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1 – 3 of 3To estimate the volatility of exchange and stock markets and examine its spillover within and across the member countries of BRICS during COVID-19 and the conflict between Russia…
Abstract
Purpose
To estimate the volatility of exchange and stock markets and examine its spillover within and across the member countries of BRICS during COVID-19 and the conflict between Russia and Ukraine.
Design/methodology/approach
The study utilizes the “dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH)” approach of Gabauer (2020). The volatility of the markets is calculated following the approach of Parkinson (1980). The sample dataset comprises the daily volatility of the stock and exchange markets for 35 months, from November 2019 to September 2022.
Findings
The study confirms the existence of contagion effects among member countries. Volatility spillover between exchange and stock markets is low within the country but substantial across borders. Russian contribution increased significantly during the conflict with Ukraine, and other countries also witnessed a surge in the spillover index during the pandemic and war.
Research limitations/implications
It adds to the body of literature by emphasizing the necessity of comprehending the economies' behavior and interdependence. Offers insightful information to decision-makers who must be more watchful regarding the financial crisis and its regional spillover.
Originality/value
The study is the first to explore the contagion of volatility among the BRICS countries during the two biggest crisis periods of the decade.
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Keywords
Barkha Dhingra, Shallu Batra, Vaibhav Aggarwal, Mahender Yadav and Pankaj Kumar
The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a…
Abstract
Purpose
The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a comprehensive review of how stock market volatility is influenced by macro and firm-level factors. Therefore, this study aims to fill this gap by systematically reviewing the major factors impacting stock market volatility.
Design/methodology/approach
This study uses a combination of bibliometric and systematic literature review techniques. A data set of 54 articles published in quality journals from the Australian Business Deans Council (ABDC) list is gathered from the Scopus database. This data set is used to determine the leading contributors and contributions. The content analysis of these articles sheds light on the factors influencing market volatility and the potential research directions in this subject area.
Findings
The findings show that researchers in this sector are becoming more interested in studying the association of stock markets with “cryptocurrencies” and “bitcoin” during “COVID-19.” The outcomes of this study indicate that most studies found oil prices, policy uncertainty and investor sentiments have a significant impact on market volatility. However, there were mixed results on the impact of institutional flows and algorithmic trading on stock volatility, and a consensus cannot be established. This study also identifies the gaps and paves the way for future research in this subject area.
Originality/value
This paper fills the gap in the existing literature by comprehensively reviewing the articles on major factors impacting stock market volatility highlighting the theoretical relationship and empirical results.
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Mumtaz Ali, Ahmed Samour, Foday Joof and Turgut Tursoy
This study aims to assess how real income, oil prices and gold prices affect housing prices in China from 2010 to 2021.
Abstract
Purpose
This study aims to assess how real income, oil prices and gold prices affect housing prices in China from 2010 to 2021.
Design/methodology/approach
This study uses a novel bootstrap autoregressive distributed lag (ARDL) testing to empirically analyze the short and long links among the tested variables.
Findings
The ARDL estimations demonstrate a positive impact of oil price shocks and real income on housing market prices in both the phrases of the short and long run. Furthermore, the results reveal that gold price shocks negatively affect housing prices both in the short and long run. The result can be attributed to China’s housing market and advanced infrastructure, resulting in a drop in housing prices as gold prices increase. Additionally, the prediction of housing market prices will provide a base and direction for housing market investors to forecast housing prices and avoid losses.
Originality/value
To the best of the authors’ knowledge, this is the first attempt to analyze the effect of gold price shocks on housing market prices in China.
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