What is quant trading?
Before any math, the big picture: what "systematic" trading actually means, why traders hand decisions to rules, and the honest reason most strategies you'll build won't work — so you can spot the few that do.
- The difference between discretionary and systematic trading
- Why rules beat gut feel — and what an "edge" really is
- The uncomfortable truth: most strategies fail, and that's normal
- The research loop every quant runs, from idea to (maybe) live
Two ways to trade
Every trader is answering one question — when do I buy and sell? — in one of two ways.
A discretionary trader decides in the moment. They read the news, look at the chart, feel the mood, and make a call. Their edge, if they have one, lives in their judgement and experience. It's powerful and very hard to copy — even for the trader themselves on a bad day.
A systematic (or quant, short for quantitative) trader writes the decision down as a rule precise enough for a computer to follow: "if these conditions are true, buy this much; exit when that becomes true." No mood, no improvisation — the same input always produces the same action.
| Discretionary | Systematic / quant | |
|---|---|---|
| Decides by | Judgement in the moment | A written rule |
| Edge lives in | The person | The rule (and the data behind it) |
| Can you test the past? | Not really | Yes — that's the whole point |
| Biggest enemy | Emotion, inconsistency | Fooling yourself with the data |
This course is about the systematic path — not because it's better, but because it's testable. If a decision is a rule, you can replay it over years of history and ask, honestly, "would this have worked?" That question is the foundation of everything that follows.
What is an "edge"?
An edge is any repeatable reason your strategy makes money over many trades — a tendency in the market that tilts the odds slightly in your favour. Not a crystal ball; a coin weighted to land your way 53% of the time instead of 50%. Over hundreds of flips, that small tilt compounds.
The catch: real edges are small, rare, and fade as others find them. Most patterns that look like an edge are just luck dressed up by hindsight. Telling the two apart is the single most valuable skill in this whole field — and it's why this course teaches honesty before it teaches strategies.
The research loop
Whether at a fund or at a kitchen table, systematic trading runs the same loop. You'll repeat it for every idea you ever have.
Notice where the loop spends its rigour: step 3, validation. A backtest that looks great (step 2) means almost nothing on its own — anyone can find a rule that fit the past. The honest question is whether it holds up on data it has never seen, after real-world trading costs. Most ideas fail that test, and that red arrow back to "bin it" is a feature, not a failure.
That's exactly what the rest of this course builds toward, and what our free tools and strategy teardowns do in practice: take a good-looking backtest and find out whether there's anything real underneath.
- Discretionary
- Deciding trades by in-the-moment judgement.
- Systematic / quant
- Deciding trades by a fixed, testable rule.
- Edge
- A repeatable reason a strategy wins over many trades — a small tilt in the odds.
- Backtest
- Replaying a rule over historical data to see how it would have done.
- Validation
- Checking whether a backtest's result is real, not luck or hindsight.
Where to go next
You now have the map. Module 1 gives you the small handful of statistics that make the rest of it click — explained with pictures, not proofs.
Try a tool while it's fresh
TeardownsSee the research loop run on real published strategies — what survives validation and what doesn't