Jules Clement Mba

Personal Details

First Name:	Jules Clement
Middle Name:
Last Name:	Mba
Suffix:
RePEc Short-ID:	pmb33
	[This author has chosen not to make the email address public]

Affiliation

College of Business and Economics
University of Johannesburg

Auckland Park, South Africa
https://www.uj.ac.za/faculties/college-of-business-and-economics/
RePEc:edi:serauza (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

1. Jules Clément Mba & Sutene Mwambetania Mwambi & Edson Pindza, 2022. "A Monte Carlo Approach to Bitcoin Price Prediction with Fractional Ornstein–Uhlenbeck Lévy Process," Forecasting, MDPI, vol. 4(2), pages 1-11, March.

   Cited by:

   1. Kate Murray & Andrea Rossi & Diego Carraro & Andrea Visentin, 2023. "On Forecasting Cryptocurrency Prices: A Comparison of Machine Learning, Deep Learning, and Ensembles," Forecasting, MDPI, vol. 5(1), pages 1-14, January.

2. Paul Gatabazi & Gaëtan Kabera & Jules Clement Mba & Edson Pindza & Sileshi Fanta Melesse, 2022. "Cryptocurrencies and Tokens Lifetime Analysis from 2009 to 2021," Economies, MDPI, vol. 10(3), pages 1-14, March.

   Cited by:

   1. Arsenii Vilkov & Gang Tian, 2023. "Blockchain’s Scope and Purpose in Carbon Markets: A Systematic Literature Review," Sustainability, MDPI, vol. 15(11), pages 1-27, May.

3. Ur Koumba & Calvin Mudzingiri & Jules Mba, 2020. "Does uncertainty predict cryptocurrency returns? A copula-based approach," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 13(1), pages 67-88, January.

   Cited by:

   1. Papadamou, Stephanos & Kyriazis, Nikolaos A. & Tzeremes, Panayiotis G., 2021. "Non-linear causal linkages of EPU and gold with major cryptocurrencies during bull and bear markets," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
   2. Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
   3. Umar, Muhammad & Shahzad, Fakhar & Ullah, Irfan & Fanghua, Tong, 2023. "A comparative analysis of cryptocurrency returns and economic policy uncertainty pre- and post-Covid-19," Research in International Business and Finance, Elsevier, vol. 65(C).
   4. Inzamam Ul Haq & Apichit Maneengam & Supat Chupradit & Wanich Suksatan & Chunhui Huo, 2021. "Economic Policy Uncertainty and Cryptocurrency Market as a Risk Management Avenue: A Systematic Review," Risks, MDPI, vol. 9(9), pages 1-24, September.
   5. Ahmed, Walid M.A. & Al Mafrachi, Mustafa, 2021. "Do higher-order realized moments matter for cryptocurrency returns?," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 483-499.
   6. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
   7. Linn Arnell & Emma Engström & Gazi Salah Uddin & Md. Bokhtiar Hasan & Sang Hoon Kang, 2023. "Volatility spillovers, structural breaks and uncertainty in technology sector markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-31, December.
   8. Nikolaos A. Kyriazis, 2021. "The Nexus of Sophisticated Digital Assets with Economic Policy Uncertainty: A Survey of Empirical Findings and an Empirical Investigation," Sustainability, MDPI, vol. 13(10), pages 1-25, May.

4. Kofi Agyarko Ababio & Jules Clement Mba & Ur Koumba & Lau Evan, 2020. "Optimisation of mixed assets portfolio using copula differential evolution: A behavioural approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1780838-178, January.

   Cited by:

   1. Mario I. Contreras-Valdez & José Antonio Núñez & Guillermo Benavides Perales, 2022. "Bitcoin in Portfolio Selection: A Multivariate Distribution Approach," SAGE Open, , vol. 12(2), pages 21582440221, May.

5. Jules Clement Mba & Sutene Mwambi, 2020. "A Markov-switching COGARCH approach to cryptocurrency portfolio selection and optimization," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(2), pages 199-214, June.

   Cited by:

   1. John Weirstrass Muteba Mwamba & Sutene Mwambetania Mwambi, 2021. "Assessing Market Risk in BRICS and Oil Markets: An Application of Markov Switching and Vine Copula," IJFS, MDPI, vol. 9(2), pages 1-22, May.
   2. Osman, Myriam Ben & Galariotis, Emilios & Guesmi, Khaled & Hamdi, Haykel & Naoui, Kamel, 2023. "Diversification in financial and crypto markets," International Review of Financial Analysis, Elsevier, vol. 89(C).
   3. Mario I. Contreras-Valdez & José Antonio Núñez & Guillermo Benavides Perales, 2022. "Bitcoin in Portfolio Selection: A Multivariate Distribution Approach," SAGE Open, , vol. 12(2), pages 21582440221, May.

6. Gatabazi, P. & Mba, J.C. & Pindza, E., 2019. "Modeling cryptocurrencies transaction counts using variable-order Fractional Grey Lotka-Volterra dynamical system," Chaos, Solitons & Fractals, Elsevier, vol. 127(C), pages 283-290.

