Mr. Mohammad Abdullah is working as Assistant Professor of Finance at University of Southampton Malaysia. He is pursuing his Ph.D. in finance from Universiti Sultan Zainal Abidin, Malaysia. He holds an MBA and BBA degree in Finance from Independent University, Bangladesh (IUB). Prior to his current position, he worked at IUB, and held various positions in the banking sector of Bangladesh. Mr. Abdullah has published several scholarly articles on emerging financial issues in different international journals and possesses expertise in econometrics modeling, machine learning, sentiment analysis, deep learning, and big data analytics. His research interests encompass corporate finance, ESG, behavioral finance, banking, and FinTech.
Email : htasfiq@gmail.com ; M.Abdullah@soton.ac.uk
Research Interests
Quantitative finance, Empirical finance, Nonlinear dynamics, Cryptocurrency, NFTs, FinTech, Asset Pricing, Machine learning, Natural Language Processing
Articles in Peer-Reviewed Journals
Wali Ullah, G. M., Cavoli, T., Khan, I., & Abdullah, M. (2024). The Impact of Social Capital on Major Customer Supply Chain Power. Economics Letters. Volume 238, 111725. https://doi.org/10.1016/j.econlet.2024.111725
Abdullah, M., Sulong, Z., and Chowdhury, M. A. F. (2024). Explainable deep learning model for stock price forecasting using textual analysis. Expert Systems with Applications, Volume 249, Part C, 123740. https://doi.org/10.1016/j.eswa.2024.123740. Dataset.
Abakah, E. J. A., Abdullah, M., Dankwah, B., & Lee, C. C. (2024). Asymmetric dynamics between the Baltic Dry Index and financial markets during major global economic events. The North American Journal of Economics and Finance, Volume 72, 102126. https://doi.org/10.1016/j.najef.2024.102126
Abakah, E. J. A., Wali Ullah, G., Abdullah, M., Lee, C. C., & Sulong, Z. (2024). Correlation structure between fiat currencies and blockchain assets. Finance Research Letters, Volume 62, Part A, 105114. https://doi.org/10.1016/j.frl.2024.105114
Abakah, E. J. A., Abdullah, M., Tiwari, A. K., & Wali Ullah, G. (2024). Asymmetric dynamics between geopolitical conflict sentiment and cryptomarkets. Research in International Business and Finance, 102273. https://doi.org/10.1016/j.ribaf.2024.102273
Tiwari, A. K., Abakah, E. J. A., Abdullah, M., Adeabah, D., & Sahay, V. S. (2024). Time-varying relationship between international monetary policy and energy markets. Energy Economics, 131, 107339. https://doi.org/10.1016/j.eneco.2024.107339
Abakah, E. J. A., Abdullah, M., Yousaf, I., Tiwari, A. K., & Li, Y. (2024). Economic sanctions sentiment and global stock markets. Journal of International Financial Markets, Institutions and Money, 91, 101910. https://doi.org/10.1016/j.intfin.2023.101910
Abakah, E. J. A., Hossain, S., Abdullah, M., & Goodell, J. W. (2024). Global uncertainty factors and price connectedness between US electricity and blockchain markets: Findings from an R-square connectedness approach. Finance Research Letters, 104693. https://doi.org/10.1016/j.frl.2023.104693
Chowdhury, M. A. F., Prince, E. R., Shoyeb, M., & Abdullah, M. (2024). The threshold effect of institutional quality on sovereign debt and economic stability. Journal of Policy Modeling, 46(1), 39-59 . https://doi.org/10.1016/j.jpolmod.2023.12.001
Abdullah, M., Abakah, E. J. A., Wali Ullah, G.M., Tiwari, A. K., & Khan, I. (2023). Tail risk contagion across electricity markets in crisis periods. Energy Economics, https://doi.org/10.1016/j.eneco.2023.107100
Chowdhury, M. A. F., Abdullah, M., Azad, ATM., Sulong, Z., & Islam, M.N. (2023). Environmental, Social and Governance (ESG) Rating Prediction Using Machine Learning Approaches. Annals of Operations Research. https://doi.org/10.1007/s10479-023-05633-7
Sulong, Z., Abdullah, M., Adeabah, D., Abakah, E. J. A., & Asongu, S. (2023). Russia-Ukraine war and G7 debt markets: Evidence from public sentiment towards economic sanctions during the conflict. International Journal of Finance and Economics. https://doi.org/10.1002/ijfe.2887
Abakah, E. J. A., Adeabah, D., Tiwari, A. K., and Abdullah, M. (2023). Effect of Russia–Ukraine war sentiment on blockchain and FinTech stