Based upon the recent work of Dacheng Xiu's team at the University of Chicago, we demonstrate that we can repurpose a consumer-level character recognition neural network to recognize price chart patterns in the Ethereum cryptocurrency for the purpose of forecasting short term (small N days)...

By defining a back-test residual for an empirical short-term drift-diffusion model, we are able to use a distribution of these residuals from long term historical back-tests to adjust or correct the drift and diffusion parameters of the short-term model for improved back-tests. In other words,...

Crypto currency perpetual futures asset price changes seem to have some predictive power for short term (tens of minutes) forecasts of underlying crypto currency price changes. In this study, we apply simple vector auto-regressive models to Bitcoin spot and futures price changes and allow for a...