April 29, 2016 

In a LinkedIn forum I participated from time to time there was this statement: Why it's not possible to teach most people to be successful (primarily related to automated trading). To see the thread follow the link. (Sorry, the link does not work anymore).

I somewhat disagreed with the initial appraisal. I did have a different take on it.

That thread initially implied that there is this 1% that made it (trading profitably, that is) when even that was not demonstrated. The other 99% were considered "rookies" from whatever profession they might have come from and who have somehow to learn the ropes, somehow.

For sure, a trader is in it for the money. No one is going out there saying: hey, I intend to be part of the worst traders you could find, be part of the 99% that lose. So, please send me a lot of your money. I will make every effort to lose it as fast as I possibly can. You will be able to see firsthand how efficient I can be at it, and you will be able to experience my limitless ability to generate excuses for "your" losses. To show you how much I care, I won't even put a dime of my own so as not to interfere or generate a conflict of interest, how about that!

No, a trader has a prime objective to make money as fast as possible, with the least risk possible, using the fastest and easiest trading methods he can find or develop on his own. A trader wants his automated trading strategy to simply print money and lots of it. He knows it is not easy, but he is ready to work for it and even program his own system if needed. Thereafter, he will want to closely monitor his "machine" as it does its job.

If most traders fail, it might be that what they were taught was not good enough to make them win.

As if implying that most of those discretionary unproven short-term trading systems, with their well-chosen examples, had no justifying or statistically relevant data to corroborate the claims. But, in that department, practically nobody does any kind of long-term testing. Why provide corroborating long-term evidence of any kind if you can get away with it without doing so?

Those trading courses for "educational purposes only" might be just that: for "educational purposes" only. A way to pass the time, a form of "paid for" entertainment. I know I could put out generalities, market folklore, and clichés for hours on end. Most probably, a lot of you readers can do the same.

I would ask this question: did the 99% all fail because of too high expectations or because they tried to apply stuff that did not work in the first place? And if such was the case, what were they taught, except maybe stuff that really did not work!

It is not that students taking those courses were not bright enough or that they lacked skills. They might simply have been too naive, believing in what they were being taught as valid, even if it was crap.

So, when they tried to apply all that educational "stuff" in real life, their portfolios were just decimated, and for good reasons. Well-chosen trade examples appear so evident in hindsight that some think that it is how the market works. Surprise, it does not work as the examples shown, not that consistently. But there, no one wants to put the stats on the table, it would tend to ruin the "course", of course.

Another reasonable reason why short-term traders lose might be due to the very nature of short-term price movements. A misunderstanding of how prevalently quasi-random-like short-term prices really are.

This would be the perfect excuse which does save, in a way, the short-term trader. It's not his/her fault if luck was not on their side. It is not as if they misread the market or the price movements; it is just that luck was not there, and they lacked coincidence. If short-term prices have a high degree of randomness, they might appear as nearly Gaussian when looked through a small sigma window.

Flipping a biased coin to outguess a randomly biased and skewed coin-flipping series will simply not give an edge to anyone wishing to play the game. But still, some can win by luck alone.

Don't look at it as some kind of talent or skill when it is just luck and nothing more. The expected value of a coin-flipping contest is still zero, and if your automated trading strategy behaves like a coin-flipper, then you should not be surprised at the output. Your trading methods need a foundation in reality that goes beyond randomness. You need to look at the long term.

Still, "rookies" have to and need to learn even if, at first, it is to learn to lose, or maybe they have to lose to learn.

If they can stick around long enough, the game will teach them how to play, but they should be aware there are tuition fees. And learning the game can be very expensive, as well as rewarding.

The novice has a hard job. He will be dealing with a secretive world where he has to reinvent almost everything that might be worthwhile since most of the interesting "stuff" is part of someone else's intellectual property. And those programs, good or bad, are not necessarily given away. Like in everything else, there is a learning curve. It is just that, in this case, you could be paying for that course of yours for quite a long time.

So, my recommendation is: test everything yourself, and over the long term. See first if a proposed trading strategy can last, since if it breaks down before reaching your goal, game over, you lost.

Take a look at my last two articles; the last one (a two-part article) was on a published trading strategy that turned out to be bad and destructive long term, while the other (a five-part series) took a mediocre and non-productive strategy based on the same common indicator and gradually transformed it into something worthwhile long term.

It is by doing the simulations that you can estimate if your particular trading strategy can stand a chance going forward. And any trading strategy should show, as a minimum, that it could have handled its past, not just its recent past, but the long term. Overall, it remains all up to you. It's your ride, it's your time, it's your money.

Created... April 29, 2016,    © Guy R. Fleury. All rights reserved.