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”

Obey your Trading and Risk control rules

In an earlier blog entry I defined a stock strategy as a combination of   Algorithms + Goals + Symbols + Trading Rules.    It is tempting to take the output of the Bayes Analytic engine and apply the recommendation without obeying the rules.     Based on results from test trading earlier this year this is a very bad idea which can cause what is profitable strategy to be less profitable.      This concept is also draws from ideas described in  “When Good traders Loose“. Continue reading “Obey your Trading and Risk control rules”

Why Language Performance Matters & Some Measurements

An optimization pass that takes 10 minutes in one language could take 15 hours in the slower language.

I work from the philosophy that I want the highest performance I can afford but this is traded off against development costs and delivery time because a great solution 6 months later  may be less valuable than a good enough solution 6 months sooner.

Continue reading “Why Language Performance Matters & Some Measurements”

How Day purchased and Week of Month affects option trading sucess

The Bayes Analytic engine is designed to predict probability of success for a given offer to meet a goal.   In some instances the goal could be will a particular customer buy from a specific offer.   I originally designed the stock prediction Engine to answer the question of which recent trades have the highest probability of meeting a specific goal such as increasing in value by 23% over a 7 day period.   The idea was that if we treat every option trade like an offer if we could isolate the set of offers which provided the highest probability of reaching the goal then we could buy those and skip the trades which offer a lower probability of delivering a profitable trade. Continue reading “How Day purchased and Week of Month affects option trading sucess”

Bayes Analytic for Communications Companies

I have been working on analytic components which may provide benefits to AT&T wireless or similar companies.   AT&T is particularly interesting because they have multi-year relationships with their customers but do such a poor job of targeting communication (I say this based on personal experience).  AT&T marketing is actually alienating customers when they could have been adding value and building loyalty.  Continue reading “Bayes Analytic for Communications Companies”