Gaussian Weights - Market Analysis for Jan 18th, 2018

This post is for Pegasus, he has requested information about how to compute weights based on assumptions of a normally distributed factor. 

The process is very simple, first take the factor that you want to use and analyze the distribution for example this one:


That distribution is mostly centered around 5 with a couple a big outliers so the weights should reflect that.

1. Compute the mean and standard deviation:

mean = 5, sd = 2.318405

2. Rank each value based on the probability density they have, here is the list of densities for each value:

0.03884446 0.15679108 0.16812061 0.17207621 0.16812061 0.16812061 0.16812061 0.17207621 0.01681642

3 Finally normalize using max density to get the weights (divided everything by the max on the previous list):

0.22573984 0.91117231 0.97701252 1.00000000 0.97701252 0.97701252 0.97701252 1.00000000 0.09772661

Those are the weights to be used.  Please let me know if you have any other questions.

Leo Valencia hosts the Gamma Optimizer options service at