slow.jl

using DataFrames
using DataFramesMeta
using GLM


function f()
	DPY = 252  ## days per year
	NWINDOW = 126  ## can be smaller or larger than 252

	ds = readtable("xri.csv")  ## a sample data set

	# create two empty arrays to store b_ols and sd_ols value
	b_ols = DataArray(Float64, size(ds)[1])
	sd_ols = DataArray(Float64, size(ds)[1])

	for i = 1:size(ds)[1]
		thisDay = ds[i, :day] ## Julia DataFrame way of accessing data, in R: ds$day[i]
		if mod(thisDay, DPY) != 0
			continue
		end
		if thisDay < DPY
			continue
		end
		thisFm = ds[i, :fm]
		dataSubset = @where(ds, (:fm .== thisFm) & (:day .>= (thisDay - NWINDOW)) & (:day .<= (thisDay - 1)))
		olsReg = fit(LinearModel, xr ~ xm, dataSubset) ## OLS from package GLM
		b_ols[i] = coef(olsReg)[2] ## returns the OLS coefficients
		sd_ols[i] = stderr(olsReg)[2] ## returns the OLS coefficients' standard error
		print(i, " ")
	end

	ds[:b_ols] = b_ols
	ds[:sd_ols] = sd_ols

	print("\nOLS Beta Regressions are Done\n")

	return ds
end

ds = readtable("xri.csv")
@time f(ds)