ORCID Profile
0000-0003-1472-0722
Current Organisation
University of Ghana Business School
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Publisher: Elsevier BV
Date: 09-2023
Publisher: Elsevier BV
Date: 03-2022
Publisher: Elsevier BV
Date: 12-2018
Publisher: Elsevier BV
Date: 02-2023
Publisher: Elsevier BV
Date: 2023
DOI: 10.2139/SSRN.4437042
Publisher: Emerald
Date: 08-05-2023
DOI: 10.1108/IJMF-09-2021-0428
Abstract: This paper investigates the static and dynamic directional return spillovers and dependence among green investments, carbon markets, financial markets and commodity markets from January 2013 to September 2020. This study employed both the quantile vector autoregression (QVAR) and time-varying parameter VAR (TVP-VAR) technique to examine the magnitude of static and dynamic directional spillovers and dependence of markets. Results show that the magnitude of connectedness is extremely higher at quantile levels (q = 0.05 and q = 0.95) compared to those in the mean of the conditional distribution. This connotes that connectedness between green bonds and other assets increases with shock size for both negative and positive shocks. This further indicates that return shocks spread at a higher magnitude during extreme market conditions relative to normal periods. Additional analyses show the behavior of return transmission between green bond and other assets is asymmetric. The findings of this study offer significant implications for portfolio investors, policymakers, regulatory authorities and investment community in terms of carefully assessing the unique characteristics offered by each markets in terms of return spillovers and dependence and ersifying the portfolios. The study, first, uses a relatively new statistical technique, the QVAR advanced by Ando et al. (2018), to capture upper and lower tails’ quantile price connectedness and directional spillover. Therefore, the results possess adequate power against departure from mean-based conditional connectedness. Second, using a portfolio of green investments, carbon markets, financial markets and commodity markets, the uniqueness of this study lies in the examination of the static and dynamic dependence of the markets examined.
Publisher: Elsevier BV
Date: 04-2023
Publisher: Elsevier BV
Date: 11-2022
Publisher: Elsevier BV
Date: 08-2023
Publisher: Elsevier BV
Date: 09-2023
Publisher: Informa UK Limited
Date: 26-06-2022
Publisher: Elsevier BV
Date: 05-2023
Publisher: Elsevier BV
Date: 09-2020
Publisher: Elsevier BV
Date: 09-2022
Publisher: Wiley
Date: 06-09-2022
DOI: 10.1002/JTR.2550
Abstract: The major tourist destinations in the Asian region are promoting and maintaining a conducive tourism environment. The susceptibility of the major tourist destinations in Asia to the uncertainties may encumber the arrival of international tourists. However, to the best of our understanding the research in this area is scant. Further though the tourism‐uncertainty nexus has been widely explored in the literature, the deliberations in a time‐varying and frequency‐domain framework continue to be ignored. Thus, building upon the earlier deficiencies this study, investigates in a time and scale varying framework the tourism uncertainty/risk nexus for Singapore and Malaysia, two major tourist destinations in the Asian region. This article endeavors to investigate the role of world policy uncertainty, US Monetary Policy Uncertainty, geopolitical risk, Global Financial Stress Index and market volatility on international tourist arrivals in Malaysia and Singapore. To the best of our understanding, this study is the foremost to scrutinize the interrelatedness between these variables in a multivariate wavelet causality framework, from January 2000 to April 2020. Our results show that the global uncertainties manifested through different macro‐based indicators affect international tourism demand for the destination countries. During the subprime crisis, Euro‐crisis and the pandemics significant coherencies are perceptible. The major empirical findings of the impact of uncertainty indicators and geopolitical risk on international tourist arrivals over the recent period have important implications for policy makers and practitioners.
Publisher: Emerald
Date: 04-06-2018
DOI: 10.1108/IJMF-10-2017-0235
Abstract: The purpose of this paper is to re-examine the weak form efficiency of five African stock markets (South Africa, Nigeria, Egypt, Ghana and Mauritius) using various tests to assess the impact of non-linearity effect and thin trading which are prevalent in African markets on market efficiency. The weekly returns of S& P/IFC return indices for five African countries over the period 2000-2013 were obtained from DataStream and analyzed. The study adopted the newly developed Non-Linear Fourier unit root test advanced by Enders and Lee (2004, 2009) which allows for an unknown number of structural breaks with unknown functional forms and non-linearity in data generating process of stock prices series to test the Random Walk Hypothesis (RWH) for the five markets, and an augment regression model. In light of the empirical evidence the author(s) using Non-linear Fourier Unit Root Test only fail to reject the RWH for South Africa, Nigeria and Egypt leading to the conclusion that these markets follow the RWH and weak-form efficient whilst Ghana and Mauritius are weak-form inefficient. Besides, evaluating non-linear models without adjusting for thin trading effect shows that, South Africa and Ghana markets are weak-form efficient while Nigeria, Egypt and Mauritius are not. However, after accounting for thin trading effect, the author(s) find that South Africa and Egypt markets follow the RWH. The findings imply that market efficiency results depend on the methodology used. This paper provides further evidence on stock market efficiency in emerging markets. The finding suggests that thin trading and non-linearity effect influences markets efficiency tests in African stock markets. Thus, recent structural adjustment and liberalization policies have not enhanced stock market operations in Africa. This paper therefore has implications for policy makers and international investors.
