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

Anthony S. Tay
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Anthony S. Tay: SMU

Macroeconomics Working Papers from East Asian Bureau of Economic Research

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 for Superior Predictive Ability (search for similar items in EconPapers)
JEL-codes: C53 E37 (search for similar items in EconPapers)
Date: 2006-01
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Citations: View citations in EconPapers (5)

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