Publication Type
Working Paper
Version
publishedVersion
Publication Date
12-2006
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 find that our mixed frequency models perform well in forecasting real output growth.
Keywords
Forecasting, Mixed Data Sampling, Functional linear regression, Test forSuperior Predictive Ability
Discipline
Econometrics | Finance
Research Areas
Econometrics
First Page
1
Last Page
33
Publisher
SMU Economics and Statistics Working Paper Series, No. 34-2006
City or Country
Singapore
Citation
TAY, Anthony S..
Mixing Frequencies: Stock Returns as a Predictor of Real Output Growth. (2006). 1-33.
Available at: https://ink.library.smu.edu.sg/soe_research/949
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.