Review of Statistical Approaches for Modeling High-Frequency Trading Data
Review of Statistical Approaches for Modeling High-Frequency Trading Data
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DOI：
10.1007/s13571-022-00280-7
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发表时间：
2022-04
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通讯作者：
Chiranjit Dutta;Kara Karpman;Sumanta Basu;N. Ravishanker
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作者：
Chiranjit Dutta;Kara Karpman;Sumanta Basu;N. Ravishanker
由于过去二十年的技术进步，算法交易策略现在广泛用于金融市场。反过来，这些策略产生了高频（HF）数据集，这些数据集提供了极其精细的信息，有助于理解市场行为、动态和微观结构。在本文中，我们讨论了信息流如何影响高频（HF）交易者的行为，以及某些高频交易（HFT）策略如何显著影响市场动态（例如，资产价格）。本文还回顾了几种统计建模方法分析高频交易数据。我们讨论了四种流行的方法来处理高频交易数据：（i）聚合数据到定期间隔箱，然后应用定期的时间序列模型，（ii）建模价格过程中的跳跃，（iii）点过程的方法来建模感兴趣的事件的发生，（iv）建模事件间的持续时间序列。我们讨论了两种定义事件的方法，一种是基于资产价格，另一种是基于资产的价格和数量。我们根据这两个定义构建久期，并将模型应用于在纽约证券交易所（NYSE）交易的资产的逐时数据。我们讨论了高频交易数据分析中出现的一些开放性挑战，包括一些实证分析，并回顾了高频交易数据在金融和经济中的应用，概述了几个研究方向。
Due to technological advancements over the last two decades, algorithmic trading strategies are now widely used in financial markets. In turn, these strategies have generated high-frequency (HF) data sets, which provide information at an extremely fine scale and are useful for understanding market behaviors, dynamics, and microstructures. In this paper, we discuss how information flow impacts the behavior of high-frequency (HF) traders and how certain high-frequency trading (HFT) strategies significantly impact market dynamics (e.g., asset prices). The paper also reviews several statistical modeling approaches for analyzing HFT data. We discuss four popular approaches for handling HFT data: (i) aggregating data into regularly spaced bins and then applying regular time series models, (ii) modeling jumps in price processes, (iii) point process approaches for modeling the occurrence of events of interest, and (iv) modeling sequences of inter-event durations. We discuss two methods for defining events, one based on the asset price, and the other based on both price and volume of the asset. We construct durations based on these two definitions, and apply models to tick-by-tick data for assets traded on the New York Stock Exchange (NYSE). We discuss some open challenges arising in HFT data analysis including some empirical analysis, and also review applications of HFT data in finance and economics, outlining several research directions.