Find the market with the right breakout structure, build a strategy point-and-click, and export it as a Python script that runs on your own data. Every strategy's tested in BreakoutOS before it reaches your code.
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The research happens in BreakoutOS. The finished strategy lands as a Python script you can read, run on your own data and build into your own research.
Breakout Radar scores each session of a market for breakout direction and how long breakouts typically last, so you start where the structure's there.
Hypothetical backtestBreakout Trading PRO builds and tests breakout strategies for that market, point-and-click, using the Mr Breakouts Formula. Pick the one you want to take further.
The export writes the strategy as a Python script using pandas and NumPy. The header lists the session and timezone settings your data needs to match.
Save it as a .py file next to your price data and run it. It prints a summary and saves every trade to a CSV you can check, chart or feed into your own research.
One strategy, backtested in BreakoutOS, then exported and run again as a Python script on the same data. The Python export reproduces the BreakoutOS results closely, so the code you run is the strategy you researched.
Hypothetical backtest
Hypothetical backtest| Measure | BreakoutOS | Python |
|---|---|---|
| Trades | 409 | 409 |
| Win rate | 57.5% | 57.5% |
| Average trade | +$287 | +$287 |
| Net profit | +$117,585 | +$117,585 |
The same 409 trades in BreakoutOS and in the Python script, with the same entries, exits and net profit. Hypothetical backtest results on both sides, not live trading. See the Hypothetical Performance Disclosure at the foot of this page.
The entry, the exit and the filters you tested in BreakoutOS, written out as plain Python you can read line by line.
The code header spells out the session and timezone the strategy was tested on, so the trades land on the same bars.
Small gaps can still come from your data file, its timezone or how its bars are timestamped. There's a guide inside BreakoutOS for tracking them down.
Strategies you've coded yourself, or a backtest from your own framework? A nice-looking backtest doesn't prove much, so import them into BreakoutOS Scale and put them through four tools.
Scores your strategy against a thousand strategies with the same DNA, across nine checks.
Finds out which indicators work best for your strategy.
Combines several strategies into one portfolio, so you see how they work together.
Gives each strategy a traffic light, so you know when to keep going and when to pause.
BreakoutOS does the research and the testing. Your Python runs the strategy on your own data, in your own setup. Here's how the two fit together, from picking a market to monitoring a portfolio.
Score each market and session for breakout potential.
BuildGenerate tested strategy candidates, without code.
BuildRun the script on your data, or build it into your own code.
PythonNine checks against a thousand look-alike strategies.
ScaleFind the indicators that work best for it.
ScaleSeveral strategies, one portfolio.
ScaleA traffic light for every strategy.
ScaleWorks across most major markets
BreakoutOS builds and tests breakout strategies on all of them. Which ones you trade depends on your data and your broker.
BreakoutOS Build has the four tools you need to go from a market to a strategy, with Python export on every strategy you build.
BreakoutOS Scale has the tools to audit, improve, combine and monitor the strategies you've already got, plus every Build tool.
Python is a registered trademark of the Python Software Foundation. BreakoutOS isn't affiliated with or endorsed by the Python Software Foundation.