High Frequency Trading (2): Ethics Assessment

High Frequency Trading (2): Normative Assessment

By Tabraiz Lodhi

High frequency trading (HFT) is a subject of controversy especially in the wake of the 2010 “Flash Crash” in the United States (Gomber, 2011). The Flash Crash was a trillion-dollar stock market crash in the electronic securities market that resulted in the Dow Jones Industrial Average falling more than 1,000 points in 10 minutes. (Kenton, 2018) This crisis brought algorithmic trading practices in general — and high frequency trading in particular — to the forefront of discussions on financial market regulation. The crash raised troubling questions about the ethics of high frequency trading as a financial practice. Indeed, the in a normative assessment the drawbacks of high-frequency trading practices are many. No surprise, proponents have ready responses to these criticisms. There may be ways to make HFT a more ethically sound practice, and policy makers should give serious consideration to them, reflecting if such recommendations are sufficient. However, because the potential for abuse for HFT is significant, and because the benefits that HFT provides are not unique, the use of HFT should be restricted.

Background

High-frequency trading is a type of algorithm-based trading found in financial markets. Financial institutions such as investment banks and hedge funds often have to execute a large number of trades at once. To facilitate this process, they use automated, pre-programed trading instructions, one type of which is high-frequency trading. The distinctive features of HFT are its sophisticated algorithms, high turnover rates and order-to-trade ratios, as well as its short-term investment horizons. High frequency trades involve moving in and out of trading positions at super high volumes and speeds, often conducting hundreds of trades in fractions of a second. Such trades are able to exploit small differences in trading prices to make small profits on individual trades, which cumulatively add up to a sizeable profit. These features make HFT a unique kind of algorithmic trading.

Another important feature of high frequency trading is its prevalence in financial markets. The use of HFT by financial institutions has accelerated rapidly since its inception. In the mid-1990s, it accounted for less than 3% of the equities market — by 2010 (the year of the Flash Crash), it accounted for over 70% of dollar trading volume. (Zhang, 2010) Today, some industry experts estimate that algorithmic trading practices account for a staggering 90% of trading volume in the equities market, and a comparable volume in the futures market. (Cheng, 2017) One of the reasons for this rapid growth is the increasing sophistication of the technologies that drive HFT. These include, inter alia, computing power, algorithmic efficiency, and data-gathering methods. It is on these technologies that high-frequency trading practices rely, and their sophistication is expected to increase over time.

There are five salient features of high frequency trading practices.

  1. They are automated, pre-programmed trading instructions;
  2. They involve moving in and out of trading positions at super high speeds (typically seconds or minutes);
  3. They execute a large number of trades with very small profits per trade;
  4. They conduct a large number of these trades (often hundreds) simultaneously;
  5. They account for a significant proportion of the dollar trading volume in financial markets.

These features also give rise to ethics issues.

Critique

An important critique of HFT is its potential for abuse and the moral problems this presents. One such avenue for abuse is the practice of quote stuffing, whereby high-frequency traders quickly enter and then withdraw large orders in an attempt to flood the market with quotes, causing competitors to lose time in processing them. This allows traders to gain a pricing edge over their competitors in an unfair way. Market manipulation and price manipulation more generally are very real ethical issues. Critics argue HFT makes market manipulation more likely, or creates incentives for traders to manipulate. Investors may be able to make huge profits on small, hard-to-detect manipulation, like the kind caused by floating rumors. They might therefore, have an incentive to create and spread such rumors in order to exploit pricing differences. One study found there was a positive correlation between the use of HFT and ticking – movements in the price or price quotation of a security – and a negative correlation between the use of HFT and Price Dislocation Alerts – an alert indicating asset mispricing. (Frine & Lipone, 2012) These two metrics typically proxy for market manipulation, and positive correlation with HFT for both may lend credibility to the claim HFT leads to increased market manipulation. 

But even if HFT does not make market manipulation easier or more likely, there is still an inherent ethical concern with HFT. Fundamentally, high-frequency trading allows traders to make money through arbitrage, that is, the practice of exploiting temporary pricing efficiencies before others have time to notice or react to them. Such a practice may be unethical because a basic principle of financial markets is — or at least should be — transparency, that is, everyone should have all financial information available to them at the same time, to whatever extent possible. This is why practices like insider trading are illegal — they unfairly advantage certain investors who have privileged access to important market information before anyone else does. When this principle of transparency is applied to HFT, it becomes apparent the system of arbitrage on which it relies is not a transparent system at all. HFT traders are able to exploit pricing differences that are so small the typical investor is not informed of them or is unable to notice them. Even if the information on such pricing differences is publically available, high frequency traders are able to exploit them on a scale that non-HFT investors simply cannot.

