What algo trading actually is
An algorithm, in trading, is a set of rules precise enough that a computer can follow them without asking you anything. A rule might read: if the 20-period moving average crosses above the 50-period moving average, enter a buy; exit if price falls 1% below the entry or the day ends.
Nothing about this is secret or magical. Algo trading does not predict the market. It removes one thing: the moment-to-moment decision of a person who might hesitate, chase or change their mind. The rules still come from you, and they can still be wrong.
The four parts of every rule-based strategy
If you can write all four down in plain sentences, you have a strategy a computer can run. If one of them is missing, the missing part is usually where the money is lost.
- Entry condition: what must be true before a position is opened, such as an indicator crossing, a price level breaking, or a candle pattern closing.
- Exit condition: what closes the position. This includes a stop-loss, a target, a trailing stop or a time-based exit.
- Position size: how much to buy or sell each time, set as a fixed quantity, a fixed amount or a share of capital.
- Constraints: when the strategy may act, for example only during certain hours, with a daily loss limit, or no new entries near the close.
The sensible order: idea, backtest, forward test, live
Most people who struggle with algo trading skip steps. The usual healthy sequence is to write the idea as rules, run it over historical data (a backtest), watch it on current data without real money (a forward test), and only then consider real orders at small size.
Each step answers a different question. A backtest asks whether the rules would have worked in the past. A forward test asks whether they behave the same way on data they have never seen. Live trading asks whether your broker, your costs and your own nerves match the assumptions.
What you need to start
- A clear written idea, however simple.
- Historical price data for the instrument and timeframe you care about.
- A way to test the rules with realistic costs, not just raw prices.
- A broker that offers an API, only when you are ready to go live.
- A risk limit you decided in advance, written before the first order.
Common mistakes beginners make
- Trusting a backtest that ignores brokerage, taxes and slippage.
- Tuning the rules until the past looks perfect, which usually means the strategy has memorised noise.
- Running a strategy nobody can read or explain, so no one knows why it entered a trade.
- Going live at full size on day one.
- Having no rule for what happens when the strategy is losing.
Why a visible strategy matters
A strategy you can read line by line is one you can question. When every entry, exit and limit is written where you can see it, you can find out why a trade happened and decide whether the logic still makes sense. Black-box systems that hide their logic ask you to trust something you cannot check. This is why MyAlgoAgent keeps every strategy's rules visible to the person who owns it.