The Impact of Process and Object Digital Transformation on the Moscow Exchange Index: A Textual Analysis of Patents

The purpose of the study is to assess the association of process and object digital transformation with daily returns of the broad and sectoral Moscow Exchange indices using textual patent analysis. The subject is the short-run response of the Russian stock market to patent-based digital technology indicators. We propose a research method that separates object transformation (material components) from process transformation (management and information technologies). The empirical base contains 850,784 patent records covering the period from 1977 to 2025; the estimates use ARXEGARCH models. Conclusions: The association is heterogeneous across technology blocks and sectors: after multiple-testing correction, robust negative short-run coefficients remain for process indicators in energy and finance. The applied and empirical-methodological novelty of this study is a reproducible patent indicator of object and process digital transformation for the Russian stock market.

1. Tregub I. V., Funtova D. V., Eterskova Ya. S. Economy of the Russian Federation for 2024–2025 and factors of its growth. Ekonomika. Nalogi. Pravo = Economics, Taxes & Law. 2024;17(1):44–55. (In Russ.). DOI: 10.26794/1999849X-2024-17-1-44-55

2. Gospodarchuk G. G., Zeleneva E. S. Consolidation of monetary policy objectives with the goals of financial and economic development. Zhurnal Sibirskogo federal’nogo universiteta. Seriya: Gumanitarnye nauki = Journal of Siberian Federal University. Humanities and Social Sciences. 2025;18(6):1091–1103.

3. Abramova M. A., Dubova S. E., Didenko V.Yu., et al. On the main directions of the unified state monetary policy for 2024 and the period 2025 and 2026: Opinion of experts of the Financial University. Ekonomika. Nalogi. Pravo = Economics, Taxes & Law. 2024;17(1):6–22. (In Russ.). DOI: 10.26794/1999-849X-2024-17-1-6-22

4. Kireeva E. F., Karaev A. K. Government regulation on economic growth and innovation: The effect of public investment in defence R&D. Upravlenets = The Manager. 2025:16(4): 2–18. (In Russ.). DOI: 10.29141/2218-50032025-16-4-1

5. Sakharov D. M. Development of the Russian financial market in the context of the structural transformation of the global financial system. Finance: Theory and Practice. 2025;29(4):49–70. DOI: 10.26794/2587-5671-2025-29-4-49-70

6. Glebova A. G., Kovaleva A. A. Forecasting the volatility of the Russian stock market in the context of international economic sanctions. Finance: Theory and Practice. 2024;28(1):20–29. DOI: 10.26794/2587-5671-2024-28-1-20-29

7. Salnikov M.Yu., Lyskov N. B., Aleksandrova A. V. Methodology for constructing an innovative patent index in the paradigm of state intellectual sovereignty. Vestnik FIPS = Bulletin of Federal Institute of Industrial Property. 2026;5(1):40–51. (In Russ.).

8. Brynjolfsson E., Rock D., Syverson C. The productivity J-curve: How intangibles complement general purpose technologies. American Economic Journal: Macroeconomics. 2021;13(1):333–372. DOI: 10.1257/mac.20180386

9. Kudryavtseva T.Yu., Kozhina K. S. Basic concepts of digitalization. Vestnik Akademii znanii = Bulletin of the Academy of Knowledge. 2021;(44):149–151. (In Russ.). DOI: 10.24412/2304-6139-2022-11228

10. Nambisan S., Lyytinen K., Majchrzak A., Song M. Digital innovation management: Reinventing innovation management research in a digital world. MIS Quarterly. 2017;41(1):223–238. DOI: 10.25300/MISQ/2017/41:1.03

11. Solow R. M. Technical change and the aggregate production function. The Review of Economics and Statistics. 1957;39(3):312–320. DOI: 10.2307/1926047

12. Romer P. M. Endogenous technological change. Journal of Political Economy. 1990:98(5–2): S71-S102. DOI: 10.1086/261725

13. Bresnahan T. F., Trajtenberg M. General purpose technologies: ‘engines of growth’? Journal of Econometrics. 1995;65(1):83–108. DOI: 10.1016/0304-4076(94)01598-t

14. Griliches Z. Patent statistics as economic indicators: A survey. Journal of Economic Literature. 1990;28(4):1661–1707.

15. Kogan L., Papanikolaou D., Seru A., Stoffman N. Technological innovation, resource allocation, and growth. The Quarterly Journal of Economics. 2017;132(2):665–712. DOI: 10.1093/qje/qjw040

16. Hall B. H., Jaffe A. B., Trajtenberg M. Market value and patent citations. RAND Journal of Economics. 2005;36(1):16–38. URL: https://eml.berkeley.edu/~bhhall/papers/HallJaffeTrajtenberg03.pdf

17. Gentzkow M., Kelly B., Taddy M. Text as data. Journal of Economic Literature. 2019;57(3):535–574. DOI: 10.1257/jel.20181020

18. Antweiler W., Frank M. Z. Is all that talk just noise? The information content of Internet stock message boards. The Journal of Finance. 2004;59(3):1259–1294. DOI:10.1111/j.1540-6261.2004.00662.x

19. Baker S. R., Bloom N., Davis S. J. Measuring economic policy uncertainty. The Quarterly Journal of Economics. 2016;131(4):1593–1636. DOI: 10.1093/qje/qjw024

20. Kelly B., Papanikolaou D., Seru A., Taddy M. Measuring technological innovation over the long run. American Economic Review: Insights. 2021;3(3):303–320. DOI: 10.1257/aeri.20190499

21. Goldfarb A., Tucker C. Digital economics. Journal of Economic Literature. 2019;57(1):3–43. DOI: 10.1257/jel.20171452