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在同态加密数据上计算趋势跟踪指标

文章 arXiv papers · 作者: Haotian Weng et al.
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总结

本研究考察能否在加密市场数据上计算趋势跟踪指标，使数据聚合方能够保密其数据，同时让分析人员生成交易信号。研究使用两个同态加密库SEAL和HEAAN实现该指标，并将加密计算与明文实现进行比较。研究背景是一种市场数据安排：中间方汇总交易决策并向分析人员分享加密输入，从而限制他们访问原始数据。

报告的指标输出与明文版本非常接近：研究给出的百分比误差为，SEAL对应0.14916%，HEAAN对应0.00020%。文中还描述了构建和分析交易策略的尝试，但所提供的摘要未给出策略层面的表现结果。作者指出，同态加密会带来实施限制。因此，证据支持该指标实现的数值相似性，但不能证明交易盈利能力、广泛适用性，或其在其他指标和数据场景中的运行适用性。

核心观点

  • 研究使用两个同态加密库在加密市场数据上实现趋势跟踪指标。
  • 研究将加密指标输出与明文实现进行比较。
  • 报告的百分比误差为：SEAL对应0.14916%，HEAAN对应0.00020%。
  • 描述提到交易策略分析，但未提供相关表现结果。
  • 加密限制了实现方式，而指标结果相似本身并不能证明盈利能力。

标签

趋势跟踪技术指标交易执行
全文
# A Trend-following Trading Indicator on Homomorphically Encrypted Data


# A Trend-following Trading Indicator on Homomorphically Encrypted Data









Algorithmic trading has proliferated the area of quantitative finance for already over a decade. The decisions are made without human intervention using the data provided by brokerage firms and exchanges. There is an emerging intermediate layer of financial players that are placed in between a broker and algorithmic traders. The role of these players is to aggregate market decisions from the algorithmic traders and send a final market order to a broker. In return, the quantitative analysts receive incentives proportional to the correctness of their predictions. In such a setup, the intermediate player - an aggregator - does not provide the market data in plaintext but encrypts it. Encrypting market data prevents quantitative analysts from trading on their own, as well as keeps valuable financial data private. This paper proposes an implementation of a popular trend-following indicator with two different homomorphic encryption libraries - SEAL and HEAAN - and compares it to the trading indicator implemented for plaintext. Then an attempt to implement a trading strategy is presented and analysed. The trading indicator implemented with SEAL and HEAAN is almost identical to that implemented on the plaintext, the percentage error is of 0.14916% and 0.00020% respectively. Despite many limitations that homomorphic encryption imposes on this algorithm's implementation, quantitative finance has a high potential of benefiting from the methods of homomorphic encryption.

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。