An Empirical Study of Macroeconomic Factors and Stock Returns in the Context of Economic Uncertainty News Sentiment Using Machine Learning
Stock markets accurately reflect countries’ economic health, and stock returns are tightly related to economic indices. One popular area of financial research is the factors that influence stock returns. Several investigations have frequently cited macroeconomic factors, among numerous elements. The...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/4646733 |
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| author | Ayesha Jabeen Muhammad Yasir Yasmeen Ansari Sadaf Yasmin Jihoon Moon Seungmin Rho |
| author_facet | Ayesha Jabeen Muhammad Yasir Yasmeen Ansari Sadaf Yasmin Jihoon Moon Seungmin Rho |
| author_sort | Ayesha Jabeen |
| collection | DOAJ |
| description | Stock markets accurately reflect countries’ economic health, and stock returns are tightly related to economic indices. One popular area of financial research is the factors that influence stock returns. Several investigations have frequently cited macroeconomic factors, among numerous elements. Therefore, this study focuses on the empirical analysis of the relationship between macroeconomic factors and stock market returns. When a stock market becomes increasingly volatile, it becomes susceptible to economic uncertainty news, and information on social media platforms. Thus, we incorporated a new dimension of economic uncertainty news sentiment (EUNS) for stock return predictions. We employed the daily data ofgold index, crude oil price, interest rate, exchange rate, and stock returns for a set of countries from January 2010 to December 2020. Subsequently, to compute coefficients, we conducted a regression analysis using one of the more sophisticated approaches: single-layer neural networks and ordinary least square regression. In addition, we only computed EUNS for the period of the fiscal budget announcement for the US, Turkey, and Hong Kong. The results indicate that the gold index, interest rate, and exchange rate are highly significant and negative macroeconomic factors for all analyzed countries. These findings also indicate that EUNS is important and detrimental for projecting stock returns. |
| format | Article |
| id | doaj-art-3821335884ca4e93982c9db275326e1b |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-3821335884ca4e93982c9db275326e1b2025-02-03T05:50:39ZengWileyComplexity1099-05262022-01-01202210.1155/2022/4646733An Empirical Study of Macroeconomic Factors and Stock Returns in the Context of Economic Uncertainty News Sentiment Using Machine LearningAyesha Jabeen0Muhammad Yasir1Yasmeen Ansari2Sadaf Yasmin3Jihoon Moon4Seungmin Rho5Department of Computer ScienceFAST School of ManagementDepartment of FinanceDepartment of Computer ScienceDepartment of Industrial SecurityDepartment of Industrial SecurityStock markets accurately reflect countries’ economic health, and stock returns are tightly related to economic indices. One popular area of financial research is the factors that influence stock returns. Several investigations have frequently cited macroeconomic factors, among numerous elements. Therefore, this study focuses on the empirical analysis of the relationship between macroeconomic factors and stock market returns. When a stock market becomes increasingly volatile, it becomes susceptible to economic uncertainty news, and information on social media platforms. Thus, we incorporated a new dimension of economic uncertainty news sentiment (EUNS) for stock return predictions. We employed the daily data ofgold index, crude oil price, interest rate, exchange rate, and stock returns for a set of countries from January 2010 to December 2020. Subsequently, to compute coefficients, we conducted a regression analysis using one of the more sophisticated approaches: single-layer neural networks and ordinary least square regression. In addition, we only computed EUNS for the period of the fiscal budget announcement for the US, Turkey, and Hong Kong. The results indicate that the gold index, interest rate, and exchange rate are highly significant and negative macroeconomic factors for all analyzed countries. These findings also indicate that EUNS is important and detrimental for projecting stock returns.http://dx.doi.org/10.1155/2022/4646733 |
| spellingShingle | Ayesha Jabeen Muhammad Yasir Yasmeen Ansari Sadaf Yasmin Jihoon Moon Seungmin Rho An Empirical Study of Macroeconomic Factors and Stock Returns in the Context of Economic Uncertainty News Sentiment Using Machine Learning Complexity |
| title | An Empirical Study of Macroeconomic Factors and Stock Returns in the Context of Economic Uncertainty News Sentiment Using Machine Learning |
| title_full | An Empirical Study of Macroeconomic Factors and Stock Returns in the Context of Economic Uncertainty News Sentiment Using Machine Learning |
| title_fullStr | An Empirical Study of Macroeconomic Factors and Stock Returns in the Context of Economic Uncertainty News Sentiment Using Machine Learning |
| title_full_unstemmed | An Empirical Study of Macroeconomic Factors and Stock Returns in the Context of Economic Uncertainty News Sentiment Using Machine Learning |
| title_short | An Empirical Study of Macroeconomic Factors and Stock Returns in the Context of Economic Uncertainty News Sentiment Using Machine Learning |
| title_sort | empirical study of macroeconomic factors and stock returns in the context of economic uncertainty news sentiment using machine learning |
| url | http://dx.doi.org/10.1155/2022/4646733 |
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