We’ve created a stock market that moves too darn fast for human beings.
—A former vice chairman of Nasdaq
First, the take home: Nearly all investment firms are using some form of algorithms and machine learning. The minor performance increases of one versus another generally do not outweigh the fees charged. Go with the cheapest no matter how much they brag about their tech.
Recently, my wife was listening to a book, and I happened to catch a little bit of the content, which focused on value investing. It was hitting on all the usual notes—buy and hold has never really been beaten—and there was the obligatory reference to some contact the author had with Warren Buffet. The part that made me chuckle was that stock prices are updated up to the second. Given the automation of the market, the notion of a second seems almost quaint.
There is a great book by Michael Lewis called Flash Boys, which describes high frequency trading in depth, but I will touch a little bit on the concepts mainly because I find the words associated with it hilarious. Essentially, trades can be made without any human input. Just put some rules in place and go, right? It reminds me of Ron Popeil, “Set it and forget it.” If a computer could learn the right rules, it could dominate and make me a bunch of money!
It’s important to note that this trading is wide-open to exploitation, but we can trust the traders to do the right thing, right? In a scheme reminiscent of Tom Sawyer, traders can “spoof” the market. They can place a ton of orders on a stock so everyone thinks it is in high demand; the price goes up, and since they are moving so fast, they can sell their stock at the high price and cancel their orders before anyone can blink an eye. Traders can also get ideas of stock changes that would be caused by their own customers and then position themselves quite nicely before executing the trades. Additionally, they can take advantage of the time it takes for information to transfer from one exchange to another, which is not a lot. All of this happens automatically. It can lead to a flash crash, which sounds more fun than it actually is. If everyone has automated rules in place, a mild fluctuation can cause a snowball reaction; the bottom will drop out of everything and pop right back up in a matter of minutes. An example of a mild fluctuation is a “fat finger error,” which refers to someone entering the wrong order information.
This sounds crazy, but there is a tremendous amount of competition for fractions of everything. The good news is that these are just fractions. A sophisticated trading algorithm is going to edge out competitors by only a fraction of a percentage, and most algorithms written by someone on a laptop in a Starbucks could at least compete. Data scientists often joke about the lengths to which some of us will go to get a point or two in performance on a model. A fraction may be a huge deal if you are working at a huge volume, but if someone is offering to increase your profits by 0.2 percent at a 2 percent cut, the math really does not add up. Go with the group that is keeping a really low overhead and passing this on to its customers because it is all automated now.
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