May 30, 2017

A Stock Trading Strategy That Is Simply Gambling

My latest book: A Quest for Stock Profits. If you want more, you will have to do more... makes the point that the original stock trading strategy, on which it is based, was simply gambling. And this automated gambling was somewhat camouflaged in code as if trying to persuade people that it was trading based on some fundamental market data.

When in fact, it was just playing market noise.

To such an extent that it did not even outperform its benchmark. It was as if randomly trading on a swarm of stocks. It is understandable since the trading method was much like having a monkey throw darts at the financial section of the newspaper where the most expected outcome would be tending to the market's average. Resulting, as should be expected, into a long term no alpha scenario.

This analysis might appear severe, but, let's see and call things as they are.

The modifications I made to the program were only to enhance this gambling notion. As if saying, if you want to gamble, at least play to win.

Winning at the stock market game is a blurry notion. You can make money, no problem. But, you have to compare whatever you do to a benchmark. And if your efforts do not result in higher profits than the said benchmark, then you have done a lot of work for nothing. That is where the winning comes in. Your efforts, your program has to generate more profits than just buying low-cost index funds. Making some money is not enough. You have to generate some alpha.

To show that your efforts resulted in more than just a random occurrence, you have to exceed by a considerable margin what the market would have given you for practically nothing, just for participating in the game for a long time.

The original trading script defined a 90-day regression line as a trend. As if there was such a thing. One can draw a line on any chart; it does not make it necessarily predictive.

It is just a line that at most can say something about past data, not what is coming next.

It should be evidently clear: there is no 90-day trend. It is a line you draw in the sand, and the market does not and will not even look at it. It will just go its way with no consideration for your "trend".

Linear Regression as Trend Line

That you draw a line on a chart does not make it a prediction! At most, maybe a guess, an excuse.

It remains just a line, and when it ends at the right edge of a price chart, you are simply at the right edge of a chart as everyone else.

You are facing an immediate quasi-random future path with a high degree of uncertainty. This is where gurus can give you this wonderful advice: the price will go up tomorrow if it does not go down.

If there was anything predictive in a 90-day trendline, it would be the equivalent of a self-defined free lunch.

The market usually offers few of those, and usually, they do not last. They are rapidly arbitraged out. One has to consider that the whole premise of the 90-day regression has practically no strategic value. Then, what could be its use?

However, if you draw 90-day trendlines for all the stocks all the time, you will find more of them going up than down over extended periods of time. Not as a predictive tool, but simply as a classification of what you see.

Sorting by Price

That you sort stocks by price, or their logs, does not give an advantage either.

Nonetheless, the strategy is sorting on what might appear as recent accomplishments, and there is some value in that. Big companies got bigger for some economic reasons.

However, it might not be enough to outperform the market. This was clearly demonstrated in the original program simulation. No alpha generation whatsoever.

Tagging along is not how you generate excess returns.

In the original strategy, a trade could be triggered due to a penny move from up to 90 days prior. This in itself makes the trading strategy operate on what looks more like market noise. You should not base a trading strategy on fundamentals where a one-cent price move some 90 days ago has the ability to trigger a trade.

The original strategy is so sensitive to minor price changes that changing its rebalancing time by only a few minutes will give different answers.

Placing bets on such minimal market noise is akin to simply gambling your way out. Try giving probabilities on that, and you will find yourself at the right edge of the chart in need of the support of the above mentioned gurus.

There is practically nothing of interest in the original strategy as was presented. The first post in the forum where the original strategy was provided confirmed this with its test results.

Gambling Acceptance

Having established that the trading strategy is simply gambling, why not accept it as is? And play accordingly.

Find in the method of play what could transform the trading strategy into an alpha generating machine.

Note that this trading strategy is very wasteful of its capital resources, even after my modifications. It trades unnecessarily, has really bad trade timing, and will still trigger a trade from a penny move some 90 days prior. There is much to improve here.

But, nonetheless, it does have a redeeming quality.

By modifying its code, and accepting its gambling habits, you can make a lot of money. You will need guts, perseverance, and capital to do so, but you will get there a lot faster than everyone else.

My modifications accept the strategy's gambling stance. Sees that the stock selection process itself has some indirect advantages and that applying a submartingale strategy can generate some considerable alpha.

That is the whole purpose of designing automated stock trading strategies. It is to outperform, not just of a few days or weeks, but for years and years. You want to reach the finish with much more than just average performance. To do so, you need some alpha generation. Average performance is always available just by buying low-cost index funds.

Should it really matter that much that you are gambling to generate your alpha? Will you accept it, even if it is gambling? All the while providing you with better odds of outperforming the averages.

That is what my simulations showed, as a kind of proof of concept. You can change the trading strategy's behavior. There are many variants and improvements that could be made.

Yes, I admit and accept that my code also trades, should I say, gambles its way to the finish line. But then again, it wins, and it wins big. There are reasons for that too.

Related Articles:

A Quest for Stock Profits – Part I
A Quest for Stock Profits – Part II

Book:

A Quest for Stock Profits. If you want more, you will have to do more...


Created... May 30,  2017 © Guy R. Fleury. All rights reserved.   

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