- Analyzes the top 200 ETFs by volume according to etfdb.com
- Uses the machine learning algorithms of the WEKA package from University of Waikato, New Zealand
in particular the RandomForest and IBk classifiers.
- Uses the following stock technical analysis tools from ta-lib libraries by TicTacTec LLC.
to create various attributes based on optimized and correlated values of other ETFs for the same period.
- Bollinger Bands
- MACD - moving average convergence/divergence
- NATR - normalized average true range.
- PPO - percentage price oscillator.
- Stochastic Momemtum (not in TA-lib package)
- TSF - time series forecast.
- Uses the following classifications:
- Very Strong Sell - value of 0;
- Strong Sell - value of 1;
- Sell - value of 2;
- May be sell - value of 3;
- Weak sell - value of 4;
- Weak buy - value of 5;
- May be buy - value of 6;
- Buy - value of 7;
- Strong Buy - value of 8;
- Very Strong Buy - value of 9;
- Take the weighted average from all calls and then average again for a period of
5 days, 1-5 days, 6-10 days, etc... More weight is applied the closer the call is to the end of the period.
- The report only shows
- Strong Buy when average > 6.75
- Strong Sell when average < 2.25
See my video on this
Getting A More Precise Buy/Sell Prediction Classifier
Last updated 2020-07-01
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