quantilogram (version 2.2.1)

crossq.max.partial: Partial Corss-Quantilogram upto a given lag order

Description

The partial cross-quantilograms from 1 to a given lag order.

Usage

crossq.max.partial(DATA, vecA, Kmax)

Value

A vector of cross-quantilogram and a vector of partial cross-quantilograms

Arguments

DATA

An input matrix

vecA

A vector of probability values at which sample quantiles are estimated

Kmax

The maximum lag order (integer)

Author

Heejoon Han, Oliver Linton, Tatsushi Oka and Yoon-Jae Whang

Details

This function calculates the partial cross-quantilograms up to the lag order users specify.

References

Han, H., Linton, O., Oka, T., and Whang, Y. J. (2016). "The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series." Journal of Econometrics, 193(1), 251-270.

Examples

## data source 
data("sys.risk") 

## data with 3 variables 
D = sys.risk[,c("Market", "JPM", "VIX")]

## probablity levels for the 3 variables 
vecA = c(0.1, 0.1, 0.1)

## partial cross-quantilogram with lags from 1 to 5
crossq.max.partial(D, vecA, 5)