Discussing the article: "Creating a mean-reversion strategy based on machine learning" - page 6
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Example of market modes. If an order opened on yellow, when changing the mode to red, will the order close?
This is very important, because the trend has already changed, and in your script it may be written in the condition to expect a stop loss
For the purity of the experiment it would be necessary to take equal takes and stops - the number of trades would not become less, and over-sitting (and shifted evaluation of correctness/profitability of signals) would be excluded.
For the purity of the experiment it would be necessary to take equal take and stops - trades would not become less, and over-sitting (and biased evaluation of correctness/profitability of signals) would be excluded.
The article was written not to get very useful tips, but to show an interesting approach. The code for independent experiments is given.
The approach is interesting and correct - nobody disputes it. I don't understand only why the default settings for the article are chosen to present the results in a disadvantageous light.
PS. While I was writing my reply, there was a note saying that you can't post something like this. I apologise if this is not what you want either.
The approach is interesting and correct - no one disputes it. What is not clear is why the default settings for the article are chosen to present the results in a disadvantageous light.
PS. While I was writing my reply, there was a note saying that you can't post something like this. I apologise if this is not what you want either.
(1)Stop settings do not affect the generalisability of models, (2)only their selection.
Why do (2) if (1) is asserted?
If I understand correctly, models without SL and TP are trained, but those that perform better are selected, in this case, when SL = TP * 10. Strange, it would be more logical to give/show Python test results without SL and TP in the article, so that (1) is clearly visible. Ah yes, you can't see equity on python charts anyway, what's the use.....
PS. (1) and (2) in the quote are set by me.Why do (2) if (1) is asserted?
If I understand correctly, the models without SL and TP are trained, but those that perform better are selected, in this case, when SL = TP * 10. Strange, it would be more logical to give/show Python test results without SL and TP in the article, so that (1) is clearly visible. Ah yes, you can't see equity on python charts anyway, what's the use.....
PS. (1) and (2) in the quote are set by me.Those who read the article will find a nice bonus at the end - a chart from the terminal, which shows the drawdown.
Instead of whining, all you have to do is run it and try it. This is roughly what an answer to such questions should look like. Training in one cycle/export/compile takes a minute. Writing a nonsensical comment like this takes 30 seconds. Some more insights come during, "Oh yeah, oh right, here I am a commenter".
What is it? Where is the irritation coming from? Where are the substantive answers?
I stopped running Python codes from articles as soon as it became clear that what is described in articles is only a small part, and the rest is done and developed by anyone but the author of the article.
You wrote an article? - be kind enough to answer questions instead of writing 3-second meaningless replies.
I don't even know how to respond to known "troll commenters". Tried different options.
Do you have any thoughts on how to improve the TC? Share)