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US laws and regulations prohibit people from lying, deceiving, or otherwise tricking prospective and actual customers in connection with buying or selling futures and other derivatives. For example, the law considers it fraud for a person to solicit money from customers to invest in a hedge fund (i.e., commodity pool) that purportedly will trade stock index futures and then (as actually happened in one 2009 CFTC civil enforcement case) use customer money to instead buy, among other things, a collection of 1,348 rare, stuffed teddy bears for more than $3 million. This prohibition should not be surprising, as just about every financial regulatory regime outlaws fraud. This chapter has to cover more territory than some of the other parts of this book because one of the central purposes behind the regulation of financial markets is the prevention of fraud, which can take many forms.
Now that we have learned about the common economic definitions of futures and other derivatives, it’s time to see how the relevant US laws and regulations define these financial instruments. The legal and regulatory definitions of derivatives and other financial instruments are often different from the common economic definitions of those selfsame instruments. Why is that? Contrary to what one might think, it is not because Congress wants to make life difficult for law students, or to confuse people. Instead, the differences between how various financial instruments are conceptualized in everyday life and how they are described in statutes and regulations are largely (although not solely) the result of Congress trying to make sure that people cannot easily evade applicable laws and regulations by simply creating look-alike financial instruments that would escape the regulatory framework that Congress had intended for such instruments. In many cases, the legal and regulatory definitions of financial instruments are more expansive and ambiguous than the definitions in common usage.
This chapter describes the elements of market manipulation claims and the history of market manipulation in connection with the US markets for derivatives. From the beginning of futures trading in the United States in Chicago shortly before the Civil War, rampant market manipulation and other abusive trading practices have threatened commodity futures trading. Accordingly, since the passage of the Grain Futures Act of 1922 (GFA), the precursor to the CEA of 1936 and the first federal effort to oversee US derivative markets (as discussed in greater detail in Chapter 2), the “central focus” and “essential goal” of the federal regulation of futures and derivatives has been “the punishment and prevention of … manipulation,” which is more specifically referred to as “price manipulation” or “market-power manipulation.” Perhaps more colorfully, a former CFTC chairman has compared market-power manipulation to situations “where the 800-pound gorilla simply invades the chicken coop.”
Before analyzing how technological innovation has changed the financial markets, one must obtain a basic understanding of some terms and concepts that are necessary to understand these markets in the first instance. As mentioned in the Introduction, the United States has two market regulators: the Commodity Futures Trading Commission (CFTC) and the Securities and Exchange Commission (SEC). In deciding to have two market regulators, Congress established a framework in which the SEC oversees the markets for securities, which include stocks in companies, as well as bonds, government securities, and even stock options and other types of derivatives that are considered to be securities under US law. The CFTC, on the other hand, governs the markets for futures contracts, commodity options, swaps, and other derivatives that the law does not categorize as securities. Some have criticized the fact that the United States has two market regulators, as opposed to one consolidated regulator for both securities and futures markets.
Many of the largest US hedge funds and investment advisors invest and trade in not only securities and bonds, but also in futures, swaps, and other derivatives. As a result, a fair number of US hedge funds and investment advisors are regulated by the CFTC. The fact that hedge funds and investment advisors are regulated by the CFTC is not common knowledge because most people focus on the fact that funds and investment advisors are known for their securities trading, but a great deal of funds and investment vehicles also trade in interest rate derivatives, a circumstance that brings them within the CFTC’s regulatory ambit. Persons that are paid to give trading and investment advice regarding derivatives are called “commodity trading advisors” (CTAs).
As discussed in Chapters 6 through 9, computers and software programs can, or soon will be able to, independently do all of the foregoing activities. As such, the legal and regulatory system must be prepared for the prospect of digital intermediaries operating in the futures markets.
In folklore, a will-o’-the-wisp is a supernatural ghostly floating light found in swamps and marshes that leads unfortunate travelers off safe paths and into dangerous areas. Although “spoof” orders for trades in futures contracts (and other financial instruments) are neither supernatural nor found in swamps, they are similar to will-o’-the-wisps in that spoof orders are fleeting presences intent on leading others astray. Modern futures market will-o’the-wisps, however, are often software algorithms that travel through trading platforms at superhuman speeds, and not the fiery fairy beings portrayed in legends.
One of the potential disadvantages of recent innovations in trading technology is that the markets now move with lightning speed in both good times and bad. With trading in futures and securities regularly counted in milliseconds (i.e., one thousandth of a second) and even microseconds (i.e., one millionth of a second), market crashes and rallies now also can occur – and, indeed, have occurred – at breakneck speeds that make human reaction times seem tortoise-like. The same algorithmic trading technologies that have enabled the markets for futures, securities, and options to incorporate information into the prices of financial instruments more quickly than ever before also have resulted in occasional high-speed crashes and rallies whose causes have, at times, confounded market participants and experts.
