rc.timescale {realized}R Documentation

Realized Covariance: Two Timescales

Description

Realized Covariance using a generalization of the popular two timescale variance method.

Usage

rc.timescale(x, y, period, align.period = 1, adj.type = "classic", cts = TRUE, makeReturns = FALSE, ...)

Arguments

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
adj.type "classic", "adj" or "aa"
... ...

Details

Realized Covariance using two timescale method.

Value

Realized covariance using two timescale method

Author(s)

Scott Payseur <spayseur@u.washington.edu>

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? Working Paper, October 2005.

See Also

rv.timescale, rRealizedVariance

Examples

data(msft.real.cts)
data(ge.real.cts)


rc.timescale(x = msft.real.cts[[1]], y = ge.real.cts[[1]], period = 60, adj.type="aa")


[Package realized version 0.81 Index]