But isn’t there a strong financial incentive to try to understand why you’re doing what you’re doing, whether it’s an algorithm or a human executing the trades? Otherwise it seems very easy to lose a lot of money.

Sure. But the market structure of investing dilutes that incentive.

The people who are developing the most sophisticated quantitative techniques work for hedge funds and investment banks. For them, there are two ways to make money. You make money by charging fees on the assets you manage, and you make money on the performance of the fund. That split will give you a sense of why there’s a dilution of the incentive. Because even if your assets don’t perform well, you can still make money on the fees that you’re charging to manage those assets.

The rewards from those fees are so large that if you can sustain a story for why your technique is superior, you can manage assets for a long time and make a ton of money without having to perform well. And, to be fair, sometimes it takes a number of years before you know whether the quantitative technique you tried actually works or not. So even if you aren’t making money in the short term, you could have a reasonable story for why you aren’t.

At the end of the day, for the manager, it’s as important to gather a lot of assets as it is to run a successful strategy. And gathering assets can be largely a marketing game.