Stock Trading Systems DO Require Durability And Scalability
The two most important traits of any stock trading strategy should be its durability and its scalability. The first, so that the strategy does not blow up in your face during its entire trading interval. The second, so that a portfolio can grow and grow big.
When designing a trading strategy, we should look at where it is ultimately going. Especially in a compounding environment where time might turn out to be the most important ingredient of all. You need the answer to this simple question: how long can this strategy last?
In an automated stock trading system, the strategy is running the whole show. Its first mission is to outperform the market averages over the long term. Otherwise, why even start when you could have bought SPY and outperform your own trading strategy?
A stock trading strategy operates in a compounding return environment. The objective is to obtain the highest possible long-term CAGR (compounded annual growth rate). It should be adapted to your own set of portfolio constraints (preferences, available cash, the methodology used, and your acceptable risk limits).
Evidently, in all cases, the portfolio's payoff matrix is the same, and has quite a simple equation:
F(t) = F_0 + Σ (H ? ΔP) = F_0?(1 + E[r_m])^t
where E[r_m] is the long term average expected market return. The final outcome will be shaped by F_0, the amount you started with and t, the duration over which you managed to compound your portfolio. It does not say which strategy you took to get there, only that you needed one. It could have been about anything as long as you participated in the game, implying (H ≠ [0]). This is a crazy concept: you can win or lose, IF and only if you play.
In the above equation, you have no control over the price matrix P, but you do have total control over H, the trading strategy itself. You can buy with your available funds any stock at any time at any price for whatever reason in almost any quantity you want short of buying the whole company.
You already know that as time increases (20+ years), rm will tend to be positive with an asymptotic probability approaching 1.00 making the proposition almost surely. The perfect argument for: you play, you win. And in all probability, you get the expected average market return over the period just for your full participation in the game.
To Get More, You Will Have To Be More Creative!
My new article: Durability And Scalability explains how you get from the above equation to the portfolio equation below:
F(t) = F_0 + Σ (1+κ)?(1.05)?(H_a?(1+g_t)^t?ΔP) = F_0 + n?x_avg = F_0?(1+r_m+α_a)^t
The equation says you can control parts of your portfolio by adding some positive alpha. Also, such a trading strategy can be scaled to accommodate small to large institutional-sized players. Or, make the very rich even richer. The strategy can be scaled down just as it was easily scaled up.
The complete article: Durability And Scalability provides the equations, explanations, and some simulation results to demonstrate its feasibility. Please follow the link below to find out more:
https://alphapowertrading.com/index.php/2-uncategorised/355-durability-and-scalability
Related Article: Financing Your Stock Trading Strategy