I should have phrased my point on smarts differently. You definitely have to be bright to make money trading; there is a baseline and it's pretty high. Beyond t

I should have phrased my point on smarts differently. You definitely have to be bright to make money trading; there is a baseline and it's pretty high. Beyond that, the most valuable things are attention to detail, working well under uncertainty where the best answer isn't obvious or even knowable, and simple hard work. Aside from systematic errors like Knight, market-makers rarely blow up due to competition or a bad model, they just fade away. They make or lose money pretty slowly, they just do it consistently over time. Aside from the most basic strategies there isn't one "right" way to price a market. It's an engineering problem like any other. How much risk do I accumulate? How should I manage this risk? How far apart should I set my bid and offer? Do I use a simplistic model with lower latency or a more complex one that's slower? Is it better to be more accurate and avoid bad trades or less accurate and build up priority in the order book by staying on a price longer? A market-maker's objective function is to maximize total profit (turnover * average gain/$ traded) while controlling risk (volatility of P&L over time). Usually changing your answer to questions like the ones above will shift turnover one way and profit per trade & risk in the opposite direction. For example, if you quote your bid and offer very close together, you'll trade large market share and have less risk exposure since you get in and out of positions very quickly, but your profit per trade will be low (if traders arrive randomly, at best you will make the small spread between your bid and offer, in reality a fraction of that since they usually have a reason to trade against you). If you set your quotes wider, you'll make more per trade on large dislocations, but do less volume and hold more risk. There are a lot of efficient points along this continuum and traders play to their strengths. Someone with little capital/risk tolerance, top-tier infrastructure, and forecasting models for the next price tick should play very differently than someone with a lot of capital, average infrastructure, and models that can forecast the next 10 minutes. And you are right regarding bonuses, but all team efforts have this problem. Who creates value and deserves the best compensation in a SaSS startup? Is it the salespeople who get clients? The engineers who build the software? The Ops team that keeps it running reliably? I actually find trading to be a bit more meritocratic than other tech jobs: either you make money or you don't, and teams are smaller so it's easier to assign reward (or blame).