@MrRahul15937
Always thanks for bringing new knowledge
@MatthewEgan-vb5jv
Impressive video, I was wondering if you have considered any strategies that incorporate order flow or something similar?
@anirudh894
hi, i am a computer science student and i feel overwhelmed watching your videos ... can you please make a detailed roadmap that i can follow to be as knowledgeable as you and be able to apply that knowledge to create trading systems like....I am a big fan.
@akam0707
Good video, i hope you can make course on udemy soon in future for algorithmic trading course step by step.
@incremental_failure
Non-correlated ML features are always interesting. Curious if you're using ML for your actual trading?
@mozkhiyar9486
awesome video
@Ejnota
if you add the roll_correlation function as a filter it works better, let me know.
signal <- numeric(0)
position <- 0 # Initialize position outside the loop
for (i in 1:nrow(df)) {
row <- df[i, ]
if (row$dif_stra > 0 &row$cor_ < 0 ) {
position <- 1 # Update position to 1 if dif_stra > 2.5
df[i,'signal'] = position
}
if (row$dif_stra < 0 &row$cor_ < 0 ) {
position <- 1 # Update position to -1 if dif_stra < -2.5
df[i,'signal'] = position
}
if (position == 1 & row$dif_stra <=0 ) {
position < 0 # Reset position to 0 if it was 1 and dif_stra <= 0
}
if (position == 1 & row$dif_stra >= 0 ) {
position < 0 # Reset position to 0 if it was 1 and dif_stra >= 0
}
signal[i] < position
}
@denizhan1010
all charts refreshin 1000 bar. 1000 day 1000 hour 1000 minutes. every calculation 1000 bar dont forget.
@lancetschirhart7676