统计套利和高频数据与应用于欧洲斯托克50股票

Jozef Rudy, C. Dunis, G. Giorgioni, Jason Laws
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引用次数: 59

摘要

本文的动机是将配对交易的统计套利技术应用于高频股票数据,并将其利润潜力与每日收盘价的标准采样频率进行比较。我们使用简单的交易策略来评估数据系列的利润潜力,并比较每个不同数据采样频率产生的信息比率。观察到的频率范围从5分钟的间隔到每个交易日收盘时记录的价格。对数据序列的分析表明,每日数据的协整程度为该货币对在高频领域的盈利能力提供了一个很好的指标。对于每个系列,样本内信息比率也是未来盈利能力的良好指标。结论性观察表明,在高频数据中应用新颖的多元化配对交易策略时,套利盈利能力实际上是存在的。特别是,即使考虑到非常保守的交易成本,建议的交易组合也实现了非常有吸引力的信息比率(例如,在高频间隔采样的平均配对高于3,而在每日采样频率高于1)。
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Statistical Arbitrage and High-Frequency Data with an Application to Eurostoxx 50 Equities
The motivation for this paper is to apply a statistical arbitrage technique of pairs trading to high-frequency equity data and compare its profit potential to the standard sampling frequency of daily closing prices. We use a simple trading strategy to evaluate the profit potential of the data series and compare information ratios yielded by each of the different data sampling frequencies. The frequencies observed range from a 5-minute interval, to prices recorded at the close of each trading day.The analysis of the data series reveals that the extent to which daily data are cointegrated provides a good indicator of the profitability of the pair in the high-frequency domain. For each series, the in-sample information ratio is a good indicator of the future profitability as well.Conclusive observations show that arbitrage profitability is in fact present when applying a novel diversified pair trading strategy to high-frequency data. In particular, even once very conservative transaction costs are taken into account, the trading portfolio suggested achieves very attractive information ratios (e.g. above 3 for an average pair sampled at the high-frequency interval and above 1 for a daily sampling frequency).
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