Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7313
Title: Private Information of the Fed and Predictability of Stock Returns
Authors: Taş, Bedri Kamil Onur
Keywords: [No Keywords]
Publisher: Routledge Journals, Taylor & Francis Ltd
Abstract: This article investigates whether the Federal Reserve's (Fed's) private Gross Domestic Product (GDP) growth forecasts, as reported in the Greenbook of the Fed, contain information about future real and excess stock returns. I implement long-horizon regressions to analyse the predictive power of the Fed's GDP growth forecasts. The regressions conclude that the Fed's GDP growth forecasts can be used to predict long-and short-term stock returns. The size of the coefficient of the Fed's orthogonal GDP growth forecast indicates that 1% increase in the Fed's forecast predicts 2-4% decrease in real and excess stock returns. The regressions considering the size effect suggest that the predictive power of the Fed's GDP growth forecasts increases as the size of the portfolio decreases. A comparison of the Fed's forecasts and the commercial forecasts shows that the Fed's GDP growth forecasts contain information that does not exist in the commercial forecasts. I investigate the sources of the Fed's superior private information and predictive power. Analysis suggests that the source of the predictive power of the Fed's GDP growth forecasts is the private information about future surprise monetary policy actions embedded in them.
URI: https://doi.org/10.1080/00036840903194220
https://hdl.handle.net/20.500.11851/7313
ISSN: 0003-6846
1466-4283
Appears in Collections:İktisat Bölümü / Department of Economics
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Show full item record



CORE Recommender

SCOPUSTM   
Citations

1
checked on Dec 21, 2024

WEB OF SCIENCETM
Citations

1
checked on Dec 21, 2024

Page view(s)

80
checked on Dec 16, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.