I'm a CS student working on a financial computing project + have a question regarding cointegration testing using linear regression with the lm() function.
https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/lm
Data:
I've seen many examples through different strategies/notes online and was wondering which is the correct one to use under certain scenarios ( +0, +1, or nothing)
eg:
m <- lm(series[[9]] ~ series[[1]] + 0)
beta <- m$coefficients[1]
cat ("Assumed hedge ratio is ", beta, "\n")
sprd <- series[[9]] - beta * series[[1]]
adf.test(sprd, alternative = 'stationary', k=0)$p.value #0.6647128
m <- lm(series[[9]] ~ series[[1]] + 1)
beta <- m$coefficients[1]
cat ("Assumed hedge ratio is ", beta, "\n")
sprd <- series[[9]] - beta * series[[1]]
adf.test(sprd, alternative = 'stationary', k=0)$p.value #0.5656023
model <- lm(series[[9]] ~ series[[1]])
b <- model$coefficients[2]
spreadp1 <- series[[9]] - b*series[[1]]
adf.test(spreadp1, k=0)$p.value # 0.4339312