Publication Type
Working Paper
Version
publishedVersion
Publication Date
7-2007
Abstract
We investigate two methods for using daily stock returns to forecast, and update forecasts of, quarterly real output growth. Both methods aggregate daily returns in some manner to form a single stock market variable. We consider (i) augmenting the quarterly AR(1) model for real output growth with daily returns using a nonparametric Mixed Data Sampling (MIDAS) setting, and (ii) augmenting the quarterly AR(1) model with the most recent r -day returns as an additional predictor. We discover that adding low frequency stock returns (up to annual returns, depending on forecast horizon) to a quarterly AR(1) model improves forecasts of output growth
Keywords
Forecasting, Mixed Frequencies, Functional linear regression.
Discipline
Econometrics
Research Areas
Econometrics
First Page
1
Last Page
29
Publisher
SMU Economics and Statistics Working Paper Series, Paper No. 14-2007
City or Country
Singapore
Citation
Tay, Anthony S..
Financial variables as predictors of real output growth. (2007). 1-29.
Available at: https://ink.library.smu.edu.sg/soe_research/1058
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.