amalsebastian7 / network-of-influence-on-the-stock-market-and-its-impact-on-risk-analysis Goto Github PK

The goal of this research is to better understand the relationships between cryptocurrencies and stock indexes, including how cryptocurrencies are interconnected. Preliminary visualization revealed a trend of market movement across all cryptocurrencies, indicating a substantial correlation. Initial analysis focusses on finding the correlation between the stock indexes and cryptocurrencies value returns. Another objective is to study the volatility of the asset value measured by standard deviation of each asset for a short period and to further calculate the correlation between them. In order to express relationships between assets in a pictorial format, graphs are used. The assets are represented by the graph vertices, and the relationships between them are shown by edges in the graph. Further, centrality is crucial in identifying important nodes. Two measures will be considered, Eigen-vector centrality (measuring likelihood of visitation to a node) and betweenness centrality (counting the instance in which counts the instances in which a node acts as a bridge facilitating the quickest and shortest route between two nodes). The tests were carried out on four indexes (three stock indexes and one crypto index) and six well-known cryptocurrencies based on the quantity and accessibility of historical trading data. The results of the research based on the time series of price returns, points to a strong relationship between Ethereum and Bitcoin in cryptocurrencies, but Dow Jones and S&P 500 have the strongest correlation when it comes to stock indices. The moving average of volatility showed that cci30 is highly volatile compared to other stock indexes and all six crypto currencies are highly volatile. The network graph demonstrates the interconnectedness and clustering of the selected cryptocurrency currencies. It’s evident that Bitcoin functions as a central node, which means it has the highest likelihood of appearing on a random path in the graph.