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.

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.

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.”

This book is about how the technological advances in automation and artificial intelligence (AI) that have fundamentally changed the nature of the US markets for futures contracts and other derivatives are necessitating, in some areas, changes to the legal and regulatory framework for these markets. To arrive at policy solutions to address the ways that AI systems are altering the markets, this book examines how algorithmic robots – algo bots, for short – have largely taken over trading in the futures markets, analyzes how regulators have responded to these changes thus far, and explores what steps policy makers should take in the future. But before diving into any of those topics, allow me to put the societal impact of these advances in computer science technologies in a broader context, beyond finance and derivatives.