blog/strategy-xgboost-classification-technical-indicators/

[allenfrostline]

http://allenfrostline.com/2017/03/12/strategy-xgboost-classification-technical-indicators/

Strategy: XGBoost Classification + Technical Indicators - Allen Frostline

[xFFFFF]

Can You share rest code?

[allenfrostline]

@xFFFFF Can You share rest code?

Thanks for the reply, but this is it. I'm using the RQAlpha trading engine by the time of this post and all I need to specify here are the __config__ and the global function init. The engine then automatically backtests against the configurations and produces the output. If you've got your own trading engine or some other third-party one and don't want to bother reading the Chinese documentation of RQAlpha, I believe you can transplant this strategy smoothly there as long as you understand what it does. Therefore, please let me know if you find anywhere confusing in the code.

[renanfilipe]

Hello, thanks for sharing the code. I'm studying your code to try to learn more about XGBoost. What I understood so far is that you fed the model with historical data, with this data you built some technical analysis data and then you trained the model. My question is: How will I use your classifier if I don't know tomorrows OHLC? Can you share an example of you using your trained model to predict next's day average price change?

[allenfrostline]

@renanfilipe Hello, thanks for sharing the code. I'm studying your code to try to learn more about XGBoost. What I understood so far is that you fed the model with historical data, with this data you built some technical analysis data and then you trained the model. My question is: How will I use your classifier if I don't know tomorrows OHLC? Can you share an example of you using your trained model to predict next's day average price change?

Hi @renanfilipe, it's a very simple strategy targeting at whether the long-term trend of a stock is up or down. Check how context.signal is defined and manipulated.