OPEN-SOURCE SCRIPT
MLP - BTC Breakout Probability [Deep Learning] [Open Source]
I trained a single Multilayer Perceptron on 13 years of Bitcoin price history and open-sourced the result. Not because it's perfect, but because the idea is worth sharing.
The concept is simple.
Most breakout strategies are rule-based. Fixed levels, static conditions. This one is different, instead of predicting direction, the model learned the distribution of Bitcoin's daily price moves. You pick a threshold, it gives you the probability. Same model, any level.
How to use it
Pick a percentage threshold , by doing that you're asking the model to evaluate. When price breaks that level and the model is showing meaningful confidence, a label is shown on the chart.. Daily only. BTC only.
Under the hood
A lightweight Multilayer Perceptron (MLP) trained on ~4,700 daily candles of raw OHLC data from May 2009 to May 2022. The architecture is two hidden layers (16→8), ReLU activations throughout, and a sigmoid output that squashes the result into a clean 0–1 probability score. ReLU keeps the internal representations sparse and non-linear, sigmoid makes the output as a probability.
What makes this interesting is that the model didn't just learn a raw number, it learned the underlying distribution of Bitcoin's daily price moves. That's what allows a single model to answer probability questions across different thresholds rather than being hardcoded to one fixed level.
The output isn't a prediction, it's a calibrated belief about where price is likely to go, derived from 13 years of market structure.
Honest limitations
Fat tails eat this model alive. The features are correlated and the model has no concept of liquidity. It underestimates the extremes.
Daily timeframe only. Bitcoin only. Long only.
This was built as a personal project, mostly for fun and to serve as a working example of how ML concepts can be applied to market data.
Disclaimer
This indicator is provided for educational and informational purposes only. It does not constitute financial advice, trading recommendations, or a guarantee of future results. Past performance does not predict future returns. You alone are responsible for your trading decisions. Always test thoroughly in a simulated environment before trading with real capital.
The concept is simple.
Most breakout strategies are rule-based. Fixed levels, static conditions. This one is different, instead of predicting direction, the model learned the distribution of Bitcoin's daily price moves. You pick a threshold, it gives you the probability. Same model, any level.
How to use it
Pick a percentage threshold , by doing that you're asking the model to evaluate. When price breaks that level and the model is showing meaningful confidence, a label is shown on the chart.. Daily only. BTC only.
Under the hood
A lightweight Multilayer Perceptron (MLP) trained on ~4,700 daily candles of raw OHLC data from May 2009 to May 2022. The architecture is two hidden layers (16→8), ReLU activations throughout, and a sigmoid output that squashes the result into a clean 0–1 probability score. ReLU keeps the internal representations sparse and non-linear, sigmoid makes the output as a probability.
What makes this interesting is that the model didn't just learn a raw number, it learned the underlying distribution of Bitcoin's daily price moves. That's what allows a single model to answer probability questions across different thresholds rather than being hardcoded to one fixed level.
The output isn't a prediction, it's a calibrated belief about where price is likely to go, derived from 13 years of market structure.
Honest limitations
Fat tails eat this model alive. The features are correlated and the model has no concept of liquidity. It underestimates the extremes.
Daily timeframe only. Bitcoin only. Long only.
This was built as a personal project, mostly for fun and to serve as a working example of how ML concepts can be applied to market data.
Disclaimer
This indicator is provided for educational and informational purposes only. It does not constitute financial advice, trading recommendations, or a guarantee of future results. Past performance does not predict future returns. You alone are responsible for your trading decisions. Always test thoroughly in a simulated environment before trading with real capital.
Open-source Skript
Ganz im Sinne von TradingView hat dieser Autor sein/ihr Script als Open-Source veröffentlicht. Auf diese Weise können nun auch andere Trader das Script rezensieren und die Funktionalität überprüfen. Vielen Dank an den Autor! Sie können das Script kostenlos verwenden, aber eine Wiederveröffentlichung des Codes unterliegt unseren Hausregeln.
Haftungsausschluss
Die Informationen und Veröffentlichungen sind nicht als Finanz-, Anlage-, Handels- oder andere Arten von Ratschlägen oder Empfehlungen gedacht, die von TradingView bereitgestellt oder gebilligt werden, und stellen diese nicht dar. Lesen Sie mehr in den Nutzungsbedingungen.
Open-source Skript
Ganz im Sinne von TradingView hat dieser Autor sein/ihr Script als Open-Source veröffentlicht. Auf diese Weise können nun auch andere Trader das Script rezensieren und die Funktionalität überprüfen. Vielen Dank an den Autor! Sie können das Script kostenlos verwenden, aber eine Wiederveröffentlichung des Codes unterliegt unseren Hausregeln.
Haftungsausschluss
Die Informationen und Veröffentlichungen sind nicht als Finanz-, Anlage-, Handels- oder andere Arten von Ratschlägen oder Empfehlungen gedacht, die von TradingView bereitgestellt oder gebilligt werden, und stellen diese nicht dar. Lesen Sie mehr in den Nutzungsbedingungen.