Boosting Bitcoin Minute Trend Prediction Using the Separation Index

TL;DR

This paper introduces the Separation Index, a novel metric for selecting informative features to improve minute-scale Bitcoin trend prediction, resulting in significantly enhanced accuracy for high-frequency trading applications.

Contribution

The study presents the Separation Index as an innovative tool for efficient feature selection, leading to improved Bitcoin trend prediction accuracy over existing methods.

Findings

Achieved unprecedented accuracy in Bitcoin minute trend prediction.

Demonstrated the effectiveness of the Separation Index for feature selection.

Surpassed previous performance benchmarks in cryptocurrency forecasting.

Abstract

Predicting the trend of Bitcoin, a highly volatile cryptocurrency, remains a challenging task. Accurate forecasting holds immense potential for investors and market participants dealing with High Frequency Trading systems. The purpose of this study is to demonstrate the significance of using a systematic approach toward selecting informative observations for enhancing Bitcoin minute trend prediction. While a multitude of data collection methods exist, a crucial barrier remains: efficiently selecting the most informative data for building powerful prediction models. This study tackles this challenge head-on by introducing the Separation Index, a groundbreaking tool for fast and effective data (feature) subset selection. The Separation Index operates by measuring the improvement in class separability (i.e. upward vs. downward trends) with each added feature set. This innovative metric guides the creation of a highly informative dataset, maximizing the model's ability to differentiate between price movements. Our research demonstrates the effectiveness of this approach, achieving unprecedented accuracy in minute-scale Bitcoin trend prediction, surpassing the performance of previous studies. This significant advancement paves the way for a new era of data-driven decision-making in the dynamic world of cryptocurrency markets.