Working on statistical analysis to find inherent market structure of cryptospace

Undirected graph G = (V,E) is defined by sets of V vertices and E edges, E belongs to .
Graph theortical extension can be seen in world wide web , call graph in telecommunications traffic , metabolic in biology and social network where real people represent vertices, Hence graph theory is applied branch of science.
All diverse graph follows power-law model which states that probability that a vertex of graph emanating k edges is

one can also say like this,

Distribution would form a straight line in the logarithmic scale, and slope of the line would be equal to parameter . Degree of distribution is an important aspect of dataset and reflects large scale pattern of connections in graph. Another common observation two vertices are more likely to be connected if they have a common neighbour which is clustering coefficient.
We study the characteristics of graph representing cryptocurrency market. It is based on cross-correlations of price fluctuations. The market graph is constructed as following
Each financial instrument (ie crypto instrument) is represented as financial instrument by a vertex and two vertices are connected by and edge if the correlation coefficient of instruments exceeds a certain threshold .
We also look for cliques and independent sets in the graph. A clique in a graph is a set of interconnected vertices. An independent set of is a set of vertices without connections.
Cliques would represent dense clusters of similar objects. On the other side independent sets can be treated as groups of objects that differ from every other objects in the group.
A clique in market graph with positive value of the of the correlation threshold , whose price fluctuations exhibit similar behaviour. Hence daily price changes can be classified using above.
An independent set in the market graph with threshold consists of diversified portfolio which are negatively correlated.
Construction and analysis on the market graph
The market graph considered represents the set of 100 of cryptocurrency market instruments traded globally. We analyse data fluctuations of their prices during 365 consecutive trading days in 2016-2017.

I am interested in help if some would like to co-author with me , This is not a school or college project.

I am not funded either.

I am doing it because I just want to understand market better.

Thanks let me know.