Uncertainty Due to Pandemic and the Volatility Connectedness Among Asian REITs Market

Periola-Fatunsin, Ololade; Oliyide, Johnson A.; Fasanya, Ismail O.

doi:10.46557/001c.22323

Cited by 13 publications

(14 citation statements)

References 14 publications

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“…This is motivated from the on-going global pandemic, in [3.22] 0.1720 a [3.32] 0.1405 a [3.57] 0.2089 a [2.73] 1.8555 b [1.80] 4.2805 a [2.12] Telecoms 0.0537 a [3.64] 0.4602 a [3.32] 0.0397 a [3.14] 0.3429 b [1.97] 3.9582 a [3.73] 9.2347 a [4.84] Note(s): Model 1 is the Historical Average model; Model 2 is the model without control; Model 3 is the model with control. Uncertainty and stocks predictability variables (see Periola-Fatunsin et al, 2021;Bouri et al, 2021;Alqaralleh and Alessandra, 2021;Camillo and Gradojevic, 2021;Fasanya et al, 2021a, b;Al-Awadhi et al, 2020;Abuzayed et al, 2021;Baker et al, 2020;Salisu and Vo, 2020). In this study, we employ panel data forecasting approach to examine the performance of infectious disease uncertainty for sectoral stock return predictability.…”

Section: Conclusion and Implication For Policymentioning

confidence: 99%

“…Our analyses cover a total of 121 firms arranged in panel of 8 different sectors which include, industrials, Financials, Health care, Telecoms, Materials, Consumer services, Consumer goods and Technology. The empirical literature is satiated with studies on how uncertainty due to pandemic can predict economic and financial variables (see Periola-Fatunsin et al. , 2021; Bouri et al.…”

Section: Conclusion and Implication For Policymentioning

confidence: 99%

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Pandemic uncertainty and sectoral stock returns predictability in South Africa

Fasanya

2022

AJEMS

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PurposeIn this paper, the author examines the role of uncertainty due to pandemic on the predictability of sectoral stock returns in South Africa. This is motivated by the ongoing global pandemic, COVID-19, in predicting sector stock returns.Design/methodology/approachThe study considers estimation of dynamic panel data with dynamic common correlated effects estimator and two pair-wise forecast measures, namely Campbell and Thompson (2008) and Clark and West (2007) tests in dealing with the nested predictive models.FindingsThe results show that pandemic uncertainty has a negative and statistically significant effect on the different sector returns, implying that sector stock returns decline as the pandemic outbreak becomes more pronounced. While the single predictor model consistently outperforms the historical average model both for in-sample and out-of-sample, controlling for other macroeconomic variables effect improves the forecast accuracy of infectious diseases uncertainty. These results are consistently robust to both the in-sample and out-of-sample forecast periods, outliers and heterogeneity. These results have implications for portfolio diversification strategies, which we set aside for future research.Originality/valueThe empirical literature is satiated with studies on how news can predict economic and financial variables, however, the role of uncertainty due to infectious diseases in the stock return predictability especially at the sectoral level is less understudied, this is the main contribution of the study.

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Section: Conclusion and Implication For Policymentioning

confidence: 99%

Section: Conclusion and Implication For Policymentioning

confidence: 99%

Pandemic uncertainty and sectoral stock returns predictability in South Africa

Fasanya

2022

AJEMS

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“…Comprehensively, various studies have documented the dynamic integration of the global REITs (Ngene et al , 2020; Hestiawan and Prijadi, 2020; Nguyen et al , 2022); however, limited studies have ascertained the striking effect on the connectedness of REITs. For instance, Periola-Fatunsin et al (2021) analyzed how the uncertainty caused by COVID-19 induces volatility among the REIT market of the Asian region. Similarly, Chong and Phillips (2022) have also examined the loss of the real estate market due to the pandemic in the USA.…”

Section: Introductionmentioning

confidence: 99%

Quantile connectedness among real estate investment trusts during COVID-19: evidence from the extreme tails of distributions

Tong

Khaskheli

Masood

2023

IJHMA

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Purpose Given the evolving market integration, this study aims to explore the connectedness of 12 real estate investment trusts (REITs) during the COVID-19 period. Design/methodology/approach The connectedness of 12 REITs was examined by considering three sample periods: full period, COVID peak period and COVID recovery period by using the quantile vector autoregressive (VAR) approach. Findings The findings ascertain that REIT markets are sensitive to COVID, revealing significant connectedness during each sample period. The USA and The Netherlands are the major shock transmitters; thus, these countries are relatively better options for the predictive behavior of the rest of the REIT markets. In contrast, Hong Kong and Japan are the least favorable REIT markets with higher shock-receiving potential. Research limitations/implications The study recommends implications for real estate industry agents and investors to evaluate and anticipate the direction of return connectedness at each phase of the pandemic, such that they can incorporate those global REITs less vulnerable to unplanned crises. Apart from these implications, the study is limited to the global REIT markets and only focused on the period of COVID-19, excluding the concept of other financial and health crises. Originality/value This study uses a novel approach of the quantile-based VAR to determine the connectedness among REITs. Furthermore, the present work is a pioneer study because it is targeting different time periods of the pandemic. Additionally, the outcomes of the study are valuable for investors, policymakers and portfolio managers to formulate future development strategies and consolidate REITs during the period of crisis.

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“…In so doing, we employ the causality-in-quantiles test originally due proposed by [ 18 ] in order to capture inherent nonlinearities, structural breaks and regime switches in the series. Apart from financial series often known to exhibit these unfavourable statistical features, the COVID-19 pandemic has resulted into wild movements in the series and notable structural shifts (see [ 19 – 21 ]). This makes linear models, such as the Granger-causality test to be unfit for this study as it could lead to spurious results resulting from misspecification bias.…”

Section: Introductionmentioning

confidence: 99%

Economic uncertainty of pandemic and international airlines behaviour

2022

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This paper examines the role of uncertainty due to infectious diseases in predicting twenty International airline stocks within a nonparametric causality-in-quantiles framework. We observe that: First, the BDS test shows that nonlinearity is very important when examining the causal relationship between EMV-ID and airline stock returns and its volatility. Second, the nonparametric quantiles-based causality test shows that airline stocks predictability driven by pandemic-based uncertainty is stronger mostly around the lower quantiles, with weak evidences in middle and higher quantiles. Relevant policy implications can be drawn from these findings.

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Uncertainty Due to Pandemic and the Volatility Connectedness Among Asian REITs Market

Cited by 13 publications

References 14 publications

Pandemic uncertainty and sectoral stock returns predictability in South Africa

Pandemic uncertainty and sectoral stock returns predictability in South Africa

Quantile connectedness among real estate investment trusts during COVID-19: evidence from the extreme tails of distributions

Economic uncertainty of pandemic and international airlines behaviour

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