Machine learning in trading: theory, models, practice and algo-trading - page 2738

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mytarmailS #:
Discretisation is a special case of filtering (compression of information) if it was not useful, it would not exist at all.... To consider it dabbling is to be an idiot, which is not surprising
MO professor ahahaha.
You've got a lot of burning and shrinking in one place at the word filtration, but as they say, dementia and bravery prevent you from distinguishing one from the other

If you have recently come out of school and try to get into science by leaps and bounds, you should not expect a quick effect, except to shine in front of your mates over a beer.

I forgot. Your neural networks are filters too. I guess you abuse unfiltered.
 
Maxim Dmitrievsky #:
You don't expect to make a quick buck, except to show off to your mates over a pint.
That's right, read that before you go to bed every night. Don't mess around where you don't know anything.

I know how to discretise to improve a model, and you go back to school!

MO professor ahahaha))
 
Maxim Dmitrievsky #:
And where did you see noise in cloze prices and how are they worse than Mashka. It has no effect. Random divided by random

That's probably one of the first ways a neophyte to MO will run to check and get crapped on

As I wrote there... first you need to define the object of study and its properties, and then the causal relationship using MO (if there is one)

IO is a painless way to test hypotheses with new data. And these guys are running around screaming that nothing works.

MAs are better in some ways:

0. The Close price inherits the noise from ticks. Literally - whether a tick was generated before the bar closed or not, whether the timer clicked somewhere. Plus or minus a couple of three points. It is on the stock exchange days have significant Open/Close.

1. MA they are already integral (yes - average)

2. they represent the price quite adequately. (that's why I pointed out that the LWMA shift by a little more than 1/3, by a third it is exactly the actual smoothed price without unnecessary noise). 3.

3. they are more convenient to compare and can be normalised.

---

finally - and what is the object of your research ?

 
Maxim Kuznetsov #:

there are suspicions that some forum persons, and even more so the filling of sites with "profitable Expert Advisors and signals" is the result of AI. That is, NN are making money on the topic of near-trading.

Absolutely neural networks and big-data earn (trade) on trend analysis of social networks. That's why they are sponsored and therefore somewhat lopsided; but it's beyond our capabilities :-(

Thanks for the reply

 
Maxim Dmitrievsky #:
If the thread is not heated up at least once a month, it will die and the forum will get boring

For example, SanSanych voiced interesting thoughts that are also in my head, so respect and respect, I got some approval implicitly from the pros in the MoD

SSF did not say much new, of course the goal to find correlation between predictors and outcome is an obvious goal. The only new thing I caught is that he has about 200 found significant features on the whole training, but for specific data, he uses only 5 per cent of them.

I understand this to mean that there are some ways to quickly determine the state/properties of a series in order to select more significant predictors just for the latest data. The question of volume or length of course arises for proper selection. But apparently it works even with only 200 found and selected predictors in the whole large training.

I see it like this. A series has properties that are stable in some indices, but these indices and their number are different in different sections. MO finds some different states of sufficient duration of stability of the series, which can be described by different models and accordingly model settings - predictors. The total number of predictors is the total number of settings for different models, and accordingly, by defining a model, one can quickly find previously found settings for it.

If to develop extensively, then to increase the total number of predictors and the number of models.

I agree with SSF that today the available and acceptable data for processing are quotations, formalisation of other data is a science, though promising.

 
Maxim Kuznetsov #:

The MAs are better in some ways:

0. Close price inherits noise from ticks. Literally - whether a tick was generated before the bar closed or not, whether the timer clicked somewhere. Plus or minus a couple of three points. It is on the stock exchange that days have significant Open/Close.

1. MA they are already integral (yes - average)

2. they represent the price quite adequately. (that's why I pointed out that the LWMA shift by a little more than 1/3, a third is exactly the actual smoothed price without unnecessary noise).

3. they are more convenient to compare and can be normalised

---

Finally, what is your object of study?

I agree with Max, short averages and thinned data are the same for investigation in terms of noise and useful signal in our discrete case.

The object of study is increments, if I'm not mistaken))))))

 
Valeriy Yastremskiy #:

SSF did not say much new, of course the goal to find correlation between predictors and outcome is an obvious goal.

NF and MD are sick of the idea of correlation between target and traits, one has been sick for a long time, the other has just started....
It doesn't occur to them that any algorithm for feature selection does this, and there are dozens of such algorithms already... exactly...
But... Ptushnik believes in his genius and firmly believes that he is creating something new and unique.....
And they carry this idea as a discovery, as their intellectual labour.
CIRC... Professor MO))))

 
mytarmailS #:
NF and MD are sick with the idea of linking the target to features, one of them has been sick for a long time, the other has just started...
It does not occur to them that any algorithm for feature selection does this, and dozens of such algorithms have already been created.....
But... Ptushnik believes in his genius and firmly believes that he is creating something new and unique.....
CIRC... Professor MO))))

I hope that nobody here believes in his genius, and personal crossings are just vampirism psychological)))) And if it brings psychological benefit to any of the parties, it has its place))))))

Everybody's toolkit is approximately the same, the data are the same, and perceptions ...

I have a small sledgehammer, not a big hammer, and not a huge big hammer at all)))))))

 
Valeriy Yastremskiy #:

The tools are all roughly the same, the data are all the more so so far the same, and the views ...

++++
Representation solves everything
 
mytarmailS #:
Alexei, it's a regular search task, just like you like, what's the problem?

So does the script do it or not?

I just wonder how many people here easily lose the thread of the conversation.

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