rmoutliers: Delete entries for which the mid-quote is outlying with...
In highfrequency: Tools for Highfrequency Data Analysis
Description
Usage
Arguments
Value
Details
Author(s)
References
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
1
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).
Value
xts object
Details
NOTE: This function works only correct if supplied input data consists of 1 day.
Author(s)
Jonathan Cornelissen and Kris Boudt
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.
highfrequency documentation built on May 2, 2019, 6:09 p.m.
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Description Usage Arguments Value Details Author(s) References
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
1 | 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). |
Value
xts object
Details
NOTE: This function works only correct if supplied input data consists of 1 day.
Author(s)
Jonathan Cornelissen and Kris Boudt
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.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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