rHYCov: Hayashi-Yoshida covariance

In highfrequency: Tools for Highfrequency Data Analysis

Hayashi-Yoshida covariance

Description

Calculates the Hayashi-Yoshida Covariance estimator

Usage

rHYCov(
  rData,
  cor = FALSE,
  period = 1,
  alignBy = "seconds",
  alignPeriod = 1,
  makeReturns = FALSE,
  makePsd = TRUE,
  ...
)

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.
period	Sampling period
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.
makePsd	boolean, in case it is TRUE, the positive definite version of rHYCov is returned. FALSE by default.
...	used internally. Do not set.

Author(s)

Scott Payseur and Emil Sjoerup.

References

Hayashi, T. and Yoshida, N. (2005). On covariance estimation of non-synchronously observed diffusion processes. Bernoulli, 11, 359-379.

See Also

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

Examples

library("xts")
hy <- rHYCov(rData = as.xts(sampleOneMinuteData)["2001-08-05"],
             period = 5, alignBy = "minutes", alignPeriod = 5, makeReturns = TRUE)

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