STOCK MARKET NETWORK ANALYSIS USING MINIMUM SPANNING TREE

Network can describe interaction between stock markets. Stock market network can be constructed by minimum spanning tree and based on correlation among stock markets. Using return data of 39 stock indices, stock market network is determined in three time periods: before, during, and after global fin...

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Main Author: MIHDA HAYATI (NIM: 10113067), MILLATI
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/23076
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:23076
spelling id-itb.:230762017-11-20T11:26:03ZSTOCK MARKET NETWORK ANALYSIS USING MINIMUM SPANNING TREE MIHDA HAYATI (NIM: 10113067), MILLATI Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/23076 Network can describe interaction between stock markets. Stock market network can be constructed by minimum spanning tree and based on correlation among stock markets. Using return data of 39 stock indices, stock market network is determined in three time periods: before, during, and after global financial crisis 2008. Dynamic changes in network can be seen by centrality scores of each stock indices. There are three centrality measures that are used in this final project. They are degree, betweenness, and closeness centrality. Changes in stock market network explain that there is significant variation of correlation among stock markets through time. Therefore, modeling correlation is important thing to help investors understanding behaviour of stock markets correlation in network. In this final project, <br /> <br /> correlation between stock indices is predicted using DCC GARCH model. DCC GARCH model is applied to data with assumption Gaussian distribution errors. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Network can describe interaction between stock markets. Stock market network can be constructed by minimum spanning tree and based on correlation among stock markets. Using return data of 39 stock indices, stock market network is determined in three time periods: before, during, and after global financial crisis 2008. Dynamic changes in network can be seen by centrality scores of each stock indices. There are three centrality measures that are used in this final project. They are degree, betweenness, and closeness centrality. Changes in stock market network explain that there is significant variation of correlation among stock markets through time. Therefore, modeling correlation is important thing to help investors understanding behaviour of stock markets correlation in network. In this final project, <br /> <br /> correlation between stock indices is predicted using DCC GARCH model. DCC GARCH model is applied to data with assumption Gaussian distribution errors.
format Final Project
author MIHDA HAYATI (NIM: 10113067), MILLATI
spellingShingle MIHDA HAYATI (NIM: 10113067), MILLATI
STOCK MARKET NETWORK ANALYSIS USING MINIMUM SPANNING TREE
author_facet MIHDA HAYATI (NIM: 10113067), MILLATI
author_sort MIHDA HAYATI (NIM: 10113067), MILLATI
title STOCK MARKET NETWORK ANALYSIS USING MINIMUM SPANNING TREE
title_short STOCK MARKET NETWORK ANALYSIS USING MINIMUM SPANNING TREE
title_full STOCK MARKET NETWORK ANALYSIS USING MINIMUM SPANNING TREE
title_fullStr STOCK MARKET NETWORK ANALYSIS USING MINIMUM SPANNING TREE
title_full_unstemmed STOCK MARKET NETWORK ANALYSIS USING MINIMUM SPANNING TREE
title_sort stock market network analysis using minimum spanning tree
url https://digilib.itb.ac.id/gdl/view/23076
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