Search Results for author: Hugo Kooijman

Found 1 papers, 0 papers with code

RCURRENCY: Live Digital Asset Trading Using a Recurrent Neural Network-based Forecasting System

no code implementations13 Jun 2021 Yapeng Jasper Hu, Ralph van Gurp, Ashay Somai, Hugo Kooijman, Jan S. Rellermeyer

Evaluation of the system through backtesting shows that RCURRENCY can be used to successfully not only maintain a stable portfolio of digital assets in a simulated live environment using real historical trading data but even increase the portfolio value over time.

Value prediction

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