融合情绪与技术指标，用机器学习预测比特币走势
Using Sentiment and Technical Analysis to Predict Bitcoin with Machine Learning
- 结合恐惧贪婪指数与技术分析指标，构建预测模型
- 实验表明投资回报优于买入持有策略
- 适合关注加密货币量化交易的研究者与投资者
近年来，由于去中心化特性及金融创新潜力，加密货币受到广泛关注，准确预测其价格成为投资者、交易员和研究人员的重要课题。已有研究显示比特币市场情绪与其价格波动存在关联，但将市场情绪与金融技术分析指标结合用于预测比特币价格的论文仍较少。本文提出一种新方法，通过融合恐惧与贪婪指数（衡量市场情绪）、技术分析指标以及机器学习算法，实现比特币价格走势预测。本研究为情感指标在加密货币预测中的重要性提供了初步实证支持。初步实验结果表明，该模型在投资回报方面优于买入持有基准策略，并为情绪与市场指标结合在加密货币预测中的应用提供了有价值洞见。
原文摘要 · Abstract (English)
Cryptocurrencies have gained significant attention in recent years due to their decentralized nature and potential for financial innovation. Thus, the ability to accurately predict its price has become a subject of great interest for investors, traders, and researchers. Some works in the literature show how Bitcoin's market sentiment correlates with its price fluctuations in the market. However, papers that consider the sentiment of the market associated with financial Technical Analysis indicators in order to predict Bitcoin's price are still scarce. In this paper, we present a novel approach for predicting Bitcoin price movements by combining the Fear & Greedy Index, a measure of market sentiment, Technical Analysis indicators, and the potential of Machine Learning algorithms. This work represents a preliminary study on the importance of sentiment metrics in cryptocurrency forecasting. Our initial experiments demonstrate promising results considering investment returns, surpassing the Buy & Hold baseline, and offering valuable insights about the combination of indicators of sentiment and market in a cryptocurrency prediction model.
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