Book: Dark Pools by Scott Patterson

Dark Pools is an informative, quick read about high frequency trading, it’s origins, evolution, and current state. The text has a clear bias against HFT, however, it does bring a few interesting points to light.

It provides a great general overview of how HFT arose, from the origins of Datek to the ECNs like Island, Instinet, and Archipelago. The ECNs arose due to frustrations with the exchange floor specialists and brokers who could favor certain orders and were sometimes inefficient and slow. It was essentially a “boys club” that was unfair. Yet with the ECNs, what originally started as a quest to make markets more efficient eventually became an electronic variation of what existed in the past, an unfair playing field that only catered to those with the fastest speeds and closest server positions at the expense of the everyday, 401k and mom and pop investors.

Towards the end, Patterson touches on machine learning AI strategies that take in vast quantities of data and information from around the world to uncover actionable correlations. Using computing power to sift through fundamental information to make trades in the market makes the market more informative and efficient. Some HFT strategies take advantage of structural inefficiencies that exist in the market. While these are in the gray area, I believe these ultimately make the market better because these inefficiencies will eventually get discovered and fixed. Until then, if others make lots of $$ off these inefficiencies, then so be it, it’s a problem with the market structure.

I believe the problem is that these market structure inefficiencies aren’t discovered fast enough and will always exist within the system, simply because the regulators will always be a step behind. I do believe it’s a shame that many of the brightest people in our society spend their entire careers creating and tweaking algorithms to solve an artificial and ultimately, inconsequential problem of making trading decisions and executions fractions of a second faster. Yet, this goes back to my underlying belief that all of our actions are driven by incentives. Unfortunately, the monetary incentives in our society are such that this is the end result.

HFT as a whole though has declined significantly since the late 2000s and early 2010s. As competition ramped up, margins became smaller and as profits shrank, many firms closed shop. While HFT dominated daily exchange volumes, they’ve come down substantially. It seems like machine learning and AI strategies are the future: computers that process millions if not billions of fundamental data points and are able to learn on their own and make investment decisions. However, I believe there will always be a place for human traders in the market.

There’s a great book on market microstructure called “Trading and Exchanges” by Larry Harris. However, the first and only edition was published in 2002, it would be great if he released an updated version of his book. I’d also be interested to hear what George Soros thinks of HFT and how it fits into his Theory of Reflexivity in the markets.

Book: The Alchemy of Finance by George Soros

It’s an extremely dense, but eye opening book which gives you an inside look into Soros’ mind. With a background and serious interest in philosophy, Soros has a very unique approach to the markets which gives him his unique edge.

His main idea is the “Theory of Reflexivity,” where the thinking and actions of participants not only reflects a situation, it directly affects it. Unlike natural science, where you observe something and that’s it (ex. you make an observation and arrive at a conclusion about how a particle will act, your thoughts and actions have no bearing on the particle), in social science, your observations have a direct effect on what you’re observing (ex. you make an observation and arrive at a conclusion about a person’s behavior, your thoughts and actions can have an effect on the person you observed becomes aware of your conclusion).

For Soros, the financial markets provide the perfect “laboratory” to test this idea, as it concentrates thousands upon thousands of market participants and provides instant feedback. Standard market theory states that market prices are a direct reflection of fundamentals (ex. if oil is priced at $50/barrel, this reflects the fundamentals of oil). Soros argues that this is completely wrong, that market prices aren’t a direct reflection of fundamentals, but rather, people’s perceptions of the fundamentals. Not only that, but people’s perceptions of the fundamentals, which create market prices, can in turn have an effect on the very fundamentals they’re supposed to reflect!

I agree with Soros’ theory and believe it’s a better framework with which to approach the markets on a macro level. There certainly is a “herd” mentality in the markets, a self-feeding, two-way channel – people’s perceptions of reality dictate prices, these perceptions in turn can directly affect the underlying fundamentals themselves in a self-fulfilling way, yet the prices still reflect the underlying prices. It’s a continuous give and take, with each side (people/prices and fundamentals) affecting the other.

The US dollar ultimately works because of people’s faith in the US government and confidence that others will value it as a medium of exchange. Imagine for whatever reason, a significant group of people stop believing in it for whatever reason, despite there being no legitimate underlying reason to do so. Others see these actions, panic, and act similarly. Eventually, what originally started as something with no basis has a real effect on the actual US dollar. Fundamentals didn’t cause the initial reaction, it was simply people’s perception of it (whatever reason it may be), which cascaded to a point where it actually did affect the underlying fundamentals. This reflexive relationship, in varying degrees, happens every day in the financial markets.

The Theory of Reflexivity better explains why we have significantly more booms and busts in the market than standard market theory would statistically predict. These assumptions are what brought down Long Term Capital Management in the late 90s, when their models assumed that extreme tail events would be very unlikely to happen, when in fact, they happen more than expected because people/prices and fundamentals are a two-way street. Soros quotes John Maynard Keyes, saying that the stock market is like a beauty contest, the winner isn’t the most beautiful contestant but the one whom the greatest number of people consider beautiful.

For Soros, this mental framework gives him the edge. One more thing I found interesting that was quickly mentioned then passed in the book was that Soros strives to have a “heightened state of self awareness.” I believe you reach this when you filter and recognize patterns/connections/relationships/etc. from a bounty of information to formulate conclusions at a pace and level of ease where you’re completely locked in.