While this book has focused on US regulation of derivatives (with an emphasis on the impact that AI systems and related technologies have had on these markets), people and firms trade futures and derivatives – often with the aid of computers – not just in the United States, but throughout the world. Algo bots are effectively borderless, and not just because they don’t have “bodies” in the sense that humans do, but because advances in AI systems and related technologies are not restricted to the United States, and because the business entities that use algo bots to trade can easily “locate” themselves at various points across the globe for tax, regulatory, or other purposes. This book would be far longer than it already is if I detailed how every nation regulated algorithmic trading of derivatives.
Scientists have observed that some animals have been able to adapt to climate change, particularly global warming, and habitat loss by human incursion, whereas other animals have not. For example, some birds have adjusted to warmer temperatures by altering their regular seasonal migration habits so that they fly to different places and at different times than would normally be the case, such as arriving earlier to their traditional winter habitats. Other birds, however, have not been so fortunate. In particular, many types of coastal nesting birds, such as the Eurasian oystercatcher, are at risk for extinction because they have been unable to adjust to the increased frequency of tidal flooding associated with rising sea levels.
If I were to paraphrase the legal concept outlined in this chapter with a slogan, it would be this: “Keep a watchful eye on your computerized trading systems because oversight failures and carelessness can lead to culpability.” This chapter analyzes a potential way to hold firms accountable for the actions of algo bots despite the fact that trading bot software programming cannot – in many circumstances under existing law – provide sufficient evidence of the culpable mental states required by causes of action for financial fraud and price manipulation. As discussed earlier, the majority of trading decisions in large segments of the futures markets are made by ATSs and related algo bots acting without specific human direction.
If you have ever wondered about the difference between “artificial intelligence” and “machine learning,” you are in luck. The purpose of this chapter is to provide background and context on key concepts in artificial intelligence (AI) and to touch on how AI tools are used in the financial markets. In recent years, hedge funds, banks, commodity trading advisors, and numerous other financial services firms have adopted AI systems and related tools from computer science to automate numerous aspects of their operations, so understanding basic AI concepts can provide insights into how these firms operate.
Gateways, which serve as entry points that can allow people to reach areas that are different from their own, play critical roles in a variety of situations and contexts. For example, gateways are important plot devices in many science fiction works, where they often take the form of wormholes, which are openings that allow people to move from one point in space (or time) to another without actually having to physically cross the distance between those two points, in a manner similar to teleportation. The idea of wormholes originated from the fact some scientists once speculated that black holes could serve as instantaneous “bridges” to other locations in space. Although scientists now generally believe that humans will not be able to use wormholes to travel through space, that has not stopped science fiction writers from using this concept in their novels.
In writing this book, my overall objective was to provide an overview of the regulation of derivatives while exploring critical legal and regulatory issues associated with the ever-increasing use of algo bots and related AI systems in these markets. While discussion and analysis of HFT firms, virtual currencies, and algorithmic market manipulation might be more fashionable topics at the moment, basic information about the existing laws and regulations governing the markets for derivatives is necessary context for understanding the impact that technological changes are having on the markets for futures and other derivatives. That is why I included chapters covering topics that described the overall regulatory framework for derivatives.
With each passing day, the futures markets continue their transition to largely electronic ecosystems for algorithmic, software robots. The automation of these markets is part of a broader trend in financial services whereby the use of computerized systems is expanding into areas of financial firm operations that had not previously been thought amenable to algorithmic control. That’s not to say that humans are no longer playing important roles in financial services in the markets for futures and other derivatives, but the scope of human roles is diminishing as algo bots become capable of performing more and more tasks that were once the sole responsibility of human traders, derivatives salespeople, risk analysts, and more. As mentioned in the Introduction, the computerization and automation of financial markets is generally associated with the rise of “financial technology,” commonly referred to as “FinTech” or “Fintech.”
Science fiction writers have frequently wrestled with questions relating to the ability of humans to understand the minds of robots and synthetic intellects. These works often portray robotic minds as functioning differently from those of humans. In some cases, analysis of someone’s mental processes and responses to specific situations is the only way to distinguish a human being from a robot. For example, one prominent protagonist in Isaac Asimov’s I, Robot collection of short stories is Dr. Susan Calvin, who is described as being a trailblazer the field of robot psychology. In Asimov’s stories, Dr. Calvin is the head “robopsychologist” for the fictional firm U.S. Robots and Mechanical Men, Incorporated. When a politician named Stephen Byerley runs for mayor of an unnamed major US city, Dr. Calvin is asked to determine if Byerley is a human being or a robot.