SCN-Conformal prediction-based bitcoin forecasting method for enhancing reliability

Abstract

Bitcoin is the world's first decentralized cryptocurrency, using blockchain technology to secure and verify transactions. A hybrid model based on stochastic configuration network (SCN) with conformal prediction is proposed in this study. Initially, an SCN model is built, and predictions are generated by the model. Subsequently, the predicted values from SCN are fed into the conformal prediction model, resulting in the generation of confidence intervals that validate the reliability of these values. Finally, the dataset of historical Bitcoin prices sourced from Wikipedia have been utilized. The results indicate that the SCN-conformal prediction combination enhances prediction reliability.