Machine learning in trading: theory, models, practice and algo-trading - page 3156

[Maxim Dmitrievsky]

СанСаныч Фоменко #:

Actually, Maxim wrote above that OOS does NOT work anywhere. It's just a naked overfitting. Just a little more and we will start to rejoice at the extraordinary results of optimisation in the tester.

I'm already used to that you always read something wrong :) I advise you not to read, not to waste your time, but to apply ready-made packages at once. Or better yet, don't write. You just waste other people's time, as if deliberately, all the time twisting information.

[mytarmailS]

Maxim Dmitrievsky #:
I'm used to you reading things wrong all the time :)

Well, write down what you have to do point by point to make it clear, or code...

[Maxim Dmitrievsky]

mytarmailS #:

So write down what you need to do to make it clear, or code...

No, I want you to suffer learning python and the formulas in the book. Which are simple.

[mytarmailS]

Maxim Dmitrievsky #:
No, I want you to suffer learning python and the formulas in the book. Which are simple.

I don't think anyone's gonna go for that.

It's expensive, it's confusing.

[Maxim Dmitrievsky]

mytarmailS #:

I don't think anyone's gonna go for that.

A lot of expense, no clear result.

I'm sure there are packages

[mytarmailS]

Maxim Dmitrievsky #:
I'm sure there are bags on the R

Is that a quip?

[Evgeni Gavrilovi]

Maxim Dmitrievsky #:

You can check it out for yourself, I've developed a bit of a kozul theme so you don't get bored.

So your last graph shows the result of the script in the last article? https://www.mql5.com/ru/articles/9138

You have not added a new function?

[Maxim Dmitrievsky]

mytarmailS #:

is that a joke?

No.

[Maxim Dmitrievsky]

Evgeni Gavrilovi #:

So your last graph shows the result of the script in the last article? https://www.mql5.com/ru/articles/9138

You didn't add a new function?

The result of mine, they are similar to the article one

It's all details, the main thing is to understand the material

[mytarmailS]

Maxim Dmitrievsky #:
No

Packages are good, but first you need to understand in principle what you need to do.

chat response about kozuli methods

There are several methods that are used for causal inference. Some of the most common methods include:

1. Randomised controlled experiments: This is a method that is used to identify causal relationships in complex environments. It involves complete control over the assignment mechanism and the assignment is^random1.
2. Observational data: This method is used when experiments are not possible or practical. It involves analysing data collected from natural sources such as surveys or administrative^records1.
3. Instrumental variables: This method is used to identify causal relationships when there are problems with endogeneity or lack of^data1.
4. Propensity matching: This method is used to compare groups with similar characteristics to remove the impact of^confounding1.
5. Difference-in-difference estimator: This method is used to analyse changes over time and between^groups1.

These are just a few of the many methods that are used for causal inference. Each method has its own advantages and disadvantages, and the choice of method depends on the particular situation and the data available.

tell us about point 1

Randomised controlled experiments, also known as randomised controlled trials (RCTs), are a powerful method for discovering causal relationships. In an RCT, participants are randomly divided into two or more groups. One group receives an intervention (such as a medication) and the other group receives a placebo or standard treatment. Researchers then compare the results between the groups to determine if there is a difference in outcomes.

The main advantage of RCT is that randomly assigning participants to groups helps eliminate bias and confounding. This means that any differences in outcomes between groups can be attributed to exposure rather than other factors.

However, RCTs are not always possible or practical. For example, they may be expensive, require a large amount of time and resources, or be ethically unacceptable. In these cases, researchers may use other methods of causal inference.

======================================

Are you doing this? It's a phyche selecta boruta by the looks of it.