SWfore: Stock-Watson Diffusion Index Forecasts

SWforeR Documentation

Stock-Watson Diffusion Index Forecasts

Description

Uses the diffusion index approach of Stock and Watson to compute out-of-sample forecasts

Usage

SWfore(y, x, orig, m)

Arguments

y

The scalar variable of interest

x

The data matrix (T-by-k) of the observed explanatory variables

orig

Forecast origin

m

The number of diffusion index used

Details

Performs PCA on X at the forecast origin. Then, fit a linear regression model to obtain the coefficients of prediction equation. Use the prediction equation to produce forecasts and compute forecast errors, if any. No recursive estimation is used.

Value

coef

Regression coefficients of the prediction equation

yhat

Predictions at the forecast origin

MSE

Mean squared errors, if available

loadings

Loading matrix

DFindex

Diffusion indices

Author(s)

Ruey S. Tsay

References

Tsay (2014, Chapter 6). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.


MTS documentation built on April 11, 2022, 5:07 p.m.