rCov: Realized covariance

In highfrequency: Tools for Highfrequency Data Analysis

Realized covariance

Description

Function returns the Realized Covariation (rCov). Let r_{t,i} be an intraday N \times M return vector and i=1,...,M the number of intraday returns.

Then, the rCov is given by

\mbox{rCov}_{t}=\sum_{i=1}^{M}r_{t,i}r'_{t,i}.

Usage

rCov(
  rData,
  cor = FALSE,
  alignBy = NULL,
  alignPeriod = NULL,
  makeReturns = FALSE,
  ...
)

Arguments

rData	an xts or data.table object containing returns or prices, possibly for multiple assets over multiple days.
cor	boolean, in case it is TRUE, and the input data is multivariate, the correlation is returned instead of the covariance matrix. FALSE by default.
alignBy	character, indicating the time scale in which alignPeriod is expressed. Possible values are: "ticks", "secs", "seconds", "mins", "minutes", "hours"
alignPeriod	positive numeric, indicating the number of periods to aggregate over. For example, to aggregate based on a 5-minute frequency, set alignPeriod = 5 and alignBy = "minutes".
makeReturns	boolean, should be TRUE when rData contains prices instead of returns. FALSE by default.
...	used internally, do not change.

Value

in case the input is and contains data from one day, an N \times N matrix is returned. If the data is a univariate xts object with multiple days, an xts is returned. If the data is multivariate and contains multiple days (xts or data.table), the function returns a list containing N by N matrices. Each item in the list has a name which corresponds to the date for the matrix.

Author(s)

Jonathan Cornelissen, Kris Boudt, and Emil Sjoerup.

See Also

ICov for a list of implemented estimators of the integrated covariance.

Examples

# Realized Variance/Covariance for prices aligned at 5 minutes.

# Univariate:
rv = rCov(rData = sampleTData[, list(DT, PRICE)], alignBy = "minutes",
          alignPeriod = 5, makeReturns = TRUE)
rv

# Multivariate:
rc = rCov(rData = sampleOneMinuteData, makeReturns = TRUE)
rc

highfrequency documentation built on Oct. 4, 2023, 5:08 p.m.