Co-Movements in Bid-Ask Spreads and Market Depth

Abstract

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.

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