highfrequency (version 0.7.0.1)

ReMeDI: ReMeDI This function estimates the auto-covariance of market-microstructure noise

Description

ReMeDI This function estimates the auto-covariance of market-microstructure noise

Usage

ReMeDI(pData, kn = 1, lags = 1, knEqual = FALSE, makeCorrelation = FALSE)

Arguments

pData

xts or data.table containing the log-prices of the asset

kn

numeric of length 1 determining the tuning parameter kn this controls the lengths of the non-overlapping interval in the ReMeDI estimation

lags

numeric containing integer values indicating

knEqual

Use an altered version of the ReMeDI estimator, where we instead use equal kn, instead of kn and 2*kn for the windows. See Figure 1 of paper in reference section.

makeCorrelation

logical indicating whether to transform the autocovariances into autocorrelations. The estimate of variance is imprecise and thus, constructing the correlation like this may show correlations that fall outside (-1,1)

References

Li and Linton (2019) (Working paper): "A ReMeDI for microstructure noise."

Examples

# NOT RUN {
remed <- ReMeDI(sampleTDataMicroseconds[as.Date(DT) == "2018-01-02", ], kn = 2, lags = 1:8)
# We can also use the algorithm for choosing the kn to 
optimalKn <- knChooseReMeDI(sampleTDataMicroseconds[as.Date(DT) == "2018-01-02",],
                            knMax = 10, tol = 0.05, size = 3,
                            lower = 2, upper = 5, plot = TRUE)
optimalKn 
remed <- ReMeDI(sampleTDataMicroseconds[as.Date(DT) == "2018-01-02", ], kn = optimalKn, lags = 1:8)
# }