| Title |
Atsinaujinančių energijos išteklių akcijų indeksų ryšys su ekonominiais rodikliais / |
| Translation of Title |
Relationship between renewable energy stock indices and economic indicators. |
| Authors |
Praniauskaitė, Monika |
| Full Text |
|
| Pages |
66 |
| Keywords [eng] |
renewable energy stock price ; Granger causality ; US ; gross domestic product ; producer price index |
| Abstract [eng] |
The aim of this final project is to investigate the relationship between renewable energy stock indices and selected country’s economic indicators. In the fist chapter discusses the review of the literature which is related with the final project. In this chapter are discussed what methods have been used in researches and what results have been obtained. The second chapter presents the calculation methods chosen in the final project and at the end of this chapter presents the data witch was used in project. The United States Economic Indicators - Gross Domestic Product (GDP) and Industrial Price Index (PPI) were selected for the research. The renewable energy stock indices „S&P Global Clean Energy“ and „Nasdaq Clean Edge Green Energy“ were selected in this final project. The third chapter presents the results of the study and the conclusions. A confidence level of α = 0.05 was used to determine the relationship between the mentioned variables. Method GARCH (1, 1) was used to look and investigate the volatility of stock indices. Granger causality methods were used to investigate the relationship. The confidence level was compared with the p-values of the F-test. The first method was linear (classical) Granger causality according to VAR. The calculations showed a reciprocal relationship with both economic indicators affecting renewable energy stock indices and the indices themselves affecting economic indicators. The results of the second method, Granger causality according to TYDL were slightly different. Reciprocal relationships were obtained with the economic indicator, but relationship with PPI were only one-sided. In other words, the economic indicator PPI has a causal relationship with renewable energy stock indices. However, stock indices do not affect the industrial price index. The third method tested in this project was the nonlinear causality of Granger using artificial neural networks. The results obtained are completely opposite to those obtained by investigating the relationship in a linear method. |
| Dissertation Institution |
Kauno technologijos universitetas. |
| Type |
Master thesis |
| Language |
Lithuanian |
| Publication date |
2022 |
