Adrian Reid explains that systematic trading uses 100% objective, rule-based decisions (explicit buy/sell rules) which produce consistent trade signals. He contrasts this with discretionary trading, where subjective interpretation of many inputs leads to inconsistent decisions. Reid uses a Toyota factory analogy to illustrate consistency and emphasizes systematic trading’s advantage in risk management because rules can be backtested over decades of market data to quantify outcomes (e.g., wins, stop-loss hits, catastrophic drops) and inform position sizing and when to disable a system.
Chapters
So systematic trading is essentially rules based trading. You have 100% objective rules that tell you exactly when to get in and exactly when to get out. If A and B and C are true, you buy. If D or E is true, you sell. So they're logical rules that I have the rules and you have the rules. We get the same trades that make sense. So there's no subjectivity, there's no interpretation, there's just the rule says buy, the rule says sell. Now this is really important because one of the biggest mistakes and risk management issues that traders face is not knowing how good or bad things could be. Now, a lot of discretionary traders, they make decisions by looking at some indicators and reading some articles and getting some advice and some tips, and they bring it all together and they try and make a decision based on all of the different inputs. Now, if we've got lots of different inputs and it's all going through our internal psychology, then the outputs become inconsistent. And this is a real problem because depending on how we're feeling, we interpret information differently and we make different decisions. Now, can you imagine a production facility like a factory? Imagine Toyota cranking out Toyota Corollas, Camry, Hilux, and every day they make them slightly differently, depending on how everyone is feeling. It would introduce huge risk, huge inefficiency, blockages, mistakes, losses into the system. They don't do it that way. They make the same car the same way every day, every time following a process, right? And then they look at that process and they say, okay, where are all of the risks in that process? Machine breakage, person fail, stock levels, etc. And they manage those risks. In systematic trading, it's similar. We have a system which is like the factory that produces trade signals. The system scans the market, finds the stocks to buy, tells you to buy them, tells you how much to buy. You place that trade, and then it tells you when to get out, you place that trade. The great thing about that is it makes your decisions consistent and it allows you to test the rules to see if they're actually profitable and to see what could go wrong. And this is where systematic trading has a huge edge in risk management over discretionary trading. Because when you have rules, you can run tests with historical market data. We have 30, 50 years of data, depending on which exchange we're talking about. We can back test our rules over all of that data and find everything that happened, all the trades, how good they were, how bad they were, how many hit their stop loss, how many times a stock went to zero, how many times, a stop gap down all of those things. And we can build that into our analysis and say, based on all of the history, how much should I risk on each trade? How much should I allocate to this system? When should I turn this system off? You can start answering questions that you cannot answer if you're trading with a discretionary approach.
