利用加密货币交易所资金流预测日内收益与波动率
文章 arXiv papers · 作者: Yeguang Chi et al.
总结
本研究检验链上资金流能否预测比特币、以太坊和泰达币的日内收益与波动率。研究考察 2017–2023 年间的一至六小时区间，并区分流入交易所的资金与投资者钱包之间的资金流动。作者还使用案例研究展示收益预测，并基于以太坊净流入制定期权策略，以评估以太坊投资的盈亏。
报告的关系因资产和结果指标而异。流入交易所的泰达币资金流在多个区间内正向预测比特币和以太坊收益；以太坊净流入则在所有测试区间内负向预测以太坊收益和波动率。除一个区间外，比特币净流入通常无法预测比特币收益，但与波动率负相关。这些是特定样本中的预测发现；所提供的摘要未说明资金流数据的构建方式、期权策略假设、交易成本，也未说明这些关系在研究时期之外是否持续。
核心观点
- 分析检验了链上资金流信号对比特币、以太坊和泰达币日内收益及波动率的预测能力。
- 据报告，流入交易所的泰达币资金流可在多个区间内预测比特币和以太坊收益上升。
- 据报告，以太坊净流入可在所有测试区间内预测以太坊收益和波动率下降。
- 比特币净流入通常缺乏收益预测能力，但与比特币波动率负相关。
- 研究考察了基于以太坊净流入的以太坊期权策略。
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全文
# Return and Volatility Forecasting Using On-Chain Flows in Cryptocurrency Markets # Return and Volatility Forecasting Using On-Chain Flows in Cryptocurrency Markets We empirically examine the intraday return- and volatility-forecasting power of on-chain flow data for Bitcoin(BTC), Ethereum(ETH), and Tether(USDT). We find ETH net inflows to strongly predict ETH returns and volatility in the 2017-2023 period. Our intraday frequencies are 1-6 hours. We find that differing significantly from forecasting patterns for BTC, ETH net inflows negatively predict ETH returns and volatility. First, we find that USDT flowing out of investors wallets and into cryptocurrency exchanges, namely, USDT net inflows into the exchanges, positively predicts BTC and ETH returns at multiple intervals and negatively predicts ETH volatility at various intervals and BTC volatility at the 6-hour interval. Second, we find that ETH net inflows negatively predict ETH returns and volatility for all intraday intervals. Third, BTC net inflows generally lack predictive power for BTC returns(except at 4 hours) but are negatively associated with volatility across all intraday intervals. We illustrate our findings on return forecasting via case studies. Moreover, we develop option strategies to assess profits and losses on ETH investments based on ETH net inflows. Our findings contribute to the growing literature on on-chain activity and its asset pricing implications, offering economically relevant insights for intraday portfolio management in cryptocurrency markets.
在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0
此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。