Races, Rushes, and Runs: Taming the Turbulence in Financial Trading

Many participants, regulators, and observers of commodity and security markets have a sense that something in recent years has gone awry: that the explosive growth of high-frequency digital trading is somehow excessive, costly, unfair, and/or destabilizing. Several ideas for changing the rules have been discussed. Without a coherent explanation of exactly what is wrong, however, it can be very difficult to develop a promising remedy. The object of this paper is to offer one such explanation: that the digitization of the trading infrastructure, in combination with ubiquitous but fleeting information asymmetries, has stimulated a dramatic expansion of racing. By racing I mean the wasteful expenditure of resources in a contest to trade ahead of other market participants; that is, racing – like its cousin, queuing – is an example of a directly unproductive profit-seeking (DUP) activity whose costs erode the gains from trade that otherwise would be available to participants in the market. The paper also offers a specific remedy: the optional use of randomizing temporal buffers in the order flow. By slightly slowing the pace of trading, such buffers will allow market-data dissemination processes to saturate (i.e., will allow information asymmetries to dissipate) a little bit faster than order execution processes, so that price discovery and trading can operate more efficiently in an environment with more symmetrical information. By decoupling order flow from market-data flow, this remedy should also help reduce the likelihood of chaotic feedback instabilities in automated trading markets. Racing and its associated costs have received a good deal of attention in other contexts, particularly the race-to-fish in certain fisheries.2 Most analyses of financial markets appear to overlook the inefficiency of racing, however, in part due to a widespread misunderstanding of the efficient market hypothesis (EMH). Because the EMH emphasizes the speed with which information is incorporated into prices, many people tend to confuse speed with economic efficiency, thinking that faster must always be better. This is nonsense, of course. Real-world markets can always be made to operate a little faster, for a cost; but they can never be instantaneous. As the speed of trading approaches instantaneity, the cost will approach infinity. It follows that the optimum speed of trading – the efficient speed, in the ordinary economic sense of efficiency – must be finite. In order to have a complete understanding of what an economically efficient market looks like, therefore, we need to be able to explain what it means for a market to be trading too fast, as well as too slow. And we need to know what conditions might cause a market to operate at the wrong speed, and how such conditions might be corrected so that the market can find its optimum speed.A few notes at the outset: • First, this paper does not rely for explanatory value on panics, manias, nor any other psychological or behavioral phenomena. Perfectly rational homo economicus will engage in racing as described herein, as will computers unburdened with any emotional baggage. “Cooling-off periods” and other psychological remedies will not cure what is broken. • Neither does the racing hypothesis depend on allegations of cheating, conspiracies, underhandedness, unlawful or unfair or “toxic” behavior, nor anything that needs to be stamped out. This is not to deny that there may be multiple abusive practices at work, but they are not a necessary part of the explanation of why racing is inefficient and why it is a growing problem. This is important because it also means that even successful efforts to eliminate abuses will not solve the underlying problem. • This paper does not blame racing on any defect in regulation or market monitoring, and it contains no prescription for a regulatory fix. Rather, it alleges that an existing market imperfection has recently been severely aggravated by a technological change, the digitization of trading systems, and that the adverse effects can largely be mitigated by another technological change, the voluntary use of temporally buffered trading systems in parallel with real-time trading systems. Market participants should find it in their interest to adopt this remedial technology; if they do not, there is no compelling reason for regulators to impose it on them. Competition will be the best test of theory. • Finally, this is not an empirical paper; it describes and illustrates the theory of racing and its application to financial markets. Additional theoretical, empirical, and experimental work will be needed to quantify the effects of racing and to test the proffered remedy. In the sections that follow, I hope at least to start that conversation.