   Cited by:

   1. P. Gatabazi & J. C. Mba & E. Pindza, 2022. "Grey Verhulst model and its chaotic behaviour with application to Bitcoin adoption," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 45(1), pages 327-341, June.
   2. Nokhaiz Tariq Khan & Javed Aslam & Ateeq Abdul Rauf & Yun Bae Kim, 2022. "The Case of South Korean Airlines-Within-Airlines Model: Helping Full-Service Carriers Challenge Low-Cost Carriers," Sustainability, MDPI, vol. 14(6), pages 1-19, March.
   3. Jules Clément Mba & Sutene Mwambetania Mwambi & Edson Pindza, 2022. "A Monte Carlo Approach to Bitcoin Price Prediction with Fractional Ornstein–Uhlenbeck Lévy Process," Forecasting, MDPI, vol. 4(2), pages 1-11, March.
   4. Xiong, Pingping & Li, Kailing & Shu, Hui & Wang, Junjie, 2021. "Forecast of natural gas consumption in the Asia-Pacific region using a fractional-order incomplete gamma grey model," Energy, Elsevier, vol. 237(C).
   5. Chen, Yan & Lifeng, Wu & Lianyi, Liu & Kai, Zhang, 2020. "Fractional Hausdorff grey model and its properties," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).

7. Gatabazi, P. & Mba, J.C. & Pindza, E. & Labuschagne, C., 2019. "Grey Lotka–Volterra models with application to cryptocurrencies adoption," Chaos, Solitons & Fractals, Elsevier, vol. 122(C), pages 47-57.

   Cited by:

   1. Nokhaiz Tariq Khan & Javed Aslam & Ateeq Abdul Rauf & Yun Bae Kim, 2022. "The Case of South Korean Airlines-Within-Airlines Model: Helping Full-Service Carriers Challenge Low-Cost Carriers," Sustainability, MDPI, vol. 14(6), pages 1-19, March.
   2. Jules Clément Mba & Sutene Mwambetania Mwambi & Edson Pindza, 2022. "A Monte Carlo Approach to Bitcoin Price Prediction with Fractional Ornstein–Uhlenbeck Lévy Process," Forecasting, MDPI, vol. 4(2), pages 1-11, March.
   3. Shu, Jingsi & Zhang, Yongping, 2023. "Fractal control and synchronization of population competition model based on the T–S fuzzy model," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
   4. Chen, Yan & Lifeng, Wu & Lianyi, Liu & Kai, Zhang, 2020. "Fractional Hausdorff grey model and its properties," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
   5. Wang, Zheng-Xin & Li, Dan-Dan & Zheng, Hong-Hao, 2020. "Model comparison of GM(1,1) and DGM(1,1) based on Monte-Carlo simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
   6. Mihaela Sterpu & Carmen Rocșoreanu & Georgeta Soava & Anca Mehedintu, 2023. "A Generalization of the Grey Lotka–Volterra Model and Application to GDP, Export, Import and Investment for the European Union," Mathematics, MDPI, vol. 11(15), pages 1-23, July.

8. Jules Clement Mba & Edson Pindza & Ur Koumba, 2018. "A differential evolution copula-based approach for a multi-period cryptocurrency portfolio optimization," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(4), pages 399-418, November.

   Cited by:

   1. Haffar, Adlane & Le Fur, Éric, 2022. "Time-varying dependence of Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 211-220.
   2. Osman, Myriam Ben & Galariotis, Emilios & Guesmi, Khaled & Hamdi, Haykel & Naoui, Kamel, 2023. "Diversification in financial and crypto markets," International Review of Financial Analysis, Elsevier, vol. 89(C).
   3. Jules Clement Mba & Sutene Mwambi, 2020. "A Markov-switching COGARCH approach to cryptocurrency portfolio selection and optimization," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(2), pages 199-214, June.
   4. Mario I. Contreras-Valdez & José Antonio Núñez & Guillermo Benavides Perales, 2022. "Bitcoin in Portfolio Selection: A Multivariate Distribution Approach," SAGE Open, , vol. 12(2), pages 21582440221, May.
   5. Jules Clément Mba & Magdaline Mbong Mai, 2022. "A Particle Swarm Optimization Copula-Based Approach with Application to Cryptocurrency Portfolio Optimisation," JRFM, MDPI, vol. 15(7), pages 1-14, June.

9. Beatrice D. Simo-Kengne & Kofi A. Ababio & Jules Mba & Ur Koumba, 2018. "Behavioral portfolio selection and optimization: an application to international stocks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(3), pages 311-328, August.

   Cited by:

   1. Omane-Adjepong, Maurice & Ababio, Kofi Agyarko & Alagidede, Imhotep Paul, 2019. "Time-frequency analysis of behaviourally classified financial asset markets," Research in International Business and Finance, Elsevier, vol. 50(C), pages 54-69.
   2. Jules Clément Mba & Kofi Agyarko Ababio & Samuel Kwaku Agyei, 2022. "Markowitz Mean-Variance Portfolio Selection and Optimization under a Behavioral Spectacle: New Empirical Evidence," IJFS, MDPI, vol. 10(2), pages 1-16, April.
   3. Jules Clement Mba & Sutene Mwambi, 2020. "A Markov-switching COGARCH approach to cryptocurrency portfolio selection and optimization," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(2), pages 199-214, June.
   4. Sweksha Srivastava & Abha Aggarwal & Pooja Bansal, 2024. "Efficiency Evaluation of Assets and Optimal Portfolio Generation by Cross Efficiency and Cumulative Prospect Theory," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 129-158, January.

10. Beatrice D. Simo-Kengne & Kofi Agyarko Ababio & Jules Mba & Ur Koumba & Makgale Molepo, 2018. "Risk, Uncertainty and Exchange Rate Behavior in South Africa," Journal of African Business, Taylor & Francis Journals, vol. 19(2), pages 262-278, April.

    Cited by:

    1. Lin Liu, 2022. "Economic Uncertainty and Exchange Market Pressure: Evidence From China," SAGE Open, , vol. 12(1), pages 21582440211, January.

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