PR.IARM: Improved Augmented Regression Method (IARM) for Predictive...

In VAR.etp: VAR Modelling: Estimation, Testing, and Prediction

Improved Augmented Regression Method (IARM) for Predictive Regression

Description

Function for Improved ARM (IARM) estimation and testing

Usage

PR.IARM(x, y, p, Rmat = diag(k * p), rvec = matrix(0, nrow = k * p))

Arguments

x	predictor or a matrix of predictors in column
y	variable to be predicted, usually data1 return
p	AR order
Rmat	Restriction matrix, refer to function Rmatrix
rvec	Restriction matrix, refer to function Rmatrix

Details

Kim J.H., 2014, Predictive Regression: Improved Augmented Regression Method, Journal of Empirical Finance, 26, 13-25.

Value

LS	Ordinary Least Squares Estimators
IARM	IARM Estimators
AR	AR parameter estimators
ARc	Bias-corrected AR parameter estimators
Fstats	Fstats and their p-values
Covbc	Covariance matrix of the IARM estimators (for the predictive coefficients only)

Note

Kim J.H., 2014, Predictive Regression: Improved Augmented Regression Method, Journal of Empirical Finance, 26, 13-25.

Author(s)

Jae H. Kim

References

Kim J.H., 2014, Predictive Regression: Improved Augmented Regression Method, Journal of Empirical Finance, 26, 13-25.

Examples

data(data1)
# Replicating Table 5 (excess return) of Kim (2014)
y=data1$ret.nyse.vw*100 -data1$tbill*100
x=cbind(log(data1$dy.nyse), data1$tbill*100); 

Rmat1=Rmatrix(p=1,k=2,type=1,index=0); Rmat=Rmat1$Rmat; rvec=Rmat1$rvec
M=PR.IARM(x,y,p=1,Rmat,rvec)

VAR.etp documentation built on Aug. 31, 2023, 9:08 a.m.