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I've been in the market for over a decade, and here's my take: - Lack of sophistication. "Classically" trained finance people don't know much about computers. I took a finance class at a top business school, and it's nothing compared to Engineering. A bit of time-value-of-money and maybe some option math, but really it doesn't come close to the sophistication of a CS or Engineering course. I went to a meeting last week with a guy who wanted an automated trading system. He hadn't heard of Python. He didn't have any idea how to execute other than on 3rd party programs (which of course use algos, but he was just providing the decisions). - Lack of scale. There's a lot of family offices who have a few tens to hundreds of millions of dollars. If they wanted an algo trading guy, they'd have to pay him a lot of money, you'd want more than one, and you'd need infrastructure. Plus there's the risk you get all this, hire the guys, and their results are no better than random. A lot of small fortunes like this tend to spend more time in tech-soft areas, like private equity or private debt. The stock trades are an afterthought that they can't spend much resource on. - Two kinds of decision making: arbitrage and investment. The put it bluntly, arbitrage is easy to mechanize. If some guy quotes some options at the wrong value, it's obvious you want to trade with him. There's looser arbs (things that sort of always come back to normal), but the principle is the same. In some sense, it's not a financial challenge, it's a technological one. For investment (I think XYZ corp will go up), you need to have a sense of what risk you want to take. Utility functions are not easy to put into code. You can try, but you end up with situations where you decide not to have the algo on. There's also the principal-agent problem; most traders are agents, they need to look good to their boss. They need to be able to explain why they are betting on some company. Often, more effort goes into how to justify your trades than what trades to do. - Things that can't go into a machine: I worked with a guy who used to go meet the CEOs, look them in the eye, and ask them if they'd make money. Now I'm not saying this approach works, but if this is your investment edge, how are you ever going to put that in a machine? - Insider information: taking this in the loose sense, not the criminal one. If you're highly dependent on understanding some part of the market better than others, you may be better off talking and networking rather than coding. Goldmans are great at this. Every time you meet them, they offer a bit of info in exchange for yours. It lets them see things like the mortgage bubble before it happens, whereas a model would probably have issues due to the small amount of computerized data. |