on market valuation – direct signaling through individual digital indicators (primarily software import substitution).