Co-Movements in Bid-Ask Spreads and Market Depth
Co-Movements in Bid-Ask Spreads and Market Depth
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买卖价差和市场深度的联动
DOI：
10.2469/faj.v56.n5.2386
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发表时间：
2000
影响因子：
2.8
通讯作者：
A. Subrahmanyam
中科院分区：
文献类型：
--
作者：
Tarun Chordia;Richard Roll;A. Subrahmanyam
报价价差、报价深度和有效价差与市场和行业范围内的流动性一起变化。在控制了众所周知的个体流动性决定因素（例如波动性、交易量和价格）后，我们发现共同影响仍然是重大且重大的。对于基于规模的多元化投资组合，超过一半的报价差价变化是由市场平均交易成本的变化来解释的。市场平均深度的每日变动解释了基于规模的投资组合 80% 以上的深度变化。当投资组合频繁换手时，交易费用会累积到总回报上相对较大的减少。由于基金经理经常同时交易多种证券，因此了解不同证券的交易成本是否相关对他们来说很重要。然而，对交易成本的研究几乎完全集中在个别证券上。通常，投资组合经理不会考虑整个市场背景下的流动性不足，而市场微观结构的经典模型涉及单一股票的交易商，该交易商以库存持有风险或与拥有高级信息的投资者进行交易的恐惧所产生的成本提供即时性。实证工作还只涉及单个资产的交易模式，最常见的是高频采样的股票。然而，由于多种原因，不同证券的交易成本可能存在相关性。例如，如果交易量随着广泛的市场波动而出现相关变化，那么这种模式应该会导致流动性成本的相关性。同样，持有库存成本的变化可能与不同证券相关，因为它部分取决于市场利率的变动。此外，与行业内大多数公司相关的各种类型的信息即将披露可能会同时影响多种证券的流动性。事实上，在一些著名的金融事件中，全系统流动性的突然变化似乎很重要。例如，1987 年 10 月的国际股市崩盘并没有与任何可识别的重大新闻事件相关，但其特点是流动性暂时减少。 1998 年夏季，流动性危机似乎同时影响了多种中低等级债券。这场危机似乎又加剧了某些高杠杆贸易公司的财务困境。我们使用纽约证券交易所股票的交易数据来分析交易成本的变化程度和协变程度。我们发现交易成本（以报价价差、报价深度和有效价差为代表）表现出显着的跨期变化。深度比买卖价差表现出更多的跨期变化。交易成本也随着市场和行业流动性的变化而变化。具体来说，在控制了众所周知的横截面流动性决定因素（例如波动性、交易量和价格）后，我们发现行业平均流动性的影响仍然显着且重大。此外，对于基于规模的多元化投资组合，报价利差的时间序列变化一半以上是由市场平均交易成本的变化解释的。市场平均深度的每日变动解释了基于规模的投资组合 80% 以上的深度变化。总体而言，结果表明多种证券的同时交易可能会产生相关的交易成本。此外，广泛多元化的投资组合经理所产生的交易成本可能会随着时间的推移而显着变化。结果还表明，平均流动性意外变化的风险包含很强的市场成分。流动性的联动表明，在适当的时机可以更好地管理交易费用。因此，我们的结果表明，平均投资组合利差较低时的交易策略可以在不影响投资组合回报表现的情况下增加投资组合周转率。
Quoted spreads, quoted depth, and effective spreads move together with market- and industrywide liquidity. After controlling for well-known individual liquidity determinants, such as volatility, volume, and price, we found that common influences remain significant and material. For well-diversified size-based portfolios, more than half the variation in quoted spreads is explained by variations in market average trading costs. Daily movements in the average depth of the market explain more than 80 percent of depth variations in size-based portfolios. When portfolios are turned over frequently, transaction expenses can accumulate to a relatively large decrement in total return. Because money managers often trade several securities simultaneously, knowing whether trading costs are correlated across securities is important to them. Yet, research on trading costs has focused almost exclusively on individual securities. Typically, portfolio managers do not think of illiquidity in a marketwide context, and the classic models of market microstructure involve a dealer in a single stock who provides immediacy at a cost that arises from inventory-holding risk or from the specter of trading with an investor with superior information. Empirical work also deals solely with the trading patterns of individual assets, most often equities sampled at high frequencies. Trading costs can, however, be correlated across securities for a variety of reasons. For example, if trading volume exhibits correlated changes in response to broad market movements, this pattern should induce a correlation in liquidity costs. Similarly, variations in the cost of holding inventory could be correlated across securities because it depends, in part, on movements in market interest rates. Also, the imminent revelation of various types of information that is pertinent for most companies in an industry sector could influence the liquidity of several securities simultaneously. In fact, sudden changes in systemwide liquidity appear to have been important in some well-known financial episodes. The international stock market crash of October 1987, for example, was associated with no identifiable major news event but was characterized by a temporary reduction in liquidity. And during the summer of 1998, a liquidity crisis appears to have simultaneously affected several mid- to low-grade bonds. This crisis, in turn, seems to have precipitated financial distress in certain highly levered trading firms. We used transaction data on NYSE stocks to analyze the extent of variation and covariation in trading costs. We found that trading costs—represented by quoted spreads, quoted depth, and effective spreads-exhibit significant intertemporal variation. Depth exhibits much more intertemporal variation than bid-ask spreads. Trading costs also move together with market- and industrywide liquidity. Specifically, after controlling for well-known cross-sectional liquidity determinants (such as volatility, volume, and price), we found that the influence of industry average liquidity remains significant and material. In addition, for well-diversified size-based portfolios, more than half the time-series variation in quoted spreads was explained by variations in market average trading costs. Daily movements in the average depth of the market explained more than 80 percent of depth variations in size-based portfolios. Overall, the results indicate that simultaneous trades of several securities are likely to incur correlated trading costs. Furthermore, the trading costs incurred by broadly diversified portfolio managers are likely to move together significantly through time. The results also suggest that the risks of unexpected changes in average liquidity contain a strong market component. Co-movements in liquidity suggest that transaction expenses might be better managed with appropriate timing. Thus, our results indicate that a strategy of trading when average portfolio spreads are low can allow for increased portfolio turnover without compromising portfolio return performance.