Stock recommendations engine with Machine Learning and AI based optimization

Introduction to Bayes analytic Stock recommendations engine

The stock recommendations engine delivers maximum stock trading profit by finding the subset of current buying opportunities which offer the highest probability of producing the desired profit.    It combines hundreds of statistical measurements with proprietary trading algorithms to deliver a high degree of accuracy and trading profits.     Advanced trading algorithms  allow the system to adjust trading recommendations throughout the day to adjust for changing market conditions.

Designed to deliver maximum profit with least capital at risk

The Bayes Analytic stock recommendations engine is built around proprietary machine learning classification algorithms combined with custom designed trading algorithms designed to predict which stock offers a have the highest probability of success.     The trading engine can be applied to  price movements to determine which stock trades are likely to make the desired profit within the desired time-frame.

The same stock recommendations engine is used to determine which positions are rising in risk and should be sold to maximize profit while minimizing risk.

Engine also handles options trading

The stock recommendations engine has been used for options trading where it allowed discovery of correlations  we had not anticipated . For example buying any PUT option for SPY or CAT on a Monday or Tuesday is a bad idea but if you buy the same option on a Thursday you have a 82% better chance of a win.

Another example is that If you buy a SPY call in the 4th week (very last couple days) of the month then it doubles your chance of a win compared to the 2nd and 3rd week.    Other  stocks have unique characteristics which the engine automatically discovers and uses to find the best stock transaction opportunities.

The Bayes Analytic  machine learning engine  has demonstrated a high degree of success at selecting offers able to meet specific goals.  It has shown the ability to reject over 80% of offers unlikely to meet specific goals while retaining those most likely to succeed. It uses statistical classification, statistical inference techniques, custom designed filters and genetic algorithms to produce output that is optimized through the day to deliver the best results.

Technical details of stock recommendations engine

The Bayes Analytic engine works by analyzing statistical similarities for many measurement features to determine the similarity of current offers as compared to past offers.    It develops a ranking based on the known success of past offers.    It then uses this knowledge to develop a rank ordered list of the best offers for action by human buyers.

The core engines is has been extended with series of specialized algorithms and proprietary indicators which help the machine learning system deliver highly accurate results. It also uses genetic algorithms to adjust the statistical weight of various features to dynamically adjust its output to better optimize for maximized success rates.

This engine includes features which allow it to handle large rates of inbound data and still present near real time recommended purchases.

 

Required Disclaimer

Forex, futures, stock, and options trading is not appropriate for everyone. There is a substantial risk of loss associated with trading these markets. Losses can and will occur. No system or methodology has ever been developed that can guarantee profits or ensure freedom from losses. No representation or implication is being made that using this methodology or system or the information in this letter will generate profits or ensure freedom from losses.  Forex and Option trading can result in losses that exceed the original principal balance.

Hypothetical or simulated performance results have certain limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not been executed, the results may have under-or-over compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profit or losses similar to those shown.

Even results from Live cash trading can be subject to specific market conditions that may not repeat in the future and as such, duplicate results from future trading is unlikely to duplicate past results.    Changing the dollar amount traded can cause different behavior in live trading markets especially when trading large positons that can exceed the liquidity available in the market and cause changes in pricing behavior.

Bayes Analytic LLC provides software that can produce trading signals.  The customer is responsible for choosing a configuration and parameters for the software that meets their own goals.  The customer is responsible for conducting their own tests and only the customer can activate the software to start trading.   The software runs in an account the customer has logged into and then activated the software.   Bayes Analytic has no control of,  influence over or visibility to the signals specific to given user because we have no visibility into configuration parameters the user has chosen to operate with.    The Bayes Analytic software is provided without Warranty on a As Is, Where is basis.  It is the customers responsibility to test the software to ensure it meets their trading requirements.   Every time Bayes Analytic releases a new version of the software the customer should conduct new tests to validate the new version continues to meet their requirements because every software change could have unexpected side effects that may not be obvious until the customer has tested it in their environment with their configurations.   The Bayes Analytic software may run as a script inside of other software packages or talking to API that Bayes Analytic has no control of or Influence over so the customer should test entire ecosystem to ensure it meets their trading requirements.    Bayes Analytic may provide the software in source form since that is required by some trading systems but it remains the exclusive copyrighted property of Bayes Analytic and may not be reverse engineered or redistributed.    The customer is responsible  for choosing their own broker and installing the Bayes Analytic software so it can trade using the desired account.  Bayes Analytic has no control over or influence of the broker and many brokers have different ways of quoting spreads,  charging commissions,  flow of orders and latency of information.  As such a strategy and software that performs well at one broker may and probably will require changes to perform well at other brokers.  It is the customers responsibility to test the software with their selected broker to ensure it meets their trading requirements.

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