Abstract

The stock market is an essential part of the country's financial system and a key tool for redistribution of funds between economic entities. In countries with high levels of well-being, it is what largely determines the dynamics of the national stock market. Stock markets of today are undergoing digital transformation. The introduction of digital technologies requires switching to fundamentally new methods and models of decision-making in the stock market, as well as mastering digital trading skills, which is extremely difficult for most private investors. To meet these challenges, we propose to move to training private investors in the investment companies through which they trade, as well as to develop an interactive methodology that allows private investors to increase the profitability of their portfolios in the Russian stock market. The proposed methodology is based on the use of artificial neural networks and autoregression, taking into account the value of the beta coefficient and the seasonal nature of stock market dynamics. During testing, we examined four types of portfolios, allowing to take into account different strategies of private investor trading in the stock market. According to the results of the test, all portfolios yielded a positive return, the average annual return exceeds the profitability of bank deposits, which indicates the feasibility of using the proposed method for teaching private investors with a low level of digital literacy. The proposed approach will help to increase the attractiveness of stock trading for individuals, boost the share of private investors in the stock market, develop digital trading skills among private investors and further their financial literacy in the face of the digital transformation of the stock market.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call