英文标题：
《Cross-Sectional Variation of Intraday Liquidity, Cross-Impact, and their
  Effect on Portfolio Execution》
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作者：
Seungki Min, Costis Maglaras, Ciamac C. Moallemi
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最新提交年份：
2018
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英文摘要：
  The composition of natural liquidity has been changing over time. An analysis of intraday volumes for the S&P500 constituent stocks illustrates that (i) volume surprises, i.e., deviations from their respective forecasts, are correlated across stocks, and (ii) this correlation increases during the last few hours of the trading session. These observations could be attributed, in part, to the prevalence of portfolio trading activity that is implicit in the growth of ETF, passive and systematic investment strategies; and, to the increased trading intensity of such strategies towards the end of the trading session, e.g., due to execution of mutual fund inflows/outflows that are benchmarked to the closing price on each day. In this paper, we investigate the consequences of such portfolio liquidity on price impact and portfolio execution. We derive a linear cross-asset market impact from a stylized model that explicitly captures the fact that a certain fraction of natural liquidity providers only trade portfolios of stocks whenever they choose to execute. We find that due to cross-impact and its intraday variation, it is optimal for a risk-neutral, cost minimizing liquidator to execute a portfolio of orders in a coupled manner, as opposed to a separable VWAP-like execution that is often assumed. The optimal schedule couples the execution of the various orders so as to be able to take advantage of increased portfolio liquidity towards the end of the day. A worst case analysis shows that the potential cost reduction from this optimized execution schedule over the separable approach can be as high as 6% for plausible model parameters. Finally, we discuss how to estimate cross-sectional price impact if one had a dataset of realized portfolio transaction records that exploits the low-rank structure of its coefficient matrix suggested by our analysis.
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中文摘要：
自然流动性的构成一直在变化。对标准普尔500成分股的日内成交量分析表明：（i）成交量意外，即与各自预测的偏差，在各个股票之间存在相关性；（ii）这种相关性在交易日的最后几个小时内增加。这些观察结果可部分归因于ETF、被动和系统性投资策略增长中隐含的投资组合交易活动的普遍性；并且，在交易日结束时，此类策略的交易强度增加，例如，由于执行以每天收盘价为基准的共同基金流入/流出。在本文中，我们研究了这种投资组合流动性对价格影响和投资组合执行的影响。我们从一个程式化模型中得出了一个线性跨资产市场影响，该模型明确地捕捉到了一个事实，即自然流动性提供者中的某一部分在选择执行时只交易股票投资组合。我们发现，由于交叉影响及其日内变化，风险中性、成本最小化的清算人以耦合方式执行订单组合是最优的，而不是通常假设的类似VWAP的可分离执行。最佳时间表将各种订单的执行结合起来，以便能够在一天结束时利用增加的投资组合流动性。最坏情况分析表明，对于合理的模型参数，与可分离方法相比，此优化执行计划的潜在成本降低可能高达6%。最后，我们讨论了如果有一个已实现的投资组合交易记录数据集，该数据集利用了我们分析建议的系数矩阵的低秩结构，那么如何估计横截面价格影响。
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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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