Mixing Frequencies: Stock Returns as a Predictor of Real Output Growth

Mixing Frequencies: Stock Returns as a Predictor of Real Output Growth

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 da...

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Bibliographic Details
Main Author: TAY, Anthony S.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2006
Subjects:
Forecasting
Mixed Data Sampling
Functional linear regression
Test forSuperior Predictive Ability
Econometrics
Finance
Online Access:https://ink.library.smu.edu.sg/soe_research/949
https://ink.library.smu.edu.sg/context/soe_research/article/1948/viewcontent/Tay_2006.pdf
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Institution: Singapore Management University
Language: English
Description
Summary: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.

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