<abstract xmlns="http://www.w3.org/1999/xhtml"><bold>Research purpose.</bold> Stocks as well as other securities are a crucial part of the financial market that helps to redistribute financial resources amongst market participants, which in a modern economy include not only professional stock players but also many common individuals seeking to increase their capital. Previous studies found a strong relationship between the macroeconomic variables and stock returns but often the explanatory power of those models seems to be limited in the applicable region. The aim of this article is to establish whether each region’s stock indices have to be predicted based on a separate set of variables.<bold>Design / Methodology / Approach.</bold> The article uses correlation–regression analysis method to confirm the initial hypothesis regarding regional limitations of such prediction models.<bold>Findings.</bold> The same set of independent variables cannot be directly applied to different regions because although the chosen Y2B model did provide an accurate relationship between macroeconomic variables and stock indices in the United Kingdom, it failed to provide accurate (usable) results in other regions (Estonia, European Union, France, Germany, Latvia and Lithuania),<bold>Originality / Value / Practical implications.</bold> The results are important in order to define the way that the smaller and less-researched economies should be examined because detailed researches of power economies such as the United States, the United Kingdom, China or Germany often cannot be directly applied outside the initial research region. Therefore, the need of separate studies for smaller regions such as Baltic States is confirmed.</abstract>

Research purpose. Stocks as well as other securities are a crucial part of the financial market that helps to redistribute financial resources amongst market participants, which in a modern economy include not only professional stock players but also many common individuals seeking to increase their capital. Previous studies found a strong relationship between the macroeconomic variables and stock returns but often the explanatory power of those models seems to be limited in the applicable region. The aim of this article is to establish whether each region’s stock indices have to be predicted based on a separate set of variables.Design / Methodology / Approach. The article uses correlation–regression analysis method to confirm the initial hypothesis regarding regional limitations of such prediction models.Findings. The same set of independent variables cannot be directly applied to different regions because although the chosen Y2B model did provide an accurate relationship between macroeconomic variables and stock indices in the United Kingdom, it failed to provide accurate (usable) results in other regions (Estonia, European Union, France, Germany, Latvia and Lithuania),Originality / Value / Practical implications. The results are important in order to define the way that the smaller and less-researched economies should be examined because detailed researches of power economies such as the United States, the United Kingdom, China or Germany often cannot be directly applied outside the initial research region. Therefore, the need of separate studies for smaller regions such as Baltic States is confirmed.

Regional Limitations of Stock Indices Prediction Models Based on Macroeconomic Variables

Department of Financial Engineering, Faculty of Business Management

Economics and Culture

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Research purpose. Stocks as well as other securities are a crucial part of the financial market that helps to redistribute financial resources amongst market...

Regional Limitations of Stock Indices Prediction Models Based on Macroeconomic Variables

Data publikacji: 30 gru 2019

Zakres stron: 5 - 20

DOI: https://doi.org/10.2478/jec-2019-0018

Słowa kluczowe
stock indices, macroeconomic variables, prediction, relationship, correlation – regression analysis

© 2019 Tomas Sovijus Kvainickas et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Regional Limitations of Stock Indices Prediction Models Based on Macroeconomic Variables

Data publikacji: 30 gru 2019

Zakres stron: 5 - 20

DOI: https://doi.org/10.2478/jec-2019-0018

Słowa kluczowestock indices, macroeconomic variables, prediction, relationship, correlation – regression analysis

© 2019 Tomas Sovijus Kvainickas et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Słowa kluczowe
stock indices, macroeconomic variables, prediction, relationship, correlation – regression analysis