Distribution Rank Purchase filter to Maximize option trading wins

Wins at option trading can be maximized by using Distribution Rank as option purchase filter.

When using Distribution Rank as a option purchase filter the best rate of winning for SPY Call options occurs when the 10 day distribution rank is 70% to 85%.  The winning rate is at this level can be 3 times higher than when the distribution rank is between 15% to 45%.   This shows the buying at the lowest possible price will not produce the best ratio of option trading wins. Continue reading “Distribution Rank Purchase filter to Maximize option trading wins”

KNN and Ensemble for stock price prediction

Applying KNN to stock price prediction

© Jan-25-2014 Joseph Ellsworth All Rights Reserved    http://bayesanalytic.com/   phone-number-for-bayes-analytic

How to apply KNN (K-nearest_neighbors) algorithms to predict future stock price movements.  How to combine KNN,  score normalization and  and Ensemble techniques for trading predictions.

See my newer work for a Quantized Classifier.    It is much faster than KNN and can deliver comparable or better results in many situations.   The code is freely available on BitBucket and I released it under MIT license so it is safe to use in commercial projects.   I hope you will buy our consulting services to help solve your problems but feel free to use the code anyway.    There is also free code showing how to read and classify machine learning CSV files using Deep Learning from TensorFlow.    Continue reading “KNN and Ensemble for stock price prediction”