dc.contributor.author |
Balcilar, Mehmet
|
|
dc.contributor.author |
Gupta, Rangan
|
|
dc.contributor.author |
Pierdzioch, Christian
|
|
dc.date.accessioned |
2023-06-08T06:06:27Z |
|
dc.date.available |
2023-06-08T06:06:27Z |
|
dc.date.issued |
2022-11-11 |
|
dc.description |
DATA AVAILABILITY STATEMENT : Data is available from the authors upon request. |
en_US |
dc.description.abstract |
We investigate whether oil-price uncertainty helps forecast the international stock returns
of ten advanced and emerging countries. We consider an out-of-sample period of August 1925
to September 2021, with an in-sample period between August 1920 and July 1925, and employ a
quantile-predictive-regression approach, which is more informative relative to a linear model, as
it investigates the ability of oil-price uncertainty to forecast the entire conditional distribution of
stock returns Based on a recursive estimation scheme, we draw the following main conclusions:
the quantile-predictive-regression approach using oil-price uncertainty as a predictor statistically
outperforms the corresponding quantile-based constant-mean model for all ten countries at certain
quantiles (capturing normal, bear, and bull markets), and over specific forecast horizons, compared to
forecastability being detected for eight countries under the linear predictive model. Importantly, we
detect forecasting gains in many more horizons (at particular quantiles) compared to the linear case.
In addition, an oil-price uncertainty-based state-contingent spillover analysis reveals that the ten
equity markets are connected more tightly at the upper regime, suggesting that heightened oil-market
volatility erodes the benefits from diversification across equity markets. |
en_US |
dc.description.department |
Economics |
en_US |
dc.description.librarian |
am2023 |
en_US |
dc.description.uri |
https://www.mdpi.com/journal/energies |
en_US |
dc.identifier.citation |
Balcilar, M.; Gupta, R.;
Pierdzioch, C. Oil-Price Uncertainty
and International Stock Returns:
Dissecting Quantile-Based
Predictability and Spillover Effects
Using More than a Century of Data.
Energies 2022, 15, 8436. https://DOI.org/10.3390/en15228436. |
en_US |
dc.identifier.issn |
1996-1073 (online) |
|
dc.identifier.other |
10.3390/en15228436 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/91050 |
|
dc.language.iso |
en |
en_US |
dc.publisher |
MDPI |
en_US |
dc.rights |
© 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license. |
en_US |
dc.subject |
International stock markets |
en_US |
dc.subject |
Oil price uncertainty |
en_US |
dc.subject |
Forecasting |
en_US |
dc.subject |
Quantile regression |
en_US |
dc.subject |
SDG-09: Industry, innovation and infrastructure |
en_US |
dc.title |
Oil-price uncertainty and international stock returns : dissecting quantile-based predictability and spillover effects using more than a century of data |
en_US |
dc.type |
Article |
en_US |