Hi: I didn't look at the paper below but the critical values are probably

in there.

http://www.nber.org/papers/t0066.pdfOn Mon, Jul 3, 2017 at 6:16 PM, David Chang <

[hidden email]> wrote:

> I'm testing whether a null hypothesis that a time series is random

> walk is true. I use Auto.VR() and Lo.Mac() from R package "vrtest" for

> variance ratio test to EURUSD. EURUSD log returns were the input.

>

> > head(returns)

> Close

> 2002-01-08 -0.005035595

> 2002-01-09 0.001905318

> 2002-01-10 -0.002017508

> 2002-01-11 0.001009263

> 2002-01-14 0.002462807

> 2002-01-15 -0.001118706

>

> Where Auto.VR() gave me

> > Auto.VR(returns)

> $stat

> [1] 54.50223

> $sum

> [1] 2.843879

>

> Lo.Mac() gave me

> > Lo.Mac(returns, 2)

> $Stats

> M1 M2

> k=2 -2.083685 -1.733119

>

> How do we evaluate the result from Auto.VR() or Lo.Mac()? In other

> words, how can we say that the null hypothesis is rejected from those

> results?

>

> David

>

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