highfrequency (version 0.2)

rAVGCov: Realized Covariance: Average Subsample

Description

Realized Covariance using average subsample.

Usage

rAVGCov(rdata, cor = FALSE, period = 1, align.by = "seconds", 
        align.period = 1, cts = TRUE, makeReturns = FALSE, ...)

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.

period

Sampling period

align.by

Align the tick data to seconds|minutes|hours

align.period

Align the tick data to this many [seconds|minutes|hours]

cts

Create calendar time sampling if a non realizedObject is passed

makeReturns

Prices are passed make them into log returns

...

...

Value

• Realized covariance using average subsample.

References

L. Zhang, P.A Mykland, and Y. Ait-Sahalia. A tale of two time scales: Determining integrated volatility with noisy high-frequency data. Journal of the American Statistical Association, 2005. Michiel de Pooter, Martin Martens, and Dick van Dijk. Predicting the daily covariance matrix for sp100 stocks using intraday data - but which frequency to use? Econometric Reviews, 2008.

Examples

# Average subsampled realized variance/covariance for CTS aligned at one minute returns at 
 # 5 subgrids (5 minutes).
 data(sample_tdata); 
 data(lltc.xts);
 data(sbux.xts);
 
 # Univariate
 rvSub = rAVGCov( rdata = sample_tdata$PRICE, period = 5, align.by ="minutes", 
                   align.period=5, makeReturns=TRUE); 
 rvSub
 
 # Multivariate:
 rcSub = rAVGCov( rdata = list(lltc.xts,sbux.xts), period = 5, align.by ="minutes", 
                   align.period=5, makeReturns=FALSE); 
 rcSub