This leads to another important critique of HFT: that it creates inequitable market conditions. HFT tends to hurt investors who do not use algorithmic or high-frequency trading methods. Because of the substantial profits they tend to make, especially as an aggregate of thousands of trades with very small margins, high frequency trading methods tend to ‘crowd out’ traditional investors who do not have access to the same kind of information and sophisticated technology. Studying the S&P 500, researchers found that high-frequency traders “made an average profit of $1.92 for every contract traded with large institutional investors and an average of $3.49 when they traded with retail investors. This allowed the most aggressive high-speed trader to make an average daily profit of $45,267,” according to the 2010 data. (Parker, 2013) The researchers concluded that these profits came at the expense of other, traditional investors, and that such practices may lead these investors to leave financial markets and abandon traditional investment techniques.

Response

Arguably, the room for abuse in HFT is not a compelling ethical argument against the practice. Financial markets are generally open to abuse and unethical manipulation — this does not mean that finance as a practice is unethical. A better approach might be to consider the extent to which (if it at all) unethical behavior in high-frequency can be minimized without abandoning HFT as a practice. If this is at all successful, and if the benefits of high-frequency trading are preserved in the process, then it will be a sufficient response to the critique that HFT is open to abuse. 

The more serious concern is the ethical drawbacks that are inherent to HFT. While it is true that high frequency traders profit through arbitrage, this does not make high frequency trading an unethical practice. The information and resources that make high-frequency trading possible are available in principle — and quite often in practice — to every investor in the financial market. This is in contrast, for example, with insider trading, where access to insider information is not available in principle or in practice to anyone outside the firm. Profiting from high frequency trading is as legitimate as profiting from one’s superior understanding of market trends or ability to interpret market data effectively. This is completely legitimate in financial markets, and indeed it is the backbone of the market system. To be able to profit off of one’s expertise in understanding financial markets is as important a market principle as transparency is, and high frequency trading involves at its core just that — the ability to profit off publicly available market information. It doesn’t matter in principle how small or imperceptible the pricing differences that HFT exploits are. Stock markets work best when information about pricing inefficiencies spreads quickly, and HFT, by exploiting pricing differences, corrects for pricing inefficiencies and helps make for an accurate market, which is better for everyone.

This leads to the final issue of inequitable market conditions. The benefits that HFT provides to the market may outweigh this potential drawback. The main benefit of HFT that is often cited is its ability to increase market liquidity and efficiency. High frequency traders act as market-movers in modern financial markets by providing a majority of liquidity, and in so doing, they create hospitable market conditions that benefit everyone. They make it easier to sell one’s shares, reduce bid-asks spreads, and generally make the market more efficient overall. This benefits everyone in the financial market, not just a select few, and therefore encourages rather than discourages traditional investors.

The problem with such an argument is it ignores the systematic inequality such an outcome creates. The benefits of increased market inefficiency do not outweigh the disadvantages, because the systematic inequality created by the exorbitant profits HFTs generate are not offset by increased efficiencies for traditional investors. According to a study of one E-mini S&P 500, 31 HFTs earned over $29 million in trading profits in one month. (Baron, et. al) That is a very large profit spread among a very small number of actors. Contrast this with studies which show reduced bid-ask spreads due to HFTs typically manifesting over a long period of time — usually a few months or years — and benefiting individual investors only marginally. (Brogaard & Garriott, 2018) Because high-frequency trading methods are only accessible to those investors with the relevant technological expertise, its proliferation leads to the accumulation of most of the liquidity in the hands of a few. That HFTs provide such liquidity is not, therefore, some kind of utilitarian based benefit when it has been acquired through conditions of systematic inequality.

Recommendations

There are policies that can reduce the potential for abuse of HFT. Some have already been put in place by government regulation, especially in the EU. There, the MiFIR — Markets in Financial Instruments Regulation — imposes a strict set of organizational requirements on investment firms and trading venues vis-à-vis HFT. These include, inter alia:

  1. Acquiring authorization to continue to use high frequency trading techniques;
  2. Storing time-sequenced records of algorithmic trading systems and trading algorithms for the past five years, and opening these up to government monitors;
  3. Implementing risk control mechanisms to ensure that trading systems are resilient and have enough capacity to prevent sending erroneous orders or contributing to a disorderly market. (Norton Rose Fulbright, 2014)

These provisions were meant to curtail widespread market abuse resulting from specialized investors sending out orders and withdrawing them immediately after using HFT methods. They may also be an effective way of preventing quote stuffing and similar abusive practices. 

While this is a good start, there is room for improvement. Other regulations that can be implemented include:

  1. Laying out a clear set of parameters to ensure consistency in the identification of high frequency trading practices. If the identification parameters of HFT are not made clear, the practice will be extremely difficult to regulate. If it remains difficult to regulate, it will be much more open to abuse and exploitation.
  2. Sharing information on HFT practices on a global scale: trading does not affect a single asset class or a single country. By sharing some of the information above (such as time-sequenced records of trading algorithms) on an intra-governmental level, regulators can make more informed regulations and minimize regulatory arbitrage.
  3. Identifying what constitutes abuse of HFT and laying out clear criteria for when such abuse occurs. These abusive practices may include, inter alia, quote stuffing, price manipulation, market dumping, and market manipulation. When these abusive practices are identified, prosecuting or penalizing firms that engage in them is much easier.

Despite these policy recommendations, problems with HFT will remain. For one thing, recommendations alone cannot increase the financial market’s resilience to shock caused by misuse of high-frequency trading practices. When such systemic shock occurs, it will be too little too late. Moreover, HFT will continue to be difficult to regulate, just as any complex financial practice is in financial markets. HFT can never be regulated perfectly or be made completely immune to abuse. Nevertheless, if proactive and vigorous action is taken against the abuse of HFT, then many of its most flagrant abuses can certainly be mitigated.

Evaluation

In the end, it is clear there is ample room for abuse in high frequency trading. While government regulations can go a long way, they cannot completely eliminate the potential for abuse. When such abuse occurs, the consequences for the market can be disastrous — the 2010 Flash Crash in the United States. Nevertheless, it is also clear that HFT as a practice is not inherently unethical, even though some of its consequences are. Perhaps the most serious of these consequences is the unequitable market conditions HFT creates. There appears to be no effective way to mitigate the inequity at present. On the basis of these harms, therefore, there is a strong case for restricting the use of HFT in financial markets. Most of the benefits that HFT does provide are either not unique to it (for example, market-movers can and do exist in markets without high frequency traders) or provide marginal benefits at best (see, for example, the studies cited on HFT’s effects on market efficiency). Therefore, high frequency trading should either be banned completely or severely restricted.

Works Cited

Baron, Matthew, Brogaard, Jonathan, and Kirilenko, Andrei. The Trading Profits of High Frequency Traders. Available online at:https://www.banqueducanada.ca/wp-content/uploads/2012/11/Brogaard-Jonathan.pdf Accessed on July 24th, 2019.

Brogaard, Jonathan & Garriott Corey. “High-Frequency Trading Competition.” Journal of Financial and Quantitative Analysis (2018). Available online at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2435999. Accessed June 22nd, 2019.

Cheng, Evelyn. Just 10% of trading is regular stock picking, JPMorgan estimates. Available online at: https://www.cnbc.com/2017/06/13/death-of-the-human-investor-just-10-percent-of trading-is-regular-stock-picking-jpmorgan-estimates.html. Accessed on July 2nd, 2019.

Frino, Alex & Lipone, Andrew. The impact of high frequency trading on martket integrity: an empirical examination. (May, 2012) Commissioned by the UK Governemnt’s Foresight Project. Available online at: https://pdfs.semanticscholar.org/4644/0e5fc9339f52c5f1f857b1ffd7e8073e2bf8.pdf. Acccessed on July 3rd, 2019.

Gomber, Peter. “High-Frequency Trading.” SSRN Electronic Journal (January, 2011). Available online at: http://ssrn.com/abstract=1858626. Accessed on June 20th, 2019.

Kenton, William. Flash Crash. Available online at:  https://www.investopedia.com/terms/f/flash crash.asp. Accessed: July 1st, 2019.

Norton Rose Fulbright. MiFID II / MiFIR: High Frequency and Algorithmic Trading Obligations (2014). Online publication. Available at: www.nortonrosefulbright.com/en/knowledge/publications/6d7b8497/. Accessed on June 23rd, 2019.

Parker, Tim. “Has High-Frequency Trading Ruined the Stock Market for the Rest of Us?” (January, 2013). Available online at: https://www.investopedia.com/financial-edge/0113/. Accessed on June 23rd, 2019.

Zhang, Frank. High-Frequency Trading, Stock Volatility, and Price Discovery (2010). Available online: http://ssrn.com/abstract=1691679. Accessed on June 19th 2019.

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