What algorithmic trading actually is
Strip away the hype: algo trading is just encoding a decision process into rules a computer can execute without you.
Algorithmic trading is the practice of turning a trading decision into explicit rules that a computer executes for you — when to buy, when to sell, how much, and when to stop. That is the whole idea. Everything else in this course is detail hanging off that sentence.
It is not a magic money printer, and it is not (necessarily) high-frequency trading run by hedge funds with microwave towers. At its core it is *automation of a process you could, in principle, do by hand* — just faster, without emotion, and testable against history.
Why encode it in code at all?
- Consistency — the rules run the same way at 3pm on a calm Tuesday and during a crash. No fear, no FOMO.
- Testability — you can replay a rule over 10 years of history in seconds and get an honest estimate of how it behaved.
- Scale — one script can watch 50 instruments across 3 exchanges without getting tired.
- Speed — it reacts in milliseconds, not the seconds it takes you to notice, decide, and click.
The three families you will meet
Most retail-accessible strategies fall into three buckets, and this course teaches you to build in all of them:
- Trend / momentum — "the trend is your friend": buy things going up, sell things going down. Simple, robust, painful in choppy markets.
- Mean reversion — "what goes too far comes back": fade extremes, bet on a return to average. Great in ranges, dangerous in trends.
- Breakout — trade the moment price escapes a range, betting the move continues.
What algo trading is NOT
In the next lesson we go one level down: how a market actually fills your order, because your strategy lives or dies on details like the spread, slippage, and fees.