medRQ: An estimator of integrated quarticity from applying the...

In highfrequency: Tools for Highfrequency Data Analysis

Description

Function returns the medRQ, defined in Andersen et al. (2012).

Assume there is N equispaced returns in period t. Let r_{t,i} be a return (with i=1, …,N) in period t.

Then, the medRQ is given by

\mbox{medRQ}_{t}=\frac{3π N}{9π +72 - 52√{3}} ≤ft(\frac{N}{N-2}\right) ∑_{i=2}^{N-1} \mbox{med}(|r_{t,i-1}|, |r_{t,i}|, |r_{t,i+1}|)^4

Usage

medRQ (rdata, align.by=NULL, align.period=NULL, makeReturns=FALSE,...)

Arguments

rdata	a zoo/xts object containing all returns in period t for one asset.
align.by	a string, align the tick data to "seconds"|"minutes"|"hours"
align.period	an integer, align the tick data to this many [seconds|minutes|hours].
makeReturns	boolean, should be TRUE when rdata contains prices instead of returns. FALSE by default.
...	additional arguments.

Value

numeric

Author(s)

Giang Nguyen, Jonathan Cornelissen and Kris Boudt

References

Andersen, T. G., D. Dobrev, and E. Schaumburg (2012). Jump-robust volatility estimation using nearest neighbor truncation. Journal of Econometrics, 169(1), 75- 93.

Examples

data(sample_tdata)
medRQ(rdata= sample_tdata$PRICE, align.by= "minutes", align.period =5, makeReturns= TRUE)
medRQ

highfrequency documentation built on May 2, 2019, 6:09 p.m.