rKernelCov: Realized Covariance: Kernel

In highfrequency: Tools for Highfrequency Data Analysis

Description

Realized covariance calculation using a kernel estimator.

Usage

 
rKernelCov(rdata, cor = FALSE, kernel.type = "rectangular", kernel.param = 1, 
            kernel.dofadj = TRUE, align.by = "seconds", align.period = 1, 
            cts = TRUE, makeReturns = FALSE, type = NULL, adj = NULL, 
            q = NULL, ...) 

Arguments

rdata	In the multivariate case: a list. Each list-item i contains an xts object with the intraday data of stock i for day t. In the univariate case: an xts object containing the (tick) data for one day.
cor	boolean, in case it is TRUE, the correlation is returned. FALSE by default.
kernel.type	Kernel name (or number)
kernel.param	Kernel parameter (usually lags)
kernel.dofadj	Kernel Degree of freedom adjustment
align.by	Align the tick data to seconds|minutes|hours
align.period	Align the tick data to this many [seconds|minutes|hours]
cts	Calendar Time Sampling is used
makeReturns	Convert to Returns
type	Deprecated, use kernel.type
adj	Deprecated, use kernel.dofadj
q	Deprecated, use kernel.param
...	...

Details

The different types of kernels can be found using rKernel.available.

Value

Kernel estimate of realized covariance.

Author(s)

Scott Payseur <[e-mail]>

References

Ole E. Barndorff-Nielsen, Peter Reinhard Hansen, Asger Lunde, and Neil Shephard. Regular and modified kernel-based estimators of integrated variance: The case with independent noise. Working Paper, 2004.

B. Zhou. High-frequency data and volatility in foreign-exchange rates. Journal of Buiness & Economic Statistics, 14:45-52, 1996.

P. Hansen and A. Lunde. Realized variance and market microstructure noise. Journal of Business and Economic Statistics, 24:127-218, 2006.

See Also

rKernel.available

Examples

 
 # Average Realized Kernel Variance/Covariance for CTS aligned at one minute returns at 
 # 5 subgrids (5 minutes).
 data(sample_tdata); 
 data(lltc.xts); 
 data(sbux.xts); 
 
 # Univariate: 
 rvKernel = rKernelCov( rdata = sample_tdata$PRICE, period = 5, align.by ="minutes", 
                   align.period=5, makeReturns=TRUE); 
 rvKernel 
 
 # Multivariate:
 rcKernel = rKernelCov( rdata = list(lltc.xts,sbux.xts), period = 5, align.by ="minutes", 
                   align.period=5, makeReturns=FALSE); 
 rcKernel 

highfrequency documentation built on May 2, 2019, 6:09 p.m.