Here the different Presentations are at different time as the progress of this research continued for the last 15 years. So the presentation MAY NOT be in sync with what we have today. As research continued new miles stones were archived and went on…..
There is no end to perfection and no limit either. Today we beat S&P by several folds easily but there could be a day when we do 100% Returns every year. We are not there yet but our next milestone of research continues…..
LIKE ANY RESEARCH ARTIFICIAL INTELLIGENCE ON EQUITY WAS ALSO A GRADUAL EVOLVING PROCESS. NOTHING HAPPENS OVERNIGHT. TO GET TO PERFECTION IT TAKES YEARS OF RESEARCH AND FINE TUNING THE ALGORITHM.
HERE I WILL TRY AND EXPLAIN THE JOURNEY OF THIS ARTIFICIAL INTELLIGENCE WHICH WENT ON FOR YEARS FROM CONCEPT TO REALITY.
A Profitable Strategy
- The concept of Breakout. Identify Breakout ahead of time was the goal.
- Currently, we are far better with ROI as shown on Presentation due to Shorting Strategy built in which was not then there.
- The velocity of Trade was already there but with time a lot improved. One can see on backtesting trade logs the average daily bar to settle is less than 3 or 4.
Machine Learning Intelligence and High-Frequency Trading
- Those were the days when the struggle was on to get accurate breakouts which generated profits.
- Increasing the Velocity was a key challenge then.
WGS Research Introduction for High ROI with Bear Minimum Portfolio Loss Technique
- This presentation goes back 10 to 12 years when I was plotting the concept of Breakouts vs. Velocity.
- Mitigating risks with equal thresholds etc.
- The presentation here was like artificial intelligence in primitive days when I was involved 100% with mathematical model formations. Statistical compilations and many more…..
- Where I came to the conclusion “Stock Trading is Not Gambling, But Purely Mathematics.”.
Real Money Trading with Strategy and Automation
- This presentation also goes back many years when I myself was trading with my OWN money to prove the concept to others.
- I wanted to prove myself 1st before I took this strategy to other convincing them the consistency of artificial intelligence.
- The hard part then was 1 out of 1,000 people ( who are investors themselves) using tradition techniques did not understand what was precision based trading. How precision can overcome human emotions?
- Still, a big challenge for investors to understand machine learning intelligence capabilities and why human emotions are not recommended. There is no consistency if humans trade.
IN OUR BACK TEST TAB ONE WOULD NOTICE THE CONSISTENCY FOR 20 YEARS and IT’S PATTERN.