rTPQuar {highfrequency} | R Documentation |
Realized tri-power quarticity
Description
Calculate the rTPQuar, defined in Andersen et al. (2012).
Assume there are N
equispaced returns r_{t,i}
in period t
, i=1, \ldots,N
. Then, the rTPQuar is given by
\mbox{rTPQuar}_{t}=N\frac{N}{N-2} \left(\frac{\Gamma \left(0.5\right)}{ 2^{2/3}\Gamma \left(7/6\right)} \right)^{3} \sum_{i=3}^{N} \mbox({|r_{t,i}|}^{4/3} {|r_{t,i-1}|}^{4/3} {|r_{t,i-2}|}^{4/3})
Usage
rTPQuar(rData, alignBy = NULL, alignPeriod = NULL, makeReturns = FALSE)
Arguments
rData |
an |
alignBy |
character, indicating the time scale in which |
alignPeriod |
positive numeric, indicating the number of periods to aggregate over. For example, to aggregate
based on a 5-minute frequency, set |
makeReturns |
boolean, should be |
Value
In case the input is an
xts
object with data from one day, a numeric of the same length as the number of assets.If the input data spans multiple days and is in
xts
format, anxts
will be returned.If the input data is a
data.table
object, the function returns adata.table
with the same column names as the input data, containing the date and the realized measures.
Author(s)
Giang Nguyen, Jonathan Cornelissen, Kris Boudt, and Emil Sjoerup.
References
Andersen, T. G., Dobrev, D., and Schaumburg, E. (2012). Jump-robust volatility estimation using nearest neighbor truncation. Journal of Econometrics, 169, 75-93.
Examples
tpq <- rTPQuar(rData = sampleTData[, list(DT, PRICE)], alignBy = "minutes",
alignPeriod = 5, makeReturns = TRUE)
tpq