PR.order: Improved Augmented Regression Method for Predictive...

View source: R/PR.order.R

PR.orderR Documentation

Improved Augmented Regression Method for Predictive Regression

Description

Function to select the order p by AIC or BIC

Usage

PR.order(x, y, pmax = 10)

Arguments

x

predictor or a matrix of predictors in column

y

variable to be predicted, usually stock return

pmax

maximum order for order selection

Details

Kim J.H., 2014, Predictive Regression: Improved Augmented Regression Method, Journal of Empirical Finance 25, 13-15.

Value

p.aic

order chosen by AIC

p.aic

order chosen by BIC

Note

Kim J.H., 2014, Predictive Regression: Improved Augmented Regression Method, Journal of Empirical Finance 25, 13-15.

Author(s)

Jae H. Kim

References

Kim J.H., 2014, Predictive Regression: Improved Augmented Regression Method, Journal of Empirical Finance 25, 13-15.

Examples


data(data1)
# Replicating Table 5 (excess return)
y=data1$ret.nyse.vw*100 -data1$tbill*100
x=cbind(log(data1$dy.nyse), data1$tbill*100); k=ncol(x) 

p=PR.order(x,y,pmax=10)$p.bic;  # AR(1) 

VAR.etp documentation built on July 2, 2022, 1:05 a.m.