The prevalent view in the media over the last few years has been that high-frequency trading (HFT) is dangerous for the financial markets and that regulation is necessary to ensure market stability. From a voluntaryist perspective I will argue that HFT — as any other technological advancement and voluntary interaction — is beneficial to the markets and that most of the undesirable phenomena for which it is blamed (market instability) are the result of unintended consequences from regulation.
HFT is implemented via computer algorithms that take market data (trades and orders) as input, process it based on statistical arbitrage algorithms, and issue trading orders as output. Statistical arbitrage is a process of discerning and exploiting statistical patterns in the market data. What makes these algorithms high-frequency, as opposed to any other trading algorithm, is the quick (sub-second) turn-around time between the occurrence of the input data and the output orders. Driven by increases in computing power and network bandwidths, the technological arms race between profit-seeking firms has driven the turn-around times down to the order of micro-seconds.
Why is speed important to a HFT firm? Assume a pattern has been discerned in the behavior of IBM and MSFT shares by which a move in the price of MSFT (and IBM) is expected to be more likely over the next few seconds/minutes given a certain input of IBM and MSFT market data (trades and orders). Whoever is the fastest in (1) acquiring the input data, (2) processing it to establish the existence of the pattern, and (3) sending the orders out to take advantage of the discerned statistical edge, will take the largest piece of the profits and, at the same time, diminish or extinguish the statistical anomaly by its actions. This is why constant investment towards lower latency (smaller delay in communicating market data and orders between the HFT algorithm and the exchanges) is necessary for maintaining competitiveness.
A typical question is raised: Why even have/allow firms and algorithms like these? Do they help markets or society as a whole? Even if, by some measure, a voluntary transaction between two parties (a buyer and a seller) does not help a third party, it is, by definition, beneficial to both interacting parties (or it wouldn’t have occurred) regardless of the time it has taken those parties to decide on and execute said transaction. Luckily, HFT firms and algorithms have also tightened the bid-ask spreads in most instruments (equities, futures, currencies, etc.) which has improved price discovery and has lowered the execution costs for all market participants over the years.
HFT have been blamed for causing market instability. The hypothesis is that whether out of malice or incompetence, HFT algorithms have produced avalanches of orders causing market imbalances and large price movements over very short periods of time. There have been calls for tighter regulation of HFT algorithms and firms towards preventing these events from occurring in the future. I will argue that, as usual, government regulation is not a solution but precisely the problem itself.
Assume that a HFT algorithm “decides” (out of malice, “greed”, or incompetence) to start selling large quantities of IBM shares, bringing the price down by 10% in five minutes (an extremely large and quick price move). Other HFT algorithms would learn about this move as they receive the market data, compare it to moves in other — typically correlated — prices, and decide whether this anomaly offers any statistical edge about prices in the near future. Some algorithms will decide that IBM has become so much cheaper than MSFT and other historically correlated instruments (and so quickly) that they would start buying IBM and selling MSFT (short) in expectation that such discrepancy will revert to its statistically expected mean. This profit-driven buying of IBM shares would start to counteract the initial wave of selling and attenuate the price slide. In this way, profit-seeking agents directly act as a stabilizing force bringing the market closer to an equilibrium. Similar but less drastic examples of the described scenario happen thousands of times a day. The “greedy”, malicious, or incompetent constantly get punished (therefore regulated) by equally self-interested, yet more competent agents.
So why do markets seem to be experiencing ever more frequent and unexpected bursts of instability? Leaving aside for the moment the subject of central banking-supported and credit-driven increase in leverage, I argue that this instability is caused by increased government regulation of the markets. With the goal of making markets more stable and fair, regulators of all sorts have intruded into the market by imposing rules and orders which — through the reliable concept of unintended consequences — inevitably add instability.
Let’s continue with the IBM / MSFT example. Assume that IBM shares had collapsed -25% (relative to the previous day’s closing price) within a 30min period while MSFT has only fallen -15%. Then, driven by the above-described counter-balancing effects of the HFT algorithms (buying more IBM and selling more MSFT), both shares end up being down “only” -10% relative to the previous day’s close. HFT algorithms had been buying IBM all the way up from -25% to -10% and have been selling (shorting) MSFT shares as they went up from -15% to -10%. After the market closed a regulator comes in and decides to retroactively cancel all IBM trades below -15% due to “irregular” market conditions. All HFT firms that had bought IBM from -25% to -15% and sold MSFT (as a hedge) have immediately been denied the profits from the long (buy, IBM) leg of their hedged trade while made to accept the losses on its short (sell, MSFT) leg. By the stroke of a pen, their profitable and market-stabilizing action has been transformed into a disaster.
Now let’s put ourselves in the shoes of one of these HFT firms the next time a large price discrepancy occurs. What would be their incentive to buy IBM and sell (short) MSFT the next time IBM experiences a precipitous fall? The answer is clearly: none – and this predicament (lack of a stabilizing counter-balance) is what will exacerbate and amplify each and every price anomaly going forward. The uncertainty of regulatory action (intrusion) and its consequences is what suppresses the market-stabilizing action of profit-seeking market agents.
The regulators and the public would then jump in with criticisms about how HFT firms participate in the market (and provide beneficial liquidity) only when markets act “normal” but quickly disappear when market experiences abnormal volatility (crisis). They also wonder why. It must be greed – which, of course, must then also be regulated out of existence. There are rules proposed (maybe even implemented) which would force certain categories of firms (as judged by regulators) to participate in the market action (i.e. provide liquidity) at all times!
The regulatory attempts don’t stop there. There are hundreds of “if-then” rules that are supposed to “calm” the markets down during volatile periods. As is typical with any regulation, their most consequential effects are of the unintended and negative kind.
Finally, participation in trading on (private) exchanges is voluntary. Regulation on establishing and running market exchanges should be removed so that multiple and competing exchanges can impose rules of behavior which they believe would be most beneficial to the customers/clients they seek to attract.
Tagged: electronic trading, flash crash, HFT, high-frequency trading, market exchanges, market instability, market liquidity, market regulation, market volatility, statistical arbitrage, trading algorithms