rmOutliers: Delete entries for which the mid-quote is outlying with respect to surrounding entries
Description
If type="standard": Function deletes entries for which the mid-quote deviated by more than "maxi"
median absolute deviations from a rolling centered median (excluding
the observation under consideration) of "window" observations.
If type="advanced": Function deletes entries for which the mid-quote deviates by more than "maxi"
median absolute deviations from the value closest to the mid-quote of
these three options:
- Rolling centered median (excluding the observation under consideration)
- Rolling median of the following "window" observations
- Rolling median of the previous "window" observations
The advantage of this procedure compared to the "standard" proposed
by Barndorff-Nielsen et al. (2010) is that it will not incorrectly remove
large price jumps. Therefore this procedure has been set as the default
for removing outliers.
Note that the median absolute deviation is taken over the entire
sample. In case it is zero (which can happen if mid-quotes don't change much),
the median absolute deviation is taken over a subsample without constant mid-quotes.Usage
rmOutliers(qdata,maxi=10,window=50,type="advanced")
Arguments
qdata
an xts object at least containing the columns "BID" and "OFR".
maxi
an integer, indicating the maximum number of median absolute deviations allowed.
window
an integer, indicating the time window for which the "outlyingness" is considered.
type
should be "standard" or "advanced" (see description).
Details
NOTE: This function works only correct if supplied input data consists of 1 day.References
Barndorff-Nielsen, O. E., P. R. Hansen, A. Lunde, and N. Shephard (2009). Realized
kernels in practice: Trades and quotes. Econometrics Journal 12, C1-C32.
Brownlees, C.T. and Gallo, G.M. (2006).
Financial econometric analysis at ultra-high frequency: Data handling concerns.
Computational Statistics & Data Analysis, 51, pages 2232-2245.