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Making Market Microstructure Matter

Financial Management (Financial Management Association), Summer, 1999 by Maureen O'Hara

What does market microstructure tell us of any value? How does the microstructure of markets matter? These may seem like odd questions to ask after more than a decade of microstructure research, but I think they point to a crucial research issue confronting finance researchers. We know that microstructure should matter in the sense that it affects economic decisions or variables, but how exactly it does matter is not clear. We are, perhaps, in the perplexing situation that while markets appear to work in practice, we are not sure they work in theory.

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The focus of this article is on the quest for this link between market microstructure and economic meaning. This focus may seem puzzling coming in the wake of Bill Christie and Paul Schultz's renowned research on the NASDAQ. Certainly, for the NASDAQ market makers who had to settle up (and for the myriad lawyers and finance colleagues who happily billed by the hour while this was all sorted out) microstructure research matters quite a lot. But, from another perspective, we could view this situation as merely a transfer problem: the dealers took from the traders, and the lawyers took from the dealers, but on balance the pie was still the same. Taking a somewhat less cynical view, we could argue that the subsequent changes in the NASDAQ market may have affected the size of the pie, but how it actually affected overall welfare remains unclear. I think such welfare issues are extremely important, and I will return to them later. First, I want to focus our attention on other, more basic issues. Does market microstructure actually affect economic behavior?

To address this issue, I will outline three areas where market microstructure should matter, but it is not clear how it does. My focus is on determining not only what we know and do not know, but also in defining a research agenda of what we ought to know.

I. Asset Pricing

If markets matter, then surely one place it should be evident is in asset pricing. We know that a major focus of market microstructure research is on the process by which information is incorporated into prices. Market microstructure models provide structural models of how prices become efficient, as well as models of volatility, both issues clearly of importance for asset pricing. But of perhaps more importance, microstructure models can provide explicit estimates of the extent of private information. We know that there is a link between this private information and spreads, but does it go further than that? In particular, if a stock has a higher probability of private information, should that have an effect on its required return?

This issue has been addressed in various ways in the literature. Perhaps the most straightforward approach is that of Amihud and Mendelson (1986) who considered a variant of this problem by arguing that liquidity should be priced. Their argument was that only investors with long horizons would hold illiquid stocks, which in their model is proxied by the bid/ask spread. In equilibrium, this clientele effect would result in higher required returns for illiquid stocks. Thus the question became, is liquidity priced?

Amihud and Mendelson present evidence that it is, but the overall research on this question has been mixed. Calculating a crude score card, we find Amihud and Mendelson (1986) and Datar, Naik, and Radcliffe (DNR) (1998) arguing that it is priced, and Chalmers and Kadlec (1998), Chen and Kan (1995), and Eleswarapu and Reinganum (1993) suggesting that it is not. Certainly, one might agree with DNR when they admit "whether liquidity affects asset returns or not remains unresolved thus far."

One difficulty in resolving this issue lies in exactly what is being sought. Is this higher return, if it exists, due to compensation for some exogenous illiquidity that manifests itself in large spreads, or is it a return for bearing the risk of higher private information that is also reflected in high spreads? These issues are obviously related, but they are not the same. The illiquidity arising from some exogenous factor (such as limited competition between dealers, for example) is akin to a tax, and its effects might be reasonably anticipated. The effects of private information are more complex, however, because of their link to the dynamic efficiency of asset prices. Do traders need compensation to hold a stock that is exposed to greater asymmetric information?

Perhaps the research closest to examining this issue is that of Brennan and Subrahmanyam (1996), who investigate empirically the role of a Kyle-[Lambda] in asset pricing. The results here are difficult to interpret, in part due to data problems, but they are intriguing. They do find support for the notion that [Lambda] somehow matters in affecting asset returns. But what motivates this result (and how to interpret it) is not clear. Could this relationship be due to inventory considerations or to liquidity problems more than to information effects? I do not think the structure tested in their work allows these issues to be disentangled, leaving us to agree that the link in the literature between asymmetric information and asset pricing is not yet apparent.

Financial Services Industry

Making Market Microstructure Matter

Financial Management (Financial Management Association), Summer, 1999 by Maureen O'Hara

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