The Quantitative Trading Industry
8 min read
Quantitative trading is trading in which decisions, what to buy or sell, at what price, in what size, at what moment, are produced by models and executed largely by machines. It is not a niche: in liquid electronic markets the majority of volume is now algorithmic, and the industry built around that fact employs mathematicians, statisticians, and engineers to do what was once done by voice and intuition.
Systematic trading driven by quantifiable signals and rules: hypotheses about prices are formalised as models, tested on data, and executed by software, with humans designing, supervising, and improving the system rather than making trade-by-trade calls.
How the industry got here
The enabling changes were structural, and each is a fact met earlier in this track. Markets electronified: order books became data structures reachable by machines, and the exchange floor's information advantage dissolved into feeds available to any connected participant. Trading costs collapsed: smaller ticks and competition compressed spreads, making high-frequency, small-edge strategies arithmetically viable. Computation and data became cheap: strategies that require estimating thousands of parameters or scanning every listed instrument continuously became routine. The result is an industry where the marginal price-setter in most liquid instruments, most of the time, is an algorithm.
The statistical heart of the business
Small edges, many trials
Expectation grows linearly in the number of independent trades while spread grows as the square root: the law of large numbers is the industry's production function.
A strategy wins 1 or loses 1 with 51 percent win probability, 10,000 independent times:
A two-sigma-positive expectation from a coin barely better than fair: repetition converts a nearly invisible edge into a reliable one. The whole track's probability spine, expectation, variance, the CLT, is this computation, and the industry is organised around finding, verifying, and scaling edges of exactly this size.
The same arithmetic explains the industry's inputs. Finding a 51 percent coin among noise requires statistics done honestly (the overfitting lessons); executing 10,000 times without the edge leaking requires market microstructure and technology (the markets course); and sizing it without ruin requires the risk arithmetic (Kelly, drawdowns, margins) this track has built. Quantitative trading is those courses, operated as a business.
Quick check
A strategy makes 10,000 independent unit bets at a 51 percent win rate. What is its expected total profit in units?
Quick check
Same strategy: what is the standard deviation of the total, in units?
Practise this