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Dipsic one of the links hinted at the possibility of selling books electronically on ozone, for example on MO in trading. You can use this option to achieve great fame and power :)
Imho, not a bad idea if you combine this with creating a community of MO-trading) Then add a platform for MO-trading and thematic meme-coin) Not a bad chance to become rich.
You can become more famous than Prado and Pugacheva.
And even more famous than Pugacheva wearing a Prado)
Then create an investment fund in Dubai and a consulting agency to attract big money.
Imho, not a bad idea if you combine this with creating a MO trading community) Then add a platform for MO trading and a themed meme coin) Not a bad chance to get rich.
And even more famous than Pugacheva wearing a Prado.)
That's even better)One gets used to everything. Ideally, to the non-stationarity of the market too :)
Some brand new type of TS has suddenly appeared. It passes forward on EURUSD at the snap of fingers with some crazy number of trades, which can be filtered quite effectively.
Classification models did not pass such a forward well, because the trend direction of the pair has changed since the beginning of 2024.
I haven't tuned it properly yet.
Before filtering by thresholds
After
What a beauty this is. it's a little off at the end, but overall.
What a beauty this is. it's a little off at the end, but overall.
the last graph is all test?
the last graph is all test?
along with the training.
It's clearer that the forward is similar to the training. That's a good criterion for me.
in conjunction with training
test c 2024? or all mixed up with shuffle 50%? what stock index is it?
test c 2024? or all mixed up with shuffle 50%? what stock index is it?
Nothing shuffled, eurobucks. Test with 2024, yes. A turning point, good for testing.
But I modified the algorithm from the article already.Nothing mixed, eurobucks. Test from 2024, yes. Turning point, good for tests.
There is a great way to test if overlearning is present. Specify learning rate = 1 and test different random seeds, in increments of 10, ranging from 0 to 100.
If all 10 runs show more or less the same graph, then congratulations, there is no overlearning.
There is a great way to check if overlearning is present. Specify learning rate = 1 and check different random seeds, in increments of 10, ranging from 0 to 100.
If all 10 runs show more or less the same graph, then congratulations, there is no overtraining.