Global commodity and equity markets spillovers to Africa during the COVID-19 pandemic

Urom, Christian; Ndubuisi, Gideon; Lo, Gaye Del; Yuni, Denis Nfor

doi:10.1016/j.ememar.2022.100948

Cited by 14 publications

(9 citation statements)

References 68 publications

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“…Across all the considered real estate indexes, the QR coefficients provide a distinct picture from the constant OLS coefficients, enabling us to examine possible asymmetries in the effects of geopolitical acts and threats on real estate price indexes across the bearish, normal and bullish market conditions. Indeed, we rely on past studies that have adopted this empirical model in the interpretation of the estimated coefficients (Nusair and Olson, 2019;Urom et al, 2022aUrom et al, , 2022b. First, as shown in Table 2, we find that across all quantiles, representing the three market conditions, the coefficients of the lagged real estate price index are significant and positive for the European, African and global indexes.…”

Section: Resultsmentioning

confidence: 72%

“…The economic effects of shocks from infectious diseases and GPRs became apparent in the measures taken to contain the COVID-19 outbreak and its consequences. A litany of literature exists that shows empirical evidence of the effect of infectious diseases (Mzoughi et al, 2019;Wang et al, 2021;Mushafiq, 2021;Urom et al, 2022aUrom et al, , 2022b and GPRs (Liu et al, 2021;Long and Guo, 2022;Brandt and Gao, 2019;Chien et al, 2021) on the economy in general. A few studies have also shown how infectious diseases affect housing prices in IJHMA 17,1 Geopolitical risks particular (Olds, 2020;Qian et al, 2021;Cheung et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…This permits a deeper analysis of the direction and sphere of influence under both bullish (upper quantiles) and bearish (lower quantiles) market conditions. Hence, as noted by Urom et al (2022aUrom et al ( , 2022b, the QR allows a thorough exploration of the data by permitting the effects of covariates to vary across the specified distribution of the dependent variable. For example, for a non-complex case of one covariate, b 0.1 > 0 indicates that an increase on the independent variable is associated with a positive influence on the 10th percentile of the dependent variable while b 0.9 < 0 suggests that the effect of the same increase becomes negative on the 90th percentile of the explained variable.…”

Section: Empirical Strategy: Quantile Regression Modelmentioning

confidence: 99%

“…where g c t denotes the composite geopolitical index. Following past studies such as Urom et al (2022aUrom et al ( , 2022b, we estimate both equations ( 6) and ( 7) by specifying nine quantiles (t = 0.10, 0.20,. . ., 0.90), which permits us to examine three market regimes including low quantiles (t = 0.10, 0.20, 0.30), which corresponds to bearish market condition; medium quantiles (t = 0.40, 0.50, 0.60), which is associated with normal market period; and upper IJHMA 17,1 quantiles (t = 0.70, 0.80, 0.90), which corresponds to bullish market condition.…”

Section: Geopolitical Risksmentioning

confidence: 99%

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Dynamic effects of geopolitical risks and infectious diseases on real estate markets

Yuni

Enwo-Irem²,

Urom

2023

IJHMA

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Purpose Geopolitical risks (GPR) and increase in equity market volatility due to health pandemics have great implications on assets prices around the world. Many empirical studies have focused on the effects of these risks on different financial assets. The purpose of this paper is to contribute to this related literature by examining the dynamic effects of GPRs and infectious diseases–induced equity market volatility on regional and global house price indexes. Design/methodology/approach This paper explores the asymmetric effects of infectious diseases and GPRs on house prices across different market conditions using the quantile regression approach. This technique enables us to examine the nonlinear asymmetric effects of GPRs and infectious diseases on both global and regional house price indexes using daily data from January 1, 2011, to June 3, 2022. It focuses on both the effects of a composite measure of GPR as well as the disaggregated effects of threats and acts (war) on the real estate markets under different market conditions. Findings The main findings of this study demonstrates that the effects of geopolitical and infectious diseases–related risks vary differently across regional real estate markets and the nature of the GPR. In particular, the effects of geopolitical threats are stronger than those of geopolitical acts, especially for the European, Asia-Pacific and North American regions during bullish market periods. Except for the effects of geopolitical threats during real estate market downturns, the African real estate market appears to be insulated from the effects of GPRs across all market conditions. Also, the authors show that infectious diseases increase losses in real estate investments when the market condition is bearish for all markets and could extend toward the normal market period for the North American, Asia-Pacific and European markets. However, across all the market conditions, the effects of the composite index of GPRs are not significant for the Asia-Pacific and European regional markets. Results are mixed for the remaining markets, especially for the global market. Whereas during bearish market periods, the effect is positive, it becomes negative when the market condition become normal and insignificant when it becomes bullish. For the North American and African regional markets, the effect is positive under the bearish market state. Originality/value Increase in equity market volatility due to infectious diseases as well as conflicts and tensions among major powers, including potential risks of financial instability, all lead to significant increase in shocks to financial markets. To the best of the authors’ knowledge, this is the first study to analyze the asymmetric and comparative effects of GPRs and infectious diseases–related equity market volatility on real estate investments across different regions and market conditions. Because of the complexity of these risks and policy shifts, and the characteristics and heterogeneity of different regional financial markets, the impacts of shock from these risks are intuitively diverse, with practical implications for portfolio management.

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Section: Resultsmentioning

confidence: 72%

Section: Discussionmentioning

confidence: 99%

Section: Empirical Strategy: Quantile Regression Modelmentioning

confidence: 99%

Section: Geopolitical Risksmentioning

confidence: 99%

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Dynamic effects of geopolitical risks and infectious diseases on real estate markets

Yuni

Enwo-Irem²,

Urom

2023

IJHMA

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“…Quantifying and analyzing the relationship between GCC financial markets and the global economy has received less attention in previous studies, which have already focused on developed countries (Laborda and Olmo, 2021;Umar et al, 2021;Mensi et al, 2022;Mensi et al, 2023) and, to a lesser extent, on large emerging economies (Balcilar et al, 2018;Bouri et al, 2020;Xie et al, 2020;Urom et al, 2022). It should also be noted that financial markets can be affected by a variety of factors during global economic crises, including oil prices (Lin and Wu, 2022;Mensi et al, 2015Mensi et al, , 2022Mensi et al, , 2023, geopolitical risks (GPRs) (Balcilar et al, 2018;Das et al,2019), uncertainty (Baker et al, 2016), commodity prices (Akinsola and Odhiambo, 2020), interest rate changes (Gu et al, 2022) and gold prices (Gokmenoglu and Fazlollahi, 2015;Arfaoui and Ben Rejeb, 2017).…”

Section: Introductionmentioning

confidence: 99%

Global hidden factors predicting financial distress in Gulf Arab states: a quantile–time–frequency analysis

Trabelsi

2023

JFEP

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Purpose This study aims to uncover the main predictors of financial distress in the Gulf Cooperation Council (GCC) countries using a wide range of global factors and asset classes. Design/methodology/approach This study uses novel approaches that take into account extreme events as well as the nonlinear behavior of time series over various time intervals (i.e. short, medium and long term) and during boom and bust episodes. This study primarily uses the conditional value at risk (CoVaR), the quantile multivariate causality test and the partial wavelet coherence method. The data collection period ranges from March 2014 to September 2022. Findings US T-bills and gold are the primary factors that can increase financial stability in the GCC region, according to VaRs and CoVaRs. More proof of the predictive value of the oil, gold and wheat markets, as well as geopolitical tensions, uncertainty over US policy and volatility in the oil and US equities markets, is provided by the multivariate causality test. When low extreme quantiles or cross extreme quantiles are taken into account, these results are substantial and sturdy. Lastly, after adjusting for the effect of crude oil prices, this study’s wavelet coherence results indicate diminished long-run connections between the GCC stock market and the chosen global determinants. Research limitations/implications Despite the implications of the author’s research for decision makers, there are some limitations mainly related to the selection of Morgan Stanley Capital International (MSCI) GCC ex-Saudi Arabia. Considering the economic importance of the Kingdom of Saudi Arabia (KSA) in the region, the author believes that it would be better to include this country in the data to obtain more robust results. In addition, there is evidence in the literature of the existence of heterogeneous responses to global shocks; some markets are more vulnerable than others. This is another limitation of this study, as this study considers the GCC as a bloc rather than each country individually. These limitations could open up further research opportunities. Originality/value These findings are important for investors seeking to manage their portfolios under extreme market conditions. They are also important for government policies aimed at mitigating the impact of external shocks.

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Connectedness and risk spillovers among sub-Saharan Africa and MENA equity markets

Lo,

Marcelin,

Bassène

et al. 2024

Emerging Markets Review

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Global commodity and equity markets spillovers to Africa during the COVID-19 pandemic

Cited by 14 publications

References 68 publications

Dynamic effects of geopolitical risks and infectious diseases on real estate markets

Dynamic effects of geopolitical risks and infectious diseases on real estate markets

Global hidden factors predicting financial distress in Gulf Arab states: a quantile–time–frequency analysis

Connectedness and risk spillovers among sub-Saharan Africa and MENA equity markets

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