用技术指标+机器学习预测比特币涨跌，准确率超92%。
Predicting Market Trends with Enhanced Technical Indicator Integration and Classification Models
- 融合均线、相对强弱等技术指标，构建分类模型预测市场方向。
- 在比特币数据上验证，买卖信号准确率达92%以上。
- 适合量化交易者或想提升决策效率的加密货币投资者。
由于高利润潜力，随着加密货币和股票市场的快速扩张，交易对投资者愈发吸引。然而，金融市场的复杂性和动态性使得准确预测价格仍具挑战性。加密货币市场的波动性进一步增加了交易者与投资者决策的难度。本文提出一种基于机器学习的分类模型，用于预测加密货币市场的走势（价格上涨或下跌）。模型利用历史数据及关键的技术指标，如移动平均收敛发散（MACD）、相对强弱指数（RSI）和布林带（Bollinger Bands）。通过对比特币收盘价的实证研究验证方法有效性，采用混淆矩阵与受试者工作特征曲线（ROC）评估性能，结果显示买卖信号准确率超过92%。研究证明，机器学习模型可有效辅助加密货币投资者在高度波动的市场中做出明智决策。
原文摘要 · Abstract (English)
Thanks to the high potential for profit, trading has become increasingly attractive to investors as the cryptocurrency and stock markets rapidly expand. However, because financial markets are intricate and dynamic, accurately predicting prices remains a significant challenge. The volatile nature of the cryptocurrency market makes it even harder for traders and investors to make decisions. This study presents a classification-based machine learning model to forecast the direction of the cryptocurrency market, i.e., whether prices will increase or decrease. The model is trained using historical data and important technical indicators such as the Moving Average Convergence Divergence, the Relative Strength Index, and the Bollinger Bands. We illustrate our approach with an empirical study of the closing price of Bitcoin. Several simulations, including a confusion matrix and Receiver Operating Characteristic curve, are used to assess the model's performance, and the results show a buy/sell signal accuracy of over 92\%. These findings demonstrate how machine learning models can assist investors and traders of cryptocurrencies in making wise/informed decisions in a very volatile market.
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