Basics
Algorithmic Trading
Trading where entries, exits, and sizing are decided by explicit rules executed by a computer instead of judgment calls made in the moment.
Algorithmic trading (algo-trading) replaces in-the-moment judgment with a written set of rules: when X happens, do Y with Z size. The rules can be as simple as "buy when price closes above the 20-day high" or as involved as a multi-timeframe system with volatility filters and dynamic stops.
Why traders do it
The same setup gets traded the same way every time, without fear or greed changing the decision halfway through. Because the rules are written down, they can be backtested against years of historical data before any money is at risk. An algorithm will also happily watch every bar of a 1-minute chart around the clock, which no human can.
What it is not
A strategy is not profitable just because it is systematic. A bad rule executed perfectly is still a bad rule, which is why validation steps like forward-walk analysis and overfitting checks matter as much as the strategy idea itself.
On AlphaProve
The when X, do Y rules can be written three ways: a Python evaluate(ctx)
function that reads candles, indicators, and position state; a no-code JSON
builder that nests long and short entries as AND/OR condition groups; or one
of six builtin strategies chosen from a registry. All three run server-side
in a sandbox against the same backtest engine, and
the AI chat can draft the Python from a plain-language description and check
it compiles before you run it.