Hey guys, this is my implementation of Renko Bars that are plotted with Live Data :-)
It is based on the brilliant work of Sergey Malchevskiy -
https://github.com/quantroom-pro/pyrenko and it is recommended to read -
https://towardsdatascience.com/renko-brick-size-optimization-34d64400f60e for a good understanding.
As you can see, I have added how to use it with historical data from OANDA and a demo account key to be used with the build_history function.
The optimal brick size is chosen from the second example, where the evaluate_renko function is used for the optimization by using optimal_brick_sfo. The Renko Bars are built with the best average value from the historical values of the ATR 14 - Average True Range.
The candles from the pricing stream are downloaded in a while loop and added to a pandas DataFrame above the while loop. They form the Renko Bars according to the current Close price.
After the data is added to the DataFrame I show how a working trading logic can be implemented. There is a function to create orders and the command to open Long or Short positions.
I hope you enjoy it!
Happy Trading :-)
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Needed packages:
Linux: pip3 install -U setuptools pip3 install numpy pip3 install matplotlib pip3 install TA-Lib pip3 install --upgrade ta pip3 install pandas_ta
more details on ta-lib: https://blog.quantinsti.com/install-ta-lib-python/#install-ta-lib-on-linux
Install TA-Lib with Windows: