June 10, 2020
You want to win the stock trading game, even with all its uncertainty. However, it should not be just winning it. It should also be with a higher purpose. Maybe something like building up your own retirement fund or helping someone else build theirs. One thing you should want, no matter what you do in managing that stock portfolio, is to make sure you will win and make it so you outperform the expected long-term averages.
Outperforming the long-term averages is the only reason for you to undertake such a tasking endeavor yourself. Otherwise, simply buy a market average surrogate (such as SPY or some equivalent), or find someone that could do better than you which would have been more productive moneywise and with a lot less work.
Trading is a lot of work, especially if your stock trading strategy is designed to make over 100,000+ trades over the years, that this be done on a discretionary basis or performed by a machine. And if you choose to perform the work yourself, you should at least find ways to make sure you will do better than the other guy who simply bought SPY and opted to wait it out.
When you buy an investment fund, you are presented with passed performance results, and the assumption is made that you could achieve the same kind of return going forward. What is being sold is g, the expected return in the following equation: F(t) = F0 ∙ (1 + E[g])t, which is the future value of your investment (F0) should the expected return be realized over those (t) years. You want the highest expected return E[g] with the least risk possible, evidently.
Trading Is Not That Simple
However, in trading, the task is not that simple. You delegate the task to someone else, or you do it yourself, either on a discretionary basis or having a stock trading program do it for you. You know, even before you start, that the above future value equation will hold and that time might be the most important part of it all. What you do not know is your own future value of E[g] and how it will fluctuate over the years. But, no matter what you do, it will reach an endpoint that will materialize F(t).
Building a long-term portfolio is not a one or two year job, it is a long-term endeavor. If you play only for a couple of years, your return will be dependent on your starting date, and the above equation will still prevail. Your expected return E[g] will entirely depend on your trading skills but also, due to the limited time, on your actual starting date. Also, due to the limited number of years, you cannot expect that high a performance level.
In my last few articles, the importance of time was quite visible in the presented charts, and the pursuit of added positive alpha became the main objective for any trading strategy. Otherwise, a strategy would underperform long-term market averages, which would go against the primary objective. If you do less than long-term market averages, technically, you lose the game. That is simple too.
The Secular Trend
If the long-term secular expected market average is 10% (E[g] = 0.10) and you do less, how could you claim that it is better or that you had better results than the market average? If you want to outperform the long-term averages, you will have to do more, not less.
Here is the payoff matrix equation again:
F(t) = F0 + $X = F0 + Σ (H ∙ ΔP) = F0 + E[n] ∙ xavg = F0 ∙ (1 + E[rm]+ α)t
The main interest will be with the alpha in the last part of the equation. With an alpha of zero, you simply get the market's average return as expectation E[g] = E[rm]. It is the payoff matrix that will generate E[rm]. It will not change that all the equal signs will hold. We could state that your expected return depends on your trading skills: E[g] = E[rm + α].
Positive Alpha Needed
To increase performance, you need at least a positive alpha (α > 0). And due to the long-term compounding, even a small alpha value will make a difference, as shown in my last article. Here is that chart again:
Rate of Return – Normal Scale: Alpha = 4%
But, even there, you might want more. A 4% added alpha is not the upper limit.
The following chart is the same as above, except a line was added to show the relative impact of raising alpha further to 10%.
Rate of Return – Normal Scale: Alpha = 10%
The above chart gives an expected return of 20%: E[g] = E[rm + α] with rm = 10% and α = 10%. This is just 6% alpha points higher than the first chart. And yet, it does make quite a difference. Again, not so much in the first 5 to 15 years, but quite a difference in the last 5, ending by making 4.66 times more than the 14% scenario and 13.0 times more than the market's average long-term 10% CAGR.
Extracting 10% more than market averages should not be considered an undoable task. On the contrary, it should be your low-end objective. For instance, Mr. Buffett has achieved, over his long career, to maintain this 10% alpha advantage. So, why should you not be able to do the same by trading your own way to the top or doing even better?
In the last chart above, the lower three lines have the same value as in the first chart. What has changed is the scale. The top line has this 10% of added alpha instead of just 4%. And again, the last 5 years is where the reward is.
Make the following calculation where the first 15 years are compared to the last 15: F0 ∙ (1 + 0.20)30 - F0 ∙ (1 + 0.20)15 with F0 = $1M. You should get: $221,969,292. The last 5 years alone would give: F0 ∙ (1 + 0.20)30 - F0 ∙ (1 + 0.20)25 = $141,980,097. What you see in these calculations is the power of compounding, just as it is illustrated in the above chart. Also, if you wanted to use F0 = $10M, it would multiply those 2 numbers by 10.
You could do even better than the 10% alpha by designing trading strategies that you make to last over the investment period. You want to make it big. You will have to learn how to do it, even in the face of continuous uncertainty. And one thing you know from the above payoff matrix equation is that no matter how you do it, the equation will prevail.
Related Recent Articles:
Winning The Stock Trading Game
The Inner Workings Of A Stock Trading Program – Part III
The Inner Workings Of A Stock Trading Program – Part II
The Inner Workings Of A Stock Trading Program – Part I
June 10, 2020, © Guy R. Fleury. All rights reserved.