# Ljung Box Test

I have an array that I want to use Ljung Box Test on. In Matlab, there is lbqtest function that works on array.

I want to know how I can do this in Julia.

``````
nz = 1250
z =randn(nz,1)# randomly generated z distributed N[0,1]

sig=0.20*sqrt(1/252); #defining the trade day volatility
#of logarithmic change from annualized volatility 20-percent
cv = zeros(nz,1)
ep = zeros(nz,1)
G = 0.75
#weight on past conditional variance
A = 0.20
#weight on innovation
cv[1] = sig^2
ep[1] = 0
kappa = sig*sig*(1-(A+G)); #unconditional variance kappa/(1-(A+G))

for j = 2:nz #for loop creating conditional variance process
cv[j] = kappa + G*cv[j-1] + A*(ep[j-1]^2)
ep[j] = sqrt(cv[j])*z[j]  #process innovation
end

mcv = exp.(ep)
mcv[1] = P0
Pcv = cumprod(mcv)

xcv = log(Pcv[2:end])-log(Pcv[1:end-1])

using HypothesisTests

LjungBoxTest(xcv) # does not work
``````

Not an expert at all (hadnâ€™t heard of the Ljung-Box test before today, and I still donâ€™t really know what itâ€™s for), but it looks like HypothesisTests.LjungBoxTest requires you to pass in the lag as the second argument, whereas the matlab documentation for lbqtest shows that the single-argument `lbqtest(res)` uses â€śthe default number of lagsâ€ť while citing [3].

(BTW, `P0` is undefined).

[3] Gourieroux, C. ARCH Models and Financial Applications. New York: Springer-Verlag, 1997.

Thanks. I missed that input. I thought I need to convert my array into a time series, but I have not worked with time series in Julia yet.

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