December 7th, 2016
Usually, when changing an automated stock trading strategy, it implies making changes to the trade selection process and trading rules resulting in changes to a portfolio's trading history. But, each time doing this brings changes to trading procedures, and these changes tend more and more to over-fitting the data.
The very process intended to improve a trading strategy might be moving it further and further away from reality. Often, even making it less valuable. Some go as far as actually destroying any chance a strategy might have had of ending with a profit.
November 25th, 2016
My last series of articles started with setting up the mathematical backdrop to a stock trading methodology made to last. Putting a stock portfolio payoff matrix at the center of it all as the bean counter for any trading strategy: A(t) = A(0) + Σ(H.*ΔP). This time function was then reduced to: A(t) = A(0) + n * u * PT.
Three numbers of interest: number of trades done, trading unit used, and average profit percent for trade. Three portfolio metrics given by any simulated, or live, stock trading portfolio whatever its composition. One could view n * u * PT as a trading strategy's signature.