使用聚合数据重建订单流

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英文标题：
《Reconstruction of Order Flows using Aggregated Data》
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作者：
Ioane Muni Toke
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最新提交年份：
2016
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英文摘要：
  In this work we investigate tick-by-tick data provided by the TRTH database for several stocks on three different exchanges (Paris - Euronext, London and Frankfurt - Deutsche B\\\"orse) and on a 5-year span. We use a simple algorithm that helps the synchronization of the trades and quotes data sources, providing enhancements to the basic procedure that, depending on the time period and the exchange, are shown to be significant. We show that the analysis of the performance of this algorithm turns out to be a a forensic tool assessing the quality of the aggregated database: we are able to track through the data some significant technical changes that occurred on the studied exchanges. We also illustrate the fact that the choices made when reconstructing order flows have consequences on the quantitative models that are calibrated afterwards on such data. Our study also provides elements on the trade signature, and we are able to give a more refined look at the standard Lee-Ready procedure, giving new elements on the way optimal lags should be chosen when using this method. The findings are in line with both financial reasoning and the analysis of an illustrative Poisson model of the order flow.
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中文摘要：
在这项工作中，我们调查了TRTH数据库为三个不同交易所（巴黎-泛欧交易所、伦敦和法兰克福-德意志交易所）的几只股票提供的逐笔数据5年的跨度。我们使用一个简单的算法来帮助交易和报价数据源的同步，为基本过程提供了增强功能，根据时间段和交换情况，这些增强功能显示出重要的意义。我们表明，对该算法性能的分析是一种评估聚合数据库质量的法医工具：我们能够通过数据跟踪所研究交易所发生的一些重大技术变化。我们还说明了这样一个事实，即重建订单流时所做的选择会对随后根据此类数据校准的定量模型产生影响。我们的研究还提供了有关商业签名的要素，我们能够更精确地查看标准Lee Ready程序，并提供了使用此方法时应选择最佳滞后的新要素。研究结果与财务推理和订单流的说明性泊松模型分析一致。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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