Hi Johannes

I remember than in the 2013 r-sig-finance conference, James Matteson talked
about the R package 'ecp', which he wrote and may just do what you want.
Its on CRAN.

Cheers
Soren
http://censix.com


On Fri, May 16, 2014 at 11:15 AM, Johannes Moser <jzmoser@gmail.com> wrote:

> Dear all,
>
> in the context of a scenario analysis framework I manually selected some
> quiet and some stressful periods in the last 25 years of DAX returns. Now I
> wish to confirm this choices by means of a change-point detection test in
> R. The test ideally should pick changes in the conditional mean, more
> importantly in the conditional variance and covariance structure.
>
> The test should be able to handle highly-dependent time series. So tests
> that assume e.g. structural breaks in iid gaussian noise or assume
> independence between the breaks in another way are not the right thing
> (chow test etc.). I've already tried to apply tests that assume
> independence to the standardized returns (after fitting a GARCH model and
> extracting the volatility estimates) as the standardized returns can be
> considered close to iid. But this approach didn't seem to work well
> (package 'changepoint', test 'segneigh.var.css').  The results seem
> intuitive when this test is applied to the rough returns series. But this
> is clearly a violation of the independence assumption.
>
> I further tried the wavelet test for covariance stationarity (test
> 'hwtos2' in the 'locits' package) but it is much too sensitive (e.g. it
> rejects covariance stationarity in a simulated Gaussian GARCH(1,1) ). Also,
> the test (and R syntax) that comes with the paper of Fryzlewicz (2014)
> "Multiple-change-point detection for auto-regressive conditional
> heteroscedastic processe" has been applied to the returns series, but I'm
> not quite satisfied with the results.
>
> There are many more change-point detection packages and tests in R that I
> have considered. But so far none seems to be appropriate for financial
> returns and gives results that are interpretable in the context of
> knowledge of crisis periods and visual examination of the series.
>
> Is there any test for change-points in highly-dependent data (such as
> financial returns) that someone could recommend from his own experience?
> I'd be more that thankful for any advice!
>
> Kind regards, Johannes
>
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