Analysis of the Dynamics of Market Graph Characteristics
Alexey Faizliev, Vladimir Balash, Andrey Vlasov, Tatiana Tryapkina, Sergei Mironov, Ivan Androsov, Vladimir Petrov
Available Online February 2019.
- https://doi.org/10.2991/cmdm-18.2019.3How to use a DOI?
- network analysis, market graph, degree distribution, maximum clique
- In recent years the network models have been successfully employed for the analysis of the stock market. The network model of the stock market is defined as a full weighted graph, which vertices correspond to the returns of market assets, and the weights of the edges are determined by the measure of its interdependencies. To obtain important information from the network model, many researches extract subgraphs, which are called network structures. One of the most popular network structures is the so called market graph. In this paper the market graph is constructed as follows: each company is a node and the value of sign correlation between assets of the two stocks establishes a link between them. Network analysis is carried out for the companies whose shares are traded on the NYSE and NASDAQ for the period from November 22, 2013 to November 10, 2017. It was shown that distribution of degrees and clustering coefficient for our network follows the power law.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Alexey Faizliev AU - Vladimir Balash AU - Andrey Vlasov AU - Tatiana Tryapkina AU - Sergei Mironov AU - Ivan Androsov AU - Vladimir Petrov PY - 2019/02 DA - 2019/02 TI - Analysis of the Dynamics of Market Graph Characteristics BT - Third Workshop on Computer Modelling in Decision Making (CMDM 2018) PB - Atlantis Press SP - 13 EP - 19 SN - 2352-538X UR - https://doi.org/10.2991/cmdm-18.2019.3 DO - https://doi.org/10.2991/cmdm-18.2019.3 ID - Faizliev2019/02 ER -