Publisher: Elsevier BV
Date: 2023
Publisher: Informa UK Limited
Date: 09-09-2022
Publisher: Elsevier BV
Date: 06-2023
Publisher: Elsevier BV
Date: 2022
Publisher: Wiley
Date: 17-10-2022
DOI: 10.1111/IRFI.12393
Abstract: This research explores the distributional and directional predictabilities among Fintech, Bitcoin, and artificial intelligence stocks from March 2018 to January 2021 using nonparametric causality‐in‐quantile and crossquantilogram approaches. We also examine connectedness across the assets using a quantile VAR approach. The results indicate the existence of bidirectional causality‐in‐variance between the variables in a normal market. We also find that directional predictability among the assets is oscillatory over time lags. Finally, we observe a strong price connectedness for highly positive and negative changes. These results further document the ersification potential and safe‐haven properties of technology‐related assets for portfolio investors.
Publisher: Informa UK Limited
Date: 20-09-2022
Publisher: Elsevier BV
Date: 2023
DOI: 10.2139/SSRN.4385987
Publisher: Elsevier BV
Date: 03-2022
Publisher: Informa UK Limited
Date: 19-01-2023
Publisher: Elsevier BV
Date: 02-2023
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 2023
Publisher: Informa UK Limited
Date: 20-12-2021
Publisher: Springer Science and Business Media LLC
Date: 13-12-2022
Publisher: Informa UK Limited
Date: 02-07-2020
Publisher: Elsevier BV
Date: 02-2022
Publisher: Elsevier BV
Date: 09-2022
Publisher: Elsevier BV
Date: 06-2022
Publisher: Elsevier BV
Date: 07-2023
Publisher: Elsevier BV
Date: 12-2021
Publisher: Elsevier BV
Date: 03-2021
Publisher: Elsevier BV
Date: 2021
Publisher: MDPI AG
Date: 18-10-2022
DOI: 10.3390/JRFM15100477
Abstract: This paper aims to examine the connectedness between green and conventional assets, particularly during the period of economic downturn. Specifically, we examine quantile-based time-varying connectedness between the green bond market and other financial assets using quantile vector autoregression (QVAR) from 9 March 2018 to 10 March 2021. We use daily prices of S& P U.S. Treasury Bond Index, S& P US Aggregate Bond Index, S& P US Treasury Bond Current 10Y Index, S& P 500 Bond Index, S& P 500 Financials index, S& P 500 Energy Bond Index and S& P 500, giving a total of 784 observations, and using Composite Index as a representative of conventional assets classes and S& P Green Bond Index to denote the green bond market. Results shows the connectedness between green bonds and the conventional asset classes intensified during the outbreak of the Coronavirus pandemic (COVID-19) as investors shifted their investment towards fixed income assets due to the plunge in the prices of stocks and commodities. The results also shows that green bonds are strongly connected with treasury bonds, aggregate bonds and bond index, as they share similarities with respect to issuance, risk and governance. Connectedness is weak in the case of composite index and energy bond index, as their prices do not have substantial influence on the green bond market. The study highlights the hedging and ersification benefits of green bonds. We have several implications for portfolio managers, policy makers and researchers.
Publisher: Wiley
Date: 09-07-2020
DOI: 10.1002/RFE.1113
Publisher: Elsevier BV
Date: 11-2023
Publisher: Elsevier BV
Date: 04-2022
Publisher: Elsevier BV
Date: 08-2022
Publisher: Wiley
Date: 19-09-2023
DOI: 10.1002/IJFE.2887
Publisher: Elsevier BV
Date: 12-2021
Publisher: Elsevier BV
Date: 06-2023
Publisher: Informa UK Limited
Date: 18-07-2022
Publisher: Elsevier BV
Date: 05-2023
Publisher: Informa UK Limited
Date: 16-01-2023
Publisher: Elsevier BV
Date: 05-2023
Publisher: Elsevier BV
Date: 09-2022
Publisher: Springer Science and Business Media LLC
Date: 14-03-2023
Publisher: Elsevier BV
Date: 2020
Publisher: Informa UK Limited
Date: 20-12-2022
No related grants have been discovered for Emmanuel Joel Aikins Abakah.