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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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
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spelling sg-smu-ink.soe_research-19482019-04-28T02:06:12Z Mixing Frequencies: Stock Returns as a Predictor of Real Output Growth TAY, Anthony S. 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. 2006-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/949 https://ink.library.smu.edu.sg/context/soe_research/article/1948/viewcontent/Tay_2006.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Forecasting Mixed Data Sampling Functional linear regression Test forSuperior Predictive Ability Econometrics Finance
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Forecasting
Mixed Data Sampling
Functional linear regression
Test forSuperior Predictive Ability
Econometrics
Finance
spellingShingle Forecasting
Mixed Data Sampling
Functional linear regression
Test forSuperior Predictive Ability
Econometrics
Finance
TAY, Anthony S.
Mixing Frequencies: Stock Returns as a Predictor of Real Output Growth
description 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.
format text
author TAY, Anthony S.
author_facet TAY, Anthony S.
author_sort TAY, Anthony S.
title Mixing Frequencies: Stock Returns as a Predictor of Real Output Growth
title_short Mixing Frequencies: Stock Returns as a Predictor of Real Output Growth
title_full Mixing Frequencies: Stock Returns as a Predictor of Real Output Growth
title_fullStr Mixing Frequencies: Stock Returns as a Predictor of Real Output Growth
title_full_unstemmed Mixing Frequencies: Stock Returns as a Predictor of Real Output Growth
title_sort mixing frequencies: stock returns as a predictor of real output growth
publisher Institutional Knowledge at Singapore Management University
publishDate 2006
url https://ink.library.smu.edu.sg/soe_research/949
https://ink.library.smu.edu.sg/context/soe_research/article/1948/viewcontent/Tay_2006.pdf
_version_ 1770569347465478144

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