Topics In Queue

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Please respond with your votes for potential articles.   I do modify when I will write various articles based on reader feedback.

The following Articles are in queue:

• Stock profit without Risk Option Hedging Strategy
• How hour purchased changes profit from stock option trade
• Initial results from Herding Behavior as Stock Selection Metric
• 10 rules for viable traders
• Option trading how Day of Week win rates change across time
• Bayes Analytic Engine Prediction versus Win Reality
• How day of week affect option trade profitability for the hour purchased
• Optimal hour to purchase call options for 25 popular stocks.
• Optimal day to purchase call options for 25 popular stocks.
• Worst hour to purchase 25 popular stocks
• Worst day to purchase 25 popular stocks
• Suppressing Manipulatory option purchases from input data in trading optimizers.   –
  • Early in our testing process we found there where a number of option purchases which seemed designed to fake a move in a given direction so unsuspecting buyers would jump in and either buy or sell at a price that did not reflect local market reality.      We found that these can falsely bias the statistics and it produced superior and less expensive results simply by filtering them than modifying the statistical algorithms to accommodate them.    This is part of the process we use to eliminate these so they do not falsely bias the statistics.
• Basic algorithm of trading strategy OptBayes1 –
  • This strategy is a purely statistical comparing  a large set of statistical features such as % above the 5 day low.      The core algorithm computes the statistical score for every trade we have available and then analyzes which trades have been successful across time.   The process of training is basically used to measure each statistical feature score as either a success or failure for that trade.     These are used to compute a raw probability for each new trade for which we do not have enough data to determine success or failure.  Post processing and genetic optimizers are applied to further adjust how the scores are applied.
• Why statistically analyze options directly rather than the underlying stock
  • A simple but incomplete answer is that we wrote 3 different analyzer engines  which predicted movement of options based on statistical features of the stock.  We found that these algorithms had a  high degree of accuracy for predicting stock movement but the relative stock movements did not always accurately  predict option movement due to several external factors such as the overall market volatility and the general perception of market risk which can dramatically change the implied volatility of the underlying option.
• Conditions where Human Assisted Genetic optimizers can produce better results than pure statistical engines.
• How comparing two RSI time ranges can be used as a buy trigger
  • Ever found that discount stock you had been tracking for months waiting for the right time to buy it at a discount only to buy it and have it drop even more.   Well I found the experience distasteful and wanted to avoid it and started working on indicators or statistical features we could use with a higher degree of accuracy to determine when to buy in.    The idea is that these can be used to determine when a downward trend has broken and a stock is approaching a period of probable recovery.

Feel free to comment on topics you think should receive the highest priority.   Also please suggest new topics you would like articles on.

I welcome your suggestions on how to improve the articles.

If you know of content that is closely related to an article please send me the links and explanation of why it is relevant.    If I agree I will add the links to the article.

I  greatly appreciate suggestions for  better and more SEO friendly names of the topics in queue.

Thanks Joseph Ellsworth

(C) 2013 Joseph Ellsworth All rights reserved
This discussion contains forward-looking statements which are based on current expectations and differences can be expected. All statements and expressions are opinions of the author and are not intended to be either investment advice or a solicitation or recommendation to buy, sell, or hold securities. Many of these statements are based on sound economic reasoning, however actual response of the economy is heavily influenced by politics and large business and so the outcome could end up substantially different.