ResearchBib Share Your Research, Maximize Your Social Impacts
Sign for Notice Everyday Sign up >> Login

THE BALTIC COUNTRIES: BUSINESS STRATEGY RECOGNITION

Journal: International scientific journal "Internauka." Series: "Economic Sciences" (Vol.1, No. 76)

Publication Date:

Authors : ; ;

Page : 194-202

Keywords : portfolio optimization; neural network; prediction model;

Source : Downloadexternal Find it from : Google Scholarexternal

Abstract

The article is devoted to business strategy recognition in the Baltic states. The small Baltic countries (Lithuania, Latvia, and Estonia) very quickly returned to the market economy system. A manifestation of such unification is, in particular, the predominance of modern industries in the optimal portfolios of these markets. At the same time, the markets retain the traditional commitment of the Baltic countries to certain industries, such as the banking sector and farming. The impact of the pandemic and the war unleashed by Russia in Europe had a significant, but not long-lasting, impact on these countries. This can be observed in the basic dynamics of investment growth and risk over the last four years. Three separate portfolios are created based on the next indices ingredients: Vilnius SE General for Lithuania, Riga General for Latvia, and Tallinn SE General for Estonia. A joint portfolio from the participants of individual portfolios with non-zero weights is built. Based on the weighting coefficients of this portfolio, the proximity of the Baltic markets to developed markets is analysed. Also their level of competition or diversification is determined in the article. The presence or absence of a long -term strategy on the basis of the 5-factor model of Fama-French is revealed. As the analysis based on Fama-French model and the approach using neural networks showed, only for half of the participants in the optimal portfolio of the region the mentioned crisis phenomena did an impact on the companies' strategies. A modification of the approach based on neural networks used in this study is an attempt to simulate a crisis in the market by adding a hidden layer with an increased number of neurons (factors) as a sign of a crisis in the market.

Last modified: 2023-12-19 03:34:15