用神经网络排名币种未来收益，实现更稳健的加密货币组合投资
Long-only cryptocurrency portfolio management by ranking the assets: a neural network approach
- 通过神经网络预测多币种相对收益排名并分配权重
- 三年间年化收益64.26%，夏普比率达1.01
- 对交易费用敏感度低，适合复杂市场环境
本文提出一种基于机器学习的加密货币组合管理方法。与以往仅预测单一币种走势不同，该方法通过分析多币种间的相对关系，在每个时间步利用神经网络预测各币种未来收益排名，并据此分配权重。基于2020年5月至2023年11月的真实日度数据回测，该方法在经历完整牛、熊及盘整周期的3.5年中表现优异，实现年化收益率64.26%，夏普比率1.01。此外，该方法对交易费用上升具有鲁棒性。
原文摘要 · Abstract (English)
This paper will propose a novel machine learning based portfolio management method in the context of the cryptocurrency market. Previous researchers mainly focus on the prediction of the movement for specific cryptocurrency such as the bitcoin(BTC) and then trade according to the prediction. In contrast to the previous work that treats the cryptocurrencies independently, this paper manages a group of cryptocurrencies by analyzing the relative relationship. Specifically, in each time step, we utilize the neural network to predict the rank of the future return of the managed cryptocurrencies and place weights accordingly. By incorporating such cross-sectional information, the proposed methods is shown to profitable based on the backtesting experiments on the real daily cryptocurrency market data from May, 2020 to Nov, 2023. During this 3.5 years, the market experiences the full cycle of bullish, bearish and stagnant market conditions. Despite under such complex market conditions, the proposed method outperforms the existing methods and achieves a Sharpe ratio of 1.01 and annualized return of 64.26%. Additionally, the proposed method is shown to be robust to the increase of transaction fee.
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