COMPLEX NETWORK ANALYSIS OF SECTORAL STOCKS ON INDONESIA’S GROSS DOMESTIC PRODUCT IN 2011-2020 USING THE MST AND RMT+MST METHOD

• Main Author: Zelin, Febrina
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/49127
• Institution: Institut Teknologi Bandung

developing countries. It can analyze the economic development of a country from year to year. GDP can be interpreted as the number of products and services produced by a country during a certain period of time. Meanwhile, stock price index can represent existing market conditions In this final project, the results of sectoral stock studies and how they relate to Indonesia's GDP will be presented. The method used is Minimum Spanning Tree (MST) method and combination of Random Matrix Theory + Minimum Spanning Tree (RMT + MST). RMT is used as noise filtering while MST is a type of network that is formed from sectoral stock price data. The results showed that the network topology formed for sectoral stock data in 2011-2020 was quite in line with the state of Indonesia's GDP. In addition a quantitative analysis is carried out, called centrality. This centrality analysis is used to determine which sectors have the dominant influence in the network formed. The use of the MST method results in an alignment of 73%. Whereas the combination of the RMT + MST method only 64%. The difference results between the two methods is composition of the network topology and their centrality.