Publication
Reframing the S&P 500 network of stocks along the 21st century
| Summary: | Based on a sample of 296 stocks from the S&P 500, the time-varying network structure within three distinct two-year periods since the beginning of the 21st century was analyzed. Logged first-differences of daily stock prices serve as input for a correlation based distance measure between any two of the 296 stocks. The computation of a Minimal Spanning Tree then abstracts from a complete network and allows for a topological analysis of the resulting community structure. Both the Great Recession (2007–2008) and the Global Commodity Crisis (2010–2011) reveal tendencies of enhanced community formation compared to a formerly rather randomized network structure. Nevertheless, the drivers of the resulting clustering are found not to be related to industry sector affiliation. |
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| Main Authors: | Araújo, Tanya |
| Other Authors: | Göbel, Maximilian |
| Subject: | S&P 500 Network Analysis Minimal Spanning Trees Minimal Spanning Trees Industrial Clusters Great Recession Global Commodity Crisis Community Detection |
| Year: | 2019 |
| Country: | Portugal |
| Document type: | article |
| Access type: | open access |
| Associated institution: | Universidade de Lisboa |
| Language: | English |
| Origin: | Repositório da Universidade de Lisboa |
| Summary: | Based on a sample of 296 stocks from the S&P 500, the time-varying network structure within three distinct two-year periods since the beginning of the 21st century was analyzed. Logged first-differences of daily stock prices serve as input for a correlation based distance measure between any two of the 296 stocks. The computation of a Minimal Spanning Tree then abstracts from a complete network and allows for a topological analysis of the resulting community structure. Both the Great Recession (2007–2008) and the Global Commodity Crisis (2010–2011) reveal tendencies of enhanced community formation compared to a formerly rather randomized network structure. Nevertheless, the drivers of the resulting clustering are found not to be related to industry sector affiliation. |
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