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  1. Article: COVID-19 and oil market risks: Evidence from new datasets.

    Salisu, Afees A / Hammed, Yinka S

    MethodsX

    2023  Volume 10, Page(s) 102008

    Abstract: We evaluate the predictive value of the newly constructed six COVID-19 indices for oil market risks from 31st December, 2019 (when COVID-19 started) to 28th December, 2021. We show that, on average, higher values of the COVID-19 indices appear to have ... ...

    Abstract We evaluate the predictive value of the newly constructed six COVID-19 indices for oil market risks from 31st December, 2019 (when COVID-19 started) to 28th December, 2021. We show that, on average, higher values of the COVID-19 indices appear to have heightened oil market risks albeit with the converse for Vaccine index regardless of the choice of oil price proxy. The predictive value of the indices is sustained over multiple out-of-sample forecasts and we attribute the outcome to the increased uncertainties associated with the pandemic. Therefore, measures aimed at mitigating these uncertainties can help moderate the oil market risks.•Testing the predictive value of the newly constructed COVID-19 measures for the out-of-sample forecasting of oil market risks.•Increased uncertainties associated with the pandemic tend to raise the level of oil market risks.•Measures aimed at mitigating these uncertainties can help moderate the oil market risks.
    Language English
    Publishing date 2023-01-07
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2830212-6
    ISSN 2215-0161
    ISSN 2215-0161
    DOI 10.1016/j.mex.2023.102008
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: The U.S. Nonfarm Payroll and the out-of-sample predictability of output growth for over six decades.

    Salisu, Afees A / Olaniran, Abeeb

    Quality & quantity

    2022  Volume 56, Issue 6, Page(s) 4663–4673

    Abstract: We examine the predictive prowess of the U.S. Nonfarm Payroll (USNFP) for output growth in the U.S. covering over six decades from 1947 to 2021. Using two different measures of output growth (with Gross Domestic Product growth being used for the main ... ...

    Abstract We examine the predictive prowess of the U.S. Nonfarm Payroll (USNFP) for output growth in the U.S. covering over six decades from 1947 to 2021. Using two different measures of output growth (with Gross Domestic Product growth being used for the main analysis and growth in Industrial Production Index for robustness check), our predictability results show that the U.S. Nonfarm Payroll offers some predictive information for output growth in the U.S. and the out-of-sample forecast results equally attest to the superiority of the USNFP-based model over the model that ignores it. Our findings have implications for policy directions in the U.S. and various national and regional governments, multilateral agencies and investors whose economic and financial conditions are directly or indirectly linked with the U.S. economy.
    Language English
    Publishing date 2022-02-13
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2003280-8
    ISSN 1573-7845 ; 0033-5177
    ISSN (online) 1573-7845
    ISSN 0033-5177
    DOI 10.1007/s11135-022-01342-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: The predictive power of Bitcoin prices for the realized volatility of US stock sector returns.

    Bouri, Elie / Salisu, Afees A / Gupta, Rangan

    Financial innovation

    2023  Volume 9, Issue 1, Page(s) 62

    Abstract: This paper is motivated by Bitcoin's rapid ascension into mainstream finance and recent evidence of a strong relationship between Bitcoin and US stock markets. It is also motivated by a lack of empirical studies on whether Bitcoin prices contain useful ... ...

    Abstract This paper is motivated by Bitcoin's rapid ascension into mainstream finance and recent evidence of a strong relationship between Bitcoin and US stock markets. It is also motivated by a lack of empirical studies on whether Bitcoin prices contain useful information for the volatility of US stock returns, particularly at the sectoral level of data. We specifically assess Bitcoin prices' ability to predict the volatility of US composite and sectoral stock indices using both in-sample and out-of-sample analyses over multiple forecast horizons, based on daily data from November 22, 2017, to December, 30, 2021. The findings show that Bitcoin prices have significant predictive power for US stock volatility, with an inverse relationship between Bitcoin prices and stock sector volatility. Regardless of the stock sectors or number of forecast horizons, the model that includes Bitcoin prices consistently outperforms the benchmark historical average model. These findings are independent of the volatility measure used. Using Bitcoin prices as a predictor yields higher economic gains. These findings emphasize the importance and utility of tracking Bitcoin prices when forecasting the volatility of US stock sectors, which is important for practitioners and policymakers.
    Language English
    Publishing date 2023-03-06
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 2824759-0
    ISSN 2199-4730 ; 2199-4730
    ISSN (online) 2199-4730
    ISSN 2199-4730
    DOI 10.1186/s40854-023-00464-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Assessing the hedging potential of gold and other precious metals against uncertainty due to epidemics and pandemics.

    Sikiru, Abdulsalam Abidemi / Salisu, Afees A

    Quality & quantity

    2021  Volume 56, Issue 4, Page(s) 2199–2214

    Abstract: We assess the hedging capabilities of four prominent precious metals namely gold, palladium, platinum and silver against market risks due to epidemics and pandemics. The research objective is informed by the COVID-19 pandemic which amplifies health risks ...

