Can you suggest a good advisor? - page 2
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How do I sort the "freebies" by popularity?
How to sort 'free' by popularity?
There are so many EAs in the marketplace, even some to test...
I would like to know which are the most popular ones. We will test them.
EUR/USD
Who uses which Expert Advisors?
The answer to this question is obvious: everyone uses the Expert Advisor that he or she understands the most.
In other words, it's not a question of whether an EA is good or bad, but where the user's hands and head are growing from.
I, for example, cannot dance, which means that my scrotum systematically prevents me from doing it. But this does not mean that the choreography sucks, it means that I'm a sucky dancer.
It's the same in algotrading. There are no bad advisors, but there are shitty dancers.
Beginners, i.e. those who do not have any competence in matters of not only automated trading, but even manual trading, prefer to use Expert Advisors with martin. The reason is simple: the balance seems to be systematically and automatically growing, while the probability of losses seems negligible. And it goes on until it becomes clear that a negligible probability can wipe out a negligible large deposit and it is obviously foolish to neglect this small probability. And this process cannot be controlled by the presence of martin in the algorithm, because martin does not provide any risk management, letting the matter drift away.
Thus, by stepping on a rake, the competence gradually increases, and you understand that the risk is also possible to manage, but you need to know how to do it. At this point, the search for information on risk management begins. And, algotraders' arsenal will widen to include reliable, but nonetheless more reliable and, what is more important, controllable (i.e., controllable). Now, algotrading is no longer a gambling addiction, but something more meaningful.
Of course, more advanced traders, because of their low competence still believe that "the simpler the Expert Advisor, the better it is". But in fact, this is not the case. The simpler the algorithm of the Expert Advisor, the more understandable it is to a semi-literate person, and not because it is better. Simple Expert Advisors are usually divided into two elementary categories: trend following and counter-trending. This leads to the addiction because if we set a trend following Expert Advisor and the trends prevail, we will profit. But in case of prevailing of the sideways trends, the losses are inevitable.
But having learned on his or her own mistakes, the algotrader comes to the point where there are more independent of the market trends. But they are not as simple as ones that the programmer has been using so far and therefore, additional competence is needed to configure them. Again the search for information is started in order to fill the gaps of this very competence.
And so on and so forth.
Of course, the more advanced algotrader, due to his or her low competence, still believes that "the simpler the Expert Advisor, the better it is". But in fact, this is not the case. The simpler the algorithm of the Expert Advisor, the more understandable it is to a semi-literate person, and not because it is better.
Hmmm... And I thought simple Expert Advisors (or rather, not Expert Advisors, but TS) were better because they have fewer degrees of freedom and are less prone to "tweaking to the curve".
When it seems, one must be baptised © Folk proverb
Such hypothesis, i.e. that supposedly redundancy of degrees of freedom will "necessarily" lead to low generalizability, is stated in the Pattern Recognition Theory of V. Vapnik, A. Chervonenkis.
In fact, such a theory is wrong in principle.
If one wants to approximate "clean" data, say given tabularly with a small error, e.g. a sine wave, the curve will be smooth. In that case, the better the algorithm adjusts to the curve, the better.
If the data in the sample is "dirty" then the results will also be "dirty". Rubbish on the inputs is rubbish on the outputs.
Another thing is that there is no need to approximate pure table functions in application areas. Most often it is necessary to approximate the results of experiments. But there is no curve there, but a set of points scattered chaotically and crowded together in places where the curve should be. Nobody forbids to dissect, i.e. to pre-smooth these very scattered points into a curve using some algorithm suitable for this purpose before adding them to the inputs. I.e. pre-clean the rubbish and not feed it to the inputs. And then large degrees of freedom of the algorithm will not only prevent a more accurate approximation, but will only contribute to it.
Leonardo da Vinci: "Simplicity is the hardest thing in the world; it is the ultimate limit of experience and the final effort of genius.
I, too, thought that if the result is achieved by simple means, it is the highest degree of craftsmanship. Too bad we both turn out to be wrong).Hmm... I thought simple EAs (or rather, not EAs, but TSs) were better because they have fewer degrees of freedom and are less prone to "tweaking the curve".
I would choose EAs that have monitoring or signals. You can fit anything in a tester. And as for simplicity, what would you prefer for mobility, a simple scooter or a complicated but efficient car? :))