Purpose

This paper aims to demonstrate a dynamic cointegration-based pairs trading strategy, including an optimal look-back window framework in the cryptocurrency market and evaluate its return and risk by applying three different scenarios.

Design/methodology/approach

This study uses the Engle-Granger methodology, the Kapetanios-Snell-Shin test and the Johansen test as cointegration tests in different scenarios. This study calibrates the mean-reversion speed of the Ornstein-Uhlenbeck process to obtain the half-life used for the asset selection phase and look-back window estimation.

Findings

By considering the main limitations in the market microstructure, the strategy of this paper exceeds the naive buy-and-hold approach in the Bitmex exchange. Another significant finding is that this study implements a numerous collection of cryptocurrency coins to formulate the model’s spread, which improves the risk-adjusted profitability of the pairs trading strategy. Besides, the strategy’s maximum drawdown level is reasonably low, which makes it useful to be deployed. The results also indicate that a class of coins has better potential arbitrage opportunities than others.

Originality/value

This research has some noticeable advantages, making it stand out from similar studies in the cryptocurrency market. First is the accuracy of data in which minute-binned data create the signals in the formation period. Besides, to backtest the strategy during the trading period, this study simulates the trading signals using best bid/ask quotes and market trades. This study exclusively takes the order execution into account when the asset size is already available at its quoted price (with one or more period gaps after signal generation). This action makes the backtesting much more realistic.

中文翻译：

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加密货币市场中基于动态协整的配对交易策略评估

目的

本文旨在展示一种基于动态协整的配对交易策略，包括加密货币市场中的最佳回顾窗口框架，并通过应用三种不同的场景来评估其回报和风险。

设计/方法/方法

本研究使用 Engle-Granger 方法、Kapetanios-Snell-Shin 检验和 Johansen 检验作为不同场景下的协整检验。本研究校准 Ornstein-Uhlenbeck 过程的均值回归速度，以获得用于资产选择阶段和回顾窗口估计的半衰期。

发现

通过考虑市场微观结构的主要限制，本文的策略超越了 Bitmex 交易所中幼稚的买入持有方法。另一个重要发现是，这项研究实施了大量加密货币硬币来制定模型的点差，从而提高了配对交易策略的风险调整盈利能力。此外，该策略的最大回撤水平相当低，这使其易于部署。结果还表明，一类硬币比其他硬币具有更好的潜在套利机会。

原创性/价值

这项研究具有一些明显的优势，使其在加密货币市场的类似研究中脱颖而出。首先是数据的准确性，其中分档数据在形成期产生信号。此外，为了在交易期间回测策略，本研究使用最佳买卖报价和市场交易模拟交易信号。当资产规模已经以其报价可用时（在信号生成后有一个或多个周期缺口），本研究仅考虑订单执行。此操作使回溯测试更加真实。