    Abstract We assess the hedging capabilities of four prominent precious metals namely gold, palladium, platinum and silver against market risks due to epidemics and pandemics. The research objective is informed by the COVID-19 pandemic which amplifies health risks with attendant concerns for financial markets. We utilize the health-related uncertainty index developed by Baker et al. (Equity market volatility: infectious disease tracker [INFECTDISEMVTRACK], 2020) which measures uncertainty in the financial markets due to infectious diseases including the COVID-19 pandemic and construct a predictive model that accommodates the salient features of both the predictand and predictor series. Our results support the safe haven property only for gold before and during the COVID-19 pandemic. We push the analysis further for in-sample and out-of-sample forecast evaluation and find that accounting for uncertainty due to infectious diseases improves the forecast of the four precious metals relative to the benchmark model (historical average). We highlight for investors that the gold market remains the safest market among the precious metals particularly during the COVID-19 pandemic.
    Language English
    Publishing date 2021-08-06
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2003280-8
    ISSN 1573-7845 ; 0033-5177
    ISSN (online) 1573-7845
    ISSN 0033-5177
    DOI 10.1007/s11135-021-01214-7
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: COVID-19 pandemic and the crude oil market risk: hedging options with non-energy financial innovations.

    Salisu, Afees A / Obiora, Kingsley

    Financial innovation

    2021  Volume 7, Issue 1, Page(s) 34

    Abstract: This study examines the hedging effectiveness of financial innovations against crude oil investment risks, both before and during the COVID-19 pandemic. We focus on the non-energy exchange traded funds (ETFs) as proxies for financial innovations given ... ...

    Abstract This study examines the hedging effectiveness of financial innovations against crude oil investment risks, both before and during the COVID-19 pandemic. We focus on the non-energy exchange traded funds (ETFs) as proxies for financial innovations given the potential positive correlation between energy variants and crude oil proxies. We employ a multivariate volatility modeling framework that accounts for important statistical features of the non-energy ETFs and oil price series in the computation of optimal weights and optimal hedging ratios. Results show evidence of hedging effectiveness for the financial innovations against oil market risks, with higher hedging performance observed during the pandemic. Overall, we show that sectoral financial innovations provide resilient investment options. Therefore, we propose that including the ETFs in an investment portfolio containing oil could improve risk-adjusted returns, especially in similar financial crisis as witnessed during the pandemic. In essence, our results are useful for investors in the global oil market seeking to maximize risk-adjusted returns when making investment decisions. Moreover, by exploring the role of structural breaks in the multivariate volatility framework, our attempts at establishing robustness for the results reveal that ignoring the same may lead to wrong conclusions about the hedging effectiveness.
    Language English
    Publishing date 2021-05-10
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 2824759-0
    ISSN 2199-4730 ; 2199-4730
    ISSN (online) 2199-4730
    ISSN 2199-4730
    DOI 10.1186/s40854-021-00253-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: The return volatility of cryptocurrencies during the COVID-19 pandemic: Assessing the news effect.

    Salisu, Afees A / Ogbonna, Ahamuefula E

    Global finance journal

    2021  Volume 54, Page(s) 100641

    Abstract: In this paper, we test the role of news in the predictability of return volatility of digital currency market during the COVID-19 pandemic. We use hourly data for cryptocurrencies and daily data for the news indicator, thus, the GARCH MIDAS framework ... ...

    Abstract In this paper, we test the role of news in the predictability of return volatility of digital currency market during the COVID-19 pandemic. We use hourly data for cryptocurrencies and daily data for the news indicator, thus, the GARCH MIDAS framework which allows for mixed data frequencies is adopted. We validate the presupposition that fear-induced news triggered by the COVID-19 pandemic increases the return volatilities of the cryptocurrencies compared with the period before the pandemic. We also establish that the predictive model that incorporates the news effects forecasts the return volatility better than the benchmark (historical average)model.
    Language English
    Publishing date 2021-04-17
    Publishing country United States
    Document type News
    ISSN 1873-5665
    ISSN (online) 1873-5665
    DOI 10.1016/j.gfj.2021.100641
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article: COVID-19 pandemic and financial innovations.

    Salisu, Afees A / Sikiru, Abdulsalam Abidemi / Omoke, Philip C

    Quality & quantity

    2022  , Page(s) 1–20

    Abstract: This study is motivated around the COVID-19 pandemic as a source of rising financial market risks. Hence, we investigate whether pandemic-induced risks can be hedged by alternative investment in financial innovations captured in exchange traded funds ( ... ...

