Purpose: Real-time stock/crypto data from Binance, Bybit, or any WebSocket source.
This plugin solves the biggest headache for retail traders: affordable real-time data. It subscribes to public WebSocket streams and pushes ticks directly into Amibroker’s database.
Key Features:
Installation: Copy the DLL into C:\Program Files\Amibroker\Plugins. Then configure config.json with your WebSocket URLs.
After loading the plugin, use in AFL:
// Returns last close price multiplied by custom factor
factor = 2.0;
result = MyCustomScaler(Close, factor);
Plot(result, "Scaled Close", colorRed, styleLine);
The ecosystem is shifting toward three major trends:
Exports AmiBroker databases to Feather format (fast, columnar). amibroker plugin github
Exposes AmiBroker’s OLE/COM interface via Python with extra performance boost.
AmiBroker has long been a favorite among retail and professional traders for its blazing-fast backtesting, customizable charting, and powerful AFL (AmiBroker Formula Language). But one of its most underrated strengths is its plugin architecture. Purpose: Real-time stock/crypto data from Binance, Bybit, or
Plugins allow AmiBroker to connect to external data sources, execute trades automatically, fetch real-time news, or even run machine learning models.
And where do developers share the most innovative, modern, and often free AmiBroker plugins? GitHub. The ecosystem is shifting toward three major trends:
Purpose: Real-time stock/crypto data from Binance, Bybit, or any WebSocket source.
This plugin solves the biggest headache for retail traders: affordable real-time data. It subscribes to public WebSocket streams and pushes ticks directly into Amibroker’s database.
Key Features:
Installation: Copy the DLL into C:\Program Files\Amibroker\Plugins. Then configure config.json with your WebSocket URLs.
After loading the plugin, use in AFL:
// Returns last close price multiplied by custom factor
factor = 2.0;
result = MyCustomScaler(Close, factor);
Plot(result, "Scaled Close", colorRed, styleLine);
The ecosystem is shifting toward three major trends:
Exports AmiBroker databases to Feather format (fast, columnar).
Exposes AmiBroker’s OLE/COM interface via Python with extra performance boost.
AmiBroker has long been a favorite among retail and professional traders for its blazing-fast backtesting, customizable charting, and powerful AFL (AmiBroker Formula Language). But one of its most underrated strengths is its plugin architecture.
Plugins allow AmiBroker to connect to external data sources, execute trades automatically, fetch real-time news, or even run machine learning models.
And where do developers share the most innovative, modern, and often free AmiBroker plugins? GitHub.
