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Models

Learn more about how the models work

1 - Creating a machine learning model

Go to models, click on the "+" button at the top left.
Then, you have to select an algorithm, data and parameters.
Select an algorithm with parameters :
SVM
XGBoost
This algorithm stands for "Support Vector Machine".
The parameters available are :
This algorithm stands for "eXtreme Gradient Boosting".
Here is a famous scientific paper that demonstrates the effectiveness of XGBoost (combined with ARIMA) in predicting the stock market : WANG, Yan et GUO, Yuankai. Forecasting method of stock market volatility in time series data based on mixed model of ARIMA and XGBoost. China Communications, 2020, vol. 17, no 3, p. 205-221.​
The parameters available are :
Select a data source:
Broker
Exchange
  • Robinhood
  • Interactive Brokers
  • Charles Schwab
  • Alpaca Markets
  • TD Ameritrade
  • IG Markets
  • Oanda
  • Degiro
  • TradeRepublic
  • Samco
  • Tradier
  • Trading Technologies
  • Zerodha
  • Binance.com
  • Binance.us
  • Coinbase
  • Kraken
  • KuCoin
  • BitStamp
  • Gate.io
  • OKX
  • BitFinex
  • ByBit
  • Bithumb
  • Gemini
  • Bitget
Then select a granularity and a period. The longer the period, the longer the training but the more interesting the results.
Then click on "save".

2 - Training & backtesting the model

Click on the training icon and click on "Train & backtest", then wait.
Once your model trained (check your chat messages), you get the results.
The graph show the cumulative returns of the asset (BUY and HOLD strategy) in black and that of the model in yellow.
Below are (in order from left to right):