Name and surname:
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Elham Kamal, PhD.
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Document type:
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Research/art/teacher profile of a person
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The name of the university:
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Comenius University Bratislava
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The seat of the university:
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Šafárikovo námestie 6, 818 06 Bratislava
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III.a - Occupation-position | III.b - Institution | III.c - Duration |
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Assistant Professor | Institute of Economics, Faculty of Social and Economic Sciences, Comenius University | 1/1/2024-present |
Lecturer | University of Mazandaran | 2018-2023 |
Researcher | Laboratoire d’Economie d’Orleans- University of Orleans, France | 2019-2021 |
V.1.a - Name of the profile course | V.1.b - Study programme | V.1.c - Degree | V.1.d - Field of study |
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Applied Econometrics | Applied Economics | Master | Economics and Management |
Operations Research | Applied Economics | Bachelor | Economics and Management |
Econometrics Modelling | Applied Economics | Master | Economics and Management |
Statistics | Applied Economics | Bachelor | Economics and Management |
Quantitative Analysis | Applied Economics | Bachelor | Economics and Management |
FTX Collapse and systemic risk spillovers from FTX Token to major cryptocurrencies. Finance Research Letters Journal(2023): We examine the dynamic lower tail dependence and downside risk spillover between the FTX Token and seven major cryptocurrencies using Rotated Gumbel copula and GARCH copula quantile regression-based ∆CoVaR models. Daily data is analyzed from May 1, 2020 to December 31, 2022. The results show a strong evidence of risk spillover effects from FTX Token to crypto markets. Solana, followed by Cardano, displays the largest downside risk spillover. Tether and Bitcoin are affected least by the FTX fallout, receiving the lowest downside risk spillovers. Furthermore, the dynamic risk spillover effects are heterogeneous over time and comparatively different for each cryptocurrency.
Dependence structure among rare earth and financial markets: A multiscale-vine copula approach. Resources Policy Journal(2023): This paper examines the dynamic upper and lower tail dependence across Rare Earth Metals, clean energy, gold, world equity, Base metals, and crude oil markets at various time scales. Firstly, raw return series are decomposed into various time scales using the maximum overlapping discrete wavelet transform method, then the time-varying pairwise dependencies, accounting for the impact of the covariate (in our case, the rare earth stock index), are analysed using vine-copula. This so called multiscale-vine copula approach is applied to daily data from June 25, 2009 to October 7, 2022, covering the Covid-19 outbreak. The results show that, for raw returns, the rare earth market moderates the positive dependence between world equity and clean energy markets. At the short-term time scale, unlike other pairwise dependencies, rare earth eases the dependency between clean energies. During the Covid-19 pandemic period, the rare earth stock index significantly affects the correlation of the gold and oil markets and makes them more resilient to global health shocks. At the mid-term time scale, the impact of the rare earth index is more pronounced, for both the entire sample and during the Covid-19 outbreak, as the dynamic dependencies of most indices, such as clean energy-world equity, base metals-world equity, and crude oil-clean energy, significantly decline after accounting for the influence of Rare Earth Metals. The main result at the long-term time scale is that the Covid-19 pandemic moderates the dependency of clean energy-gold even further when considering the impact of the rare earth stock index. In general, the rare earth stock index plays a significant role in easing the extent of dependency in the medium term during the entire sample and the pandemic. These findings provide some useful implications for heterogeneous investors and market participants operating at various time scales.
Inflation expectations and the stock-bond nexus in the US: hedging implications. The European Journal of Finance, (2024): This paper first examines the impact of inflation expectations on the correlation and tail-dependence between stock and Treasury (corporate) bond markets in the US and then assesses the portfolio and hedging implications. Using dynamic C-vine copula models, the results show in several cases a shift in the stock-bond nexus after conditioning on the levels of inflation expectations. The average dynamic tail-dependence between stocks and 10- and 30-year Treasury bonds becomes positive in the post-Covid era. High inflation expectations intensify the average tail-dependence between stocks and mid-term corporate bonds since the Covid-19 outbreak, and between stock and Treasury bonds from early 2020 to the beginning of the conflict between Russia and Ukraine. A hedging analysis shows that the hedging effectiveness improves after taking into account the impact of inflation expectations on stock-bond nexus, especially in the post-Covid-19 subperiod. This hedging effectiveness sustains after changing the proxy of inflation expectations.
FTX Collapse and systemic risk spillovers from FTX Token to major cryptocurrencies. Finance Research Letters Journal(2023): We examine the dynamic lower tail dependence and downside risk spillover between the FTX Token and seven major cryptocurrencies using Rotated Gumbel copula and GARCH copula quantile regression-based ∆CoVaR models. Daily data is analyzed from May 1, 2020 to December 31, 2022. The results show a strong evidence of risk spillover effects from FTX Token to crypto markets. Solana, followed by Cardano, displays the largest downside risk spillover. Tether and Bitcoin are affected least by the FTX fallout, receiving the lowest downside risk spillovers. Furthermore, the dynamic risk spillover effects are heterogeneous over time and comparatively different for each cryptocurrency.
Dependence structure among rare earth and financial markets: A multiscale-vine copula approach. Resources Policy Journal(2023): This paper examines the dynamic upper and lower tail dependence across Rare Earth Metals, clean energy, gold, world equity, Base metals, and crude oil markets at various time scales. Firstly, raw return series are decomposed into various time scales using the maximum overlapping discrete wavelet transform method, then the time-varying pairwise dependencies, accounting for the impact of the covariate (in our case, the rare earth stock index), are analysed using vine-copula. This so called multiscale-vine copula approach is applied to daily data from June 25, 2009 to October 7, 2022, covering the Covid-19 outbreak. The results show that, for raw returns, the rare earth market moderates the positive dependence between world equity and clean energy markets. At the short-term time scale, unlike other pairwise dependencies, rare earth eases the dependency between clean energies. During the Covid-19 pandemic period, the rare earth stock index significantly affects the correlation of the gold and oil markets and makes them more resilient to global health shocks. At the mid-term time scale, the impact of the rare earth index is more pronounced, for both the entire sample and during the Covid-19 outbreak, as the dynamic dependencies of most indices, such as clean energy-world equity, base metals-world equity, and crude oil-clean energy, significantly decline after accounting for the influence of Rare Earth Metals. The main result at the long-term time scale is that the Covid-19 pandemic moderates the dependency of clean energy-gold even further when considering the impact of the rare earth stock index. In general, the rare earth stock index plays a significant role in easing the extent of dependency in the medium term during the entire sample and the pandemic. These findings provide some useful implications for heterogeneous investors and market participants operating at various time scales.
VIII.a - Name of the institution | VIII.b - Address of the institution | VIII.c - Duration (indicate the duration of stay) | VIII.d - Mobility scheme, employment contract, other (describe) |
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Laboratoire d’Economie d’Orleans, University of Orleans-France | Laboratoire d’Economie d’Orleans, University of Orleans, 8 Avenue du Parc Floral, 45100 Orleans | 2019-2021 | Visiting researcher |