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A New Form of Market Efficiency: High Frequency Trading

October 03, 2016
When most individuals think of the stock market, they think of people in the famous trading pits depicted in popular media throughout the Twentieth Century. This antiquated scene, however, is far from the reality in today’s various securities exchanges. With everything being digitized, the same can be said of buying and selling securities; increasingly, broker-dealers are using algorithmic trading (aka high frequency trading) to not only conduct transactions at a more rapid pace, but also compensate for any market inefficiencies that may exist.

By: Tanner Bowen, W’18

Although studying market inefficiencies and failures seems to limit itself to the realm of an economics classroom, we often forget that the trading of securities (despite the number of complex financial instruments) is just like a typical transaction, in which we are concerned about both the supply and demand side. And whenever humans are involved in trading, various types of market failures can propagate.

One market failure in particular that can be almost systemic is adverse selection. Take liquidity providers such as broker-dealers, for example. Whenever you want to buy or sell a security, you have to go through a brokerage firm and have a brokerage account set up. One of the perks of having a brokerage account is that you can borrow money from the firm. In fact, the purpose of a brokerage firm is to act as a liquidity provider to those seeking to buy and sell securities. However, these liquidity providers will often charge a price concession whenever the “true” price of the security is unknown. Whenever these brokerage firms charge this price concession, this propagates market inefficiencies. Because of this, only the most informed investors who will always put in a buy/sell order whenever the price goes up/down will find it worthwhile to invest. Thus, the average investor is hurt.

Now, what role does high frequency trading play in the economics of trading securities? Due to how relatively new high frequency trading is, a lot of the minute details are not available, since firms who employ HFT do not want to leak their operational processes to potential competitors. However, high frequency trading has been shown to lead to different securities being synchronized. And whenever prices are synchronized, this can lead to a higher accuracy of security prices and even lower transaction costs.

A recent working paper from the SEC points out just how intuitive high frequency trading can be in leading to synchronization. Take, for example, that some event occurs which increases the likelihood that a country defaults on its sovereign debt. This information is then used by firms to buy securities to track the probability of this country’s default. Now, if the prices increase and markets are synchronized, then other securities adjust as well. Eventually, a more accurate price of a security is realized. This also decreases transaction costs since liquidity providers feel more confident in market prices.[1]

So, synchronizing prices, a result of HFT, helps to facilitate the diffusion of information between investors. The caveat to this, though, is that overall profits as a result of synchronization go down. This makes sense, since overall profits concentrated in the most informed investors will be diffused to even the average investor. This is because even the average investor will be able to see which securities are synchronized and how the trend in prices is going.

For this, the analogy of a school of fish seems appropriate.[2] In financial markets, the economy is monitored by a slew of investors that broadcast changes to each other via price movements. Through synchronization thanks to HFT, the many eyes of investors now function as one homogeneous group in which price trajectories look like those movements of a school of fish. This leads to efficiency and a reduction in wasteful resources; hopefully, saving those other investors against “predators.”

Although HFT can have many powerful results such as eventual price synchronization, the automatization of trading does have even larger drawbacks. Often the main issues are that localized errors can quickly propagate through the financial system via this admired synchronization. These incorrect relationships between securities can end up being disastrous beyond any efficient functionality that an economic relationship might warrant.

Finally, having algorithmic trading of the sorts like HFT comes with its own potential issues. For example, many algorithms used will leave the market whenever an event occurs that the system does not know how to handle. In some situations, this could be good. However, staying in the market can have potential risks too such as propagating errors and increasing a firm’s operational risks.

With the recent Flash Crash in mind, many investors are still a little foggy about HFT in general, let alone its benefits or potential drawbacks. The one thing that seems certain is that synchronization via automated trading does appear to have larger economic benefits in terms of decreasing transaction costs and improving market efficiency. Whether informed investors will easily let go of profits is another debate. Regardless, we are living in a now digitized society and the new trading mechanisms that result will have to be monitored and considered for public policy reforms by entities such as the CFTC and the SEC.

References

  [1] A. Gerig, “High-Frequency Trading Synchronizes Prices in Financial Markets,” 2016 [Online]. Available: https://www.sec.gov/dera/staff-papers/working-papers/dera-wp-hft-synchronizes.pdf

  [2] Ibid.

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