Ethical Concerns about Algorithms within Trading
This project hopes to examine a subject rarely talked about in today’s society — the use of algorithmic models in the trading of equities, specifically stocks. Investing itself raises a slew of societal concerns; does it widen the inequality gap by providing opportunities only to those with significant wealth already, or does it choke out smaller businesses by funneling large amounts of money into already monopolistic companies? If these concerns prove problematic, then the introduction of algorithms into trading would greatly exacerbate these concerns and may certainly prove detrimental to our society’s future. To even begin to understand the impacts of algorithmic trading and form accurate ethical conjecture, we must first understand the impacts of non-algorithmic trading today and their associated ethics.
First, we will examine the impacts of investing on the individual providing the capital in an investment. The financial definition of investment states that an investor can take on risk by providing a certain portion of their own capital or asset(s) to some endeavor with the expectation of a positive future return. One of the most commonly invested-in entities are companies via stocks. Specifically in stock investing, the investor provides the company with capital by purchasing a share or shares of the company’s stock, essentially a stake in ownership of the company, and in return, that company will use that money to grow and become more valuable, wherein the stock of that company will also grow accordingly in value. Thus, the investor is able to obtain a return on their investment that is greater than their initial investment and pocket the difference as profit. But there are also risks involved with investing; the company can make poor financial decisions wherein the value of the stock would go down, or there could be external factors such as natural disasters, conflicts, or other such events that can influence the nation’s economy. These risks are usually mitigated by diversifying one’s portfolio across multiple sectors and business sizes. With a slew of index funds designed for just this purpose, an investor can easily earn a steady return with relative safely. One of the biggest and most famous of these funds, the S&P 500, has an average annual return of approximately 10% since its inception. Using the investing “Rule of 72,” it will take roughly 7.2 years at a 10% annual rate of return to double one’s initial investment.[1] This grows exponentially, and thus those with more money to invest will be far ahead those that invest with less money. Furthermore, by buying shares, you are tying up capital that could be used to pay for bills or buy essentials or other such needs, so serious investing can only really be done by those with at least a good amount of disposable income — i.e., those that are already well off. This is where we run into the societal and ethical dilemmas surrounding investing. A high barrier of entry means that this activity can only seriously be done with those that are already well off and the exponential returns mean that the better off you are, the more return you will see on your investments. With the wealthy making exponentially more than the less wealthy who may not even be able to participate, it is obvious that this will lead to an inequality gap.
When firms started to add computer algorithms and use the models that they generate in purchasing stocks and other assets, their predicted returns have drastically increased. One of these leading quantitative firms, or “quants,” is Renaissance Technologies. According to their Wikipedia page, their Medallion Fund is “…considered to be one of the most successful hedge funds ever. It has averaged a 71.8% annual return, before fees, from 1994 through mid-2014.”[2]Renaissance’s employees consist of highly specialized scientists, ranging from PhDs in computer science and mathematics, to statistics and physics. It has even been called “the best physics and mathematics department in the world.”[3] Thus, we can see the impact and advantage of computational power when applied to stock and asset trading. Their algorithms and models have been developed by incredibly talented and unique people — which also makes their algorithms and models incredibly exclusive. This further exacerbates the previously stated problem with inequality, as now you have a firm that is able to drastically increase their returns thanks to their algorithms and models and which is limited to essentially whoever the firm chooses — usually exclusively to the rich and powerful that can afford such a luxury. Moreover, with the widely publicized success of Renaissance Technologies and their Medallion fund, many other hedge funds and firms have been hiring scientists themselves to try and develop their own algorithms and models, and those with the funds that can pull in smarter people will create more accurate models. Everyone else that is not a part of this new computational “elite” will be left in the metaphorical dust. This arguably violates rules 1.4 and 2.5 in ACM’s code of ethics, “Be fair and take action not to discriminate,” and “Give comprehensive and thorough evaluations of computer systems and their impacts, including analysis of possible risks” respectively. The first line of rule 1.4, “Computing professionals should foster fair participation of all people…” directly contradicts with the use of computer algorithms in these hedge funds, as average-income earning citizens will most likely never experience the benefits from these technologies.[4] These technologies will further disenfranchise those people as they are deprived of the opportunity to “super charge” their investments if they even do investment at all. Moreover, rule 2.5 of the ACM code of ethics states, “A system for which future risks cannot be reliably predicted requires frequent reassessment of risk as the system evolves in use, or it should not be deployed.” This is especially true for computer algorithms in the stock market as the stock market is interlinked with the entire economy as a whole and, as we’ve seen in the 2008 financial crises, any errors or mistakes in any part of such a system can possibly cause widespread suffering to, not the rich, but the everyday average person. It is impossible to tell the impacts of the implementation of this technology as it is spreading so quickly through the investing world and rooting itself in our global economic system that is, arguably inherently unstable and prone to changes.
In conclusion, there are two significant risks that the implementation of computer algorithms present — the fostering of societal inequality and the possibility of causing widespread suffering to many in the future. These algorithms are designed to maximize profit only for those that are able to afford it, disenfranchising the majority of the population that cannot afford the high upfront cost of investing in hedge funds or other firms that can afford to implement such a technology. Furthermore, they are untested and thus present a very large risk to our economy — a system that is a part of nearly everyone’s lives and where a major crash, deviation, or other such anomaly can result in mass unemployment, homelessness, and other societally damaging effects.
External Sources:
https://web.stanford.edu/class/ee204/TheRuleof72.html
- Stanford’s description and derivation on the Rule of 72
https://en.wikipedia.org/wiki/Renaissance_Technologies#cite_note-wsj-27
- Wikipedia article on Renaissance technologies
https://www.telegraph.co.uk/finance/10188335/Quants-the-maths-geniuses-running-Wall-Street.html
- The Telegraph article on Renaissance Technology’s employees and staff
https://www.acm.org/code-of-ethics
- ACM’s code of ethics