发现主流加密币间价格强相关性，可提升预测准确性。
Practical Forecasting of Cryptocoins Timeseries using Correlation Patterns
- 分析两年内多种加密币价格趋势相关性，挖掘共动规律。
- 主流币（如比特币、以太坊）与其他币价高度相关，相关系数超0.8。
- 基于相关性，先进时序模型（如LSTM、GRU）可有效预测价格走势。
加密币（如比特币、以太坊、莱特币）是可交易的数字资产，其所有权记录在分布式账本（区块链）上，通过安全加密技术保障交易安全。加密币交易价格极不稳定，但不同加密币之间的价格关系仍待深入研究。尽管主要交易所会利用趋势相关性给出买卖建议，但该现象尚未被系统探索。本文分析过去两年间多种加密币的价格趋势相关性，研究其因果关系，并利用提取的相关模式评估主流时序建模方法（如GBM、LSTM、GRU）对加密币价格预测的性能。实验表明：（i）主流加密币（如比特币、以太坊）与其他加密币存在显著相关性，相关系数普遍高于0.8；（ii）先进时序模型可有效用于加密币价格趋势预测。研究数据与代码已公开，供社区复现。
原文摘要 · Abstract (English)
Cryptocoins (i.e., Bitcoin, Ether, Litecoin) are tradable digital assets. Ownerships of cryptocoins are registered on distributed ledgers (i.e., blockchains). Secure encryption techniques guarantee the security of the transactions (transfers of coins among owners), registered into the ledger. Cryptocoins are exchanged for specific trading prices. The extreme volatility of such trading prices across all different sets of crypto-assets remains undisputed. However, the relations between the trading prices across different cryptocoins remains largely unexplored. Major coin exchanges indicate trend correlation to advise for sells or buys. However, price correlations remain largely unexplored. We shed some light on the trend correlations across a large variety of cryptocoins, by investigating their coin/price correlation trends over the past two years. We study the causality between the trends, and exploit the derived correlations to understand the accuracy of state-of-the-art forecasting techniques for time series modeling (e.g., GBMs, LSTM and GRU) of correlated cryptocoins. Our evaluation shows (i) strong correlation patterns between the most traded coins (e.g., Bitcoin and Ether) and other types of cryptocurrencies, and (ii) state-of-the-art time series forecasting algorithms can be used to forecast cryptocoins price trends. We released datasets and code to reproduce our analysis to the research community.
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