In this project, we are interested in addressing the following questions:
1- What is the underlying distribution of the token (Network) data?
2- How to split data based on the TokenAmount to some layers and to find a feature which has a corrolation to the Closing Price?
3- Proposing some features to find a regression model to pridict the future (time t+1) price of the token.
In this study, we focused on the "OMISEGO" token. First, we found outliers data based on the "tokenAmount". After excluding them from the data, we used two Network data and Graph data for furthure processing.
Each code addresses the related above questions.