rc.avg {realized} | R Documentation |
Realized Covariance using average subsample.
rc.avg(x, y, period, align.period = 1, cts = TRUE, makeReturns = FALSE, ...)
x |
RealizedObject or TimeSeries for S+ |
y |
RealizedObject or TimeSeries for S+ |
period |
Sampling period |
align.period |
Align the returns to this period first |
cts |
Create calendar time sampling if a non realizedObject is passed |
makeReturns |
Prices are passed make them into log returns |
... |
... |
Realized covariance using average subsample.
Scott Payseur <spayseur@u.washington.edu>
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? Working Paper, October 2005.
data(msft.real.cts) data(ge.real.cts) # # Average subsampled realized covariance for CTS aligned at one second returns at # 600 subgrids (10 minutes). # rc.avg(x = msft.real.cts[[1]], y = ge.real.cts[[1]], period = 600) # # Average subsampled realized covariance for CTS aligned at one minute returns at # 5 subgrids (5 minutes). # rc.avg(x = msft.real.cts[[1]], y = ge.real.cts[[1]], period = 5, align.period=60)