Blockchain Analytics for Intraday Financial Risk Modeling
25 Pages Posted: 19 Jan 2019
Date Written: January 9, 2019
Blockchain offers the opportunity to use the transaction graph for financial governance, yet properties of this graph are understudied. One key question in this direction is the extent to which the transaction graph can serve as an early-warning indicator for large financial losses.
In this article, we demonstrate the impact of extreme transaction graph activity on the intraday volatility of the Bitcoin prices series. Specifically, we identify certain sub-graphs ('chainlets') that exhibit predictive influence on Bitcoin price and volatility and characterize the types of chainlets that signify extreme losses. Using bars ranging from 15 minutes up to a day, we fit GARCH models with and without the extreme chainlets and show that the former exhibit superior Value-at-Risk backtesting performance.
Keywords: Cryptocurrencies, Graph Analysis, Forecasting, Financial Risk, ICOs
JEL Classification: C58, C63, G18
Suggested Citation: Suggested Citation