Machine learning in trading: theory, models, practice and algo-trading - page 250
You are missing trading opportunities:
- Free trading apps
- Over 8,000 signals for copying
- Economic news for exploring financial markets
Registration
Log in
You agree to website policy and terms of use
If you do not have an account, please register
Okay, but what if we work as limiters, quoting, standing on both sides like in currency exchanges, selling liquidity? What are the predictions for?
That's the answer, we stand limiters on both sides and get a risk-free profit.
it's interesting to look at
https://www.youtube.com/watch?v=p5UngSem9f0
Time-consuming.
Can anyone tell me how to bring a matrix, for analysis and subsequent diagnosis through wavelet transforms?
I'm not very good at wavelets, but here, for example, examples with the package dplR were posted, I will rely on them.
1) This is a time series, so the matrix must somehow be converted into one long vector. You have, for example, each matrix row is like a sliding window of length 9, and the window offset on each new row = 0.5. I will add one last element from every other row to the vector. It would be better if you took your vector as it is, without the sliding windows and matrices.
I got a time series like this - 1 1 1 1 1 1 2 4 6 8 10 12 14 16 18 20 22 1 1 1 1 1.
2) What is shaded on the graph is unreliable, and cannot be used to predict the future. The "rightmost on the scale" color in the rightmost unshaded area is green (for periods 2 to 8).
And the answer would be "at the moment, periods from 2 to 8 prevail", which is really useless.)
1, 1, 1, 1, 2, 3, 5, 7, 9,
1, 1, 1, 1, 3, 4, 6, 8, 10,
1, 1, 1, 2, 4, 5, 7, 9, 11,
1, 1, 1, 3, 5, 6, 8, 10, 12,
1, 1, 1, 4, 6, 7, 9, 11, 13,
1, 1, 1, 5, 7, 8, 10, 12, 14,
1, 1, 2, 6, 8, 9, 11, 13, 15,
1, 1, 3, 7, 9, 10, 12, 14, 16,
1, 1, 4, 8, 10, 11, 13, 15, 17,
1, 2, 5, 9, 11, 12, 14, 16, 18,
1, 3, 6, 10, 12, 13, 15, 17, 19,
1, 4, 7, 11, 13, 14, 16, 18, 20,
1, 5, 8, 12, 14, 15, 17, 19, 21,
1, 6, 9, 13, 15, 16, 18, 20, 22,
2, 7, 10, 14, 16, 17, 19, 21, 1,
3, 8, 11, 15, 17, 18, 20, 22, 1,
4, 9, 12, 16, 18, 19, 21, 1, 1,
5, 10, 13, 17, 19, 20, 22, 1, 1,
6, 11, 14, 18, 20, 21, 1, 1, 1,
7, 12, 15, 19, 21, 22, 1, 1, 1,
8, 13, 16, 20, 22, 1, 1, 1, 1,
9, 14, 17, 21, 1, 1, 1, 1, 1,
10, 15, 18, 22, 1, 1, 1, 1, 1
), ncol=24, nrow = 9))
#создаём из матрицы временной ряд
for(i in seq(from = 1, to = nrow(inputMatrix), by = 2)){
if(i==1){
#первая строка матрицы берётся как есть`
tsVector <- inputMatrix[i,]
}else{
#от каждой строй строки берётся последний элемент
tsVector <- c(tsVector, inputMatrix[i,ncol(inputMatrix)])
}
}
#полученный вектор
tsVector
library(dplR)
#рассчёт вейвлетов
waveletObj <- morlet(tsVector)
#показать расчитанные коэффициенты
waveletObj
#график
wavelet.plot(waveletObj)
I'm not very good at wavelets, but there were examples with dplR package, I'll rely on them.
1) This is a time series, so the matrix must somehow be converted into one long vector. You have, for example, each matrix row is like a sliding window of length 9, and the window offset on each new row = 0.5. I will add one last element from every other row to the vector. It would be better if you took your vector as it is, without the sliding windows and matrices.
I came out with a time series like this - 1 1 1 1 1 1 2 4 6 8 10 12 14 16 18 20 22 1 1 1 1 1.
2) What is shaded on the graph is unreliable, and cannot be used to predict the future. The "rightmost on the scale" color in the unshaded area is green (for period = 8).
Does anyone know if the numbers need to be converted to trigonometric values for the wavelet transform?
Or what do they need to be converted to to start calculations?
What is R?
What's R?
Have you tried using google?
What's the R?