Machine learning in trading: theory, models, practice and algo-trading - page 3065
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Scalpers - interesting.
Vladimir, did you use the blotter package?
by the way, the strategy from this book really works on the day trades, on stocks but not on forex.
and so on. A lot of stocks...
Although I used data from a brokerage centre that has stocks, so everything is possible ...
derivatives are traded on the exchange, bitcoin doesn't care about that.
I was talking about the cryptocurrency exchange of course.....
I was talking about the cryptocurrency exchange of course.....
Without it, you can't exchange signs
There are exchanges. But, in general, something about something else already... I mean that tokens have an original meaning, which is lost over time and only the exchange rate remains. And since there's no economic sense in them, their price is just speculative. It's clear that bitcoin is now being used essentially for dark deeds - that's its value.
What is the sr - why isn't it on the list that was given? What are you using it for?
The sr package is "
... Selecting good prognostic inputs using gamma test ...
... to determine lags in the time series. How far ahead does the signal appear? This is a classic example of the problem of figuring out which of our input variables, the predictor variables, is actually predictive. This problem is nonlinear and multivariate. This is the problem that the Gamma test solves.
...The use of Gamma to find causal relationships in time series data, determine optimal delays and attachments, and tune the performance of a neural network is demonstrated. "
Missing from the list. Purpose of use above.
hopelessness )))
Absolutely.
The blotter package did not apply. It is not in CRAN at the moment.
Asked Kandinsky to draw a trader with packages
Package sr - "
... Selecting good predictive inputs using gamma test ...
... identifying lags in the time series. How far ahead does the signal appear? This is a classic example of the problem of figuring out which of our input variables, the predictor variables, is actually predictive. This problem is nonlinear and multivariate. This is the problem that the gamma test solves.
...The use of Gamma to find causal relationships in time series data, determine optimal delays and attachments, and tune the performance of a neural network is demonstrated. "
Missing from the list. Purpose of use above.
Should be a useful thing, judging by the description.
How to run this for testing on a sample - can you share the code for the public?
Should be a useful thing, judging by the description.
How to run it for testing on a sample - can you share the code for the public?
similar to the Kolmogorov-Smirnov test
To test something, you have to first determine what to test. That usually takes forever in our field.
It's desperate.