    Abstract This study is motivated around the COVID-19 pandemic as a source of rising financial market risks. Hence, we investigate whether pandemic-induced risks can be hedged by alternative investment in financial innovations captured in exchange traded funds (ETFs). We explore the hedging effectiveness of sectoral ETFs along with a battery of robustness measures. Following the predictability analyses, we find that financial innovations captured in ETFs can effectively hedge both pandemic-induced and financially engineered market risks especially after controlling for the role of oil price in the predictive model. Our model provides better in-sample and out-of-sample forecasting accuracy and economic gains than the benchmark model and this is more pronounced for the COVID-19 pandemic period.
    Language English
    Publishing date 2022-10-06
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2003280-8
    ISSN 1573-7845 ; 0033-5177
    ISSN (online) 1573-7845
    ISSN 0033-5177
    DOI 10.1007/s11135-022-01540-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Predicting stock returns in the presence of COVID-19 pandemic: The role of health news.

    Salisu, Afees A / Vo, Xuan Vinh

    International review of financial analysis

    2020  Volume 71, Page(s) 101546

    Abstract: This study derives its motivation from the current global pandemic, COVID-19, to evaluate the relevance of health-news trends in the predictability of stock returns. We demonstrate this by using data covering top-20 worst-hit countries, distinctly in ... ...

    Abstract This study derives its motivation from the current global pandemic, COVID-19, to evaluate the relevance of health-news trends in the predictability of stock returns. We demonstrate this by using data covering top-20 worst-hit countries, distinctly in terms of reported cases and deaths. The results reveal that the model that incorporates health-news index outperforms the benchmark historical average model, indicating the significance of health news searches as a good predictor of stock returns since the emergence of the pandemic. We also find that accounting for "asymmetry" effect, adjusting for macroeconomic factors and incorporating financial news improve the forecast performance of the health news-based model. These results are consistently robust to data sample (both for the in-sample and out-of-sample forecast periods), outliers and heterogeneity.
    Language English
    Publishing date 2020-06-29
    Publishing country United States
    Document type Journal Article
    ISSN 1873-8079
    ISSN (online) 1873-8079
    DOI 10.1016/j.irfa.2020.101546
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: Geopolitical risk and forecastability of tail risk in the oil market: Evidence from over a century of monthly data

    Salisu, Afees A. / Pierdzioch, Christian / Gupta, Rangan

    Energy. 2021 Nov. 15, v. 235

    2021  

    Abstract: Using monthly data for the period from 1916 to 2020, we report that geopolitical risk, when decomposed into threats and actual risk, has predictive value for tail risk in the oil market. When we study the full sample of data, we find that threats ... ...

    Abstract Using monthly data for the period from 1916 to 2020, we report that geopolitical risk, when decomposed into threats and actual risk, has predictive value for tail risk in the oil market. When we study the full sample of data, we find that threats increase tail risk in the oil market, while actual acts related risk reduces tail risk at longer forecast horizons. While the findings of the full-sample analysis show that the effect of threats and acts on tail risk in the oil market is quantitatively small, results of an out-of-sample analysis show that, for several model configurations, geopolitical risks associated with threats are statistically significant predictors of tail risk in the oil market, even after controlling for a factor capturing global equity-market tail-risk spillovers. Our results have important investment implications.
    Keywords energy ; markets ; oils ; politics ; risk ; tail
    Language English
    Dates of publication 2021-1115
    Publishing place Elsevier Ltd
    Document type Article
    ZDB-ID 2019804-8
    ISSN 0360-5442 ; 0360-5442
    ISSN (online) 0360-5442
    ISSN 0360-5442
    DOI 10.1016/j.energy.2021.121333
    Database NAL-Catalogue (AGRICOLA)

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  10. Article ; Online: Hedging oil price risk with gold during COVID-19 pandemic.

    Salisu, Afees A / Vo, Xuan Vinh / Lawal, Adedoyin

    Resources policy

    2020  Volume 70, Page(s) 101897

    Abstract: This paper assesses the role of gold as a safe haven or hedge against crude oil price risks. We employ the asymmetric VARMA-GARCH model, using daily data from January 2016 to August 2020. To account for the impact of COVID-19 pandemic, we partitioned the ...

    Abstract This paper assesses the role of gold as a safe haven or hedge against crude oil price risks. We employ the asymmetric VARMA-GARCH model, using daily data from January 2016 to August 2020. To account for the impact of COVID-19 pandemic, we partitioned the data into two to reflect the periods before and during the pandemic. Our empirical results find gold as a significant safe haven against oil price risks. The optimal portfolio and hedging analyses conducted also validate the hedging effectiveness of gold against risk associated with oil. The robustness of our results is further confirmed using three other prominent precious metals - silver, platinum, and palladium. In sum, our results are useful for investors and portfolio managers that are desirous of using gold and other precious metals as portfolio rebalancing tools to minimize or circumvent risks associated with volatile oil returns.
    Language English
    Publishing date 2020-10-10
    Document type Journal Article
    ISSN 1873-7641
    ISSN (online) 1873-7641
    DOI 10.1016/j.resourpol.2020.101897
    Database MEDical Literature Analysis and Retrieval System OnLINE

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