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The risks and returns of algorithmic trading

On Friday, March 23, 2012, a sequence of events unraveled in the equity markets that left many investors puzzled and the staff at Better Alternative Trading Systems (BATS) scrambling. BATS, a major U.S. trading venue, went public that day and started trading its own stock only to withdraw the offering a few hours later. This was not the first time that erroneous trades caused a market-wide panic, but the fact that such trades caused BATS to pull back its IPO offering was significant.

Although the precise sequence of events is still unknown, the situation started with an erroneous trade of Apple stock on the BATS platform, triggering circuit breakers in all venues trading the stock. That was followed by BATS’ own stock trading down significantly lower after opening at $15.25, which, according to different *sources, touched as low as $0.02. Many participants are questioning how such trading events can occur and how can they be prevented. More importantly, such occurrences have revived the debate about the complexities of today’s capital markets and whether algorithmic trading does more harm than good.

High-frequency or algorithmic traders dominate the markets today and their role has a profound impact on the market microstructure. In a quest to achieve superior returns through better execution, algorithmic trading has also introduced new risks to the marketplace that are still not thoroughly understood by most participants.

Take adverse selection risk as an example. In a traditional market, this translates to the risk faced by market makers of losing out on a transaction due to trader(s) on the other side of the trade having more (and potentially material) information about the asset. To mitigate this risk, market makers usually require compensation through bid-ask spreads.

In an electronic setting, traders place and market makers fill orders in fractions of a second. Market makers have to ensure that they provide the required liquidity on the opposite end of the trade by monitoring the flow of orders. In cases where there is a significant, unanticipated flow of orders from one end and absence of liquidity on the other, the flow of orders becomes toxic and may cause extreme price fluctuations. In the world of algorithmic trading, therefore, flow toxicity is analogous to the risk of adverse selection.

Fragmentation of the market combined with the dominance of algorithmic trading means that events where liquidity appears to have vanished will occur more frequently. Moreover, such events are not isolated to one venue but have widespread consequences that engulf other venues and securities. The Flash Crash is a case in point, which all started with the drying up of liquidity in the S&P 500 E-mini Futures contracts and pushed global markets into chaos.

On the other hand, this fragmentation and increased competition in the industry translates to lower transaction costs and better returns for investors. Research on the impact of alternative venues in the United States has also indicated that market quality has improved due to market fragmentation.

A balancing act
How society and regulators balance the good versus harmful aspects of algorithmic trading has turned into a philosophical debate, but industry practitioners need to come up with viable solutions to this paradox. How can the impact of such malfunctions be limited? What degree of cooperation is required among the various competing trading venues to limit the potential harm caused by algorithmic traders?

As practitioners, the starting point should be the technology architecture of the trading venues themselves. Their internal systems need to be robust and thoroughly tested against unconventional situations rather than relying on regulators to draft the rules of the game. While aberrant trading occurrences need to be contained at the source, sound recovery strategies also need to be in place to ensure that trading activities are uninterrupted.

Like any industry, new problems are bound to emerge and pose new challenges for participants. Winners in this fragmented market will be those who have anticipated these challenges in advance and stand ready to confront them. As Albert Einstein once said, “A clever person solves a problem. A wise person avoids it.”

*Sources

  1. Bats CEO Blaming Code Stirs Concern on Market Complexity,” Bloomberg, Nina Mehta et
  2. “High-Frequency Trading, Flow Toxicity, and the Flash Crash,” Maureen O’Hara, Take 15 Series, CFA Institute
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