Universiti Teknologi Malaysia Institutional Repository

Network topology of renewable energy companies: minimal spanning tree and sub-dominant ultrametric for the american stock

Kazemilari, Mansooreh and Mohamadi, Ali and Mardani, Abbas and Streimikis, Justas (2019) Network topology of renewable energy companies: minimal spanning tree and sub-dominant ultrametric for the american stock. Technological and Economic Development of Economy, 25 (2). pp. 168-187. ISSN 2029-4913

[img]
Preview
PDF
783kB

Official URL: http://dx.doi.org/10.3846/tede.2019.7686

Abstract

Renewable energy has become a significant market player after the turn of the millen-nium. Wind, solar, smart grid and further renewable energy stocks have experienced both serious up and down trends since that time. In this paper, computed the Minimal Spanning Tree (MST) and Sub-Dominant Ultrametric (SDU) for topological properties of what has been driving the price of renewable energy stock markets and sectors. In this regard, the main object is to define the similarity among sectors in financial market, which is statistically a multivariate time series. The principal mathematical tool to do macro analysis is multivariate vector correlation where multi-dimensional data is considered as a complex system. Furthermore, the base approach for filtering the significant information in a financial system is similarity network analysis. In this paper, the behavior of economic sectors of renewable energy played during 30th July 2015 – 1th January 2018 in America. Results of this study found that, solar sector in renewable energy is confirmed as the dominant sector in America during this period. In addition, results demonstrated that, the leader sector is Solar and the central hubs are Canadian Solar Inc. (CSIQ)from Solar and then Pattern Energy Group Inc. (PEGI)from Solar-Wind sectors.

Item Type:Article
Uncontrolled Keywords:renewable energy, sector analysis, similarity network analysis
Subjects:H Social Sciences > H Social Sciences (General)
H Social Sciences > HF Commerce
H Social Sciences > HG Finance
Divisions:International Business School
ID Code:89240
Deposited By: Yanti Mohd Shah
Deposited On:22 Feb 2021 06:01
Last Modified:22 Feb 2021 06:01

Repository Staff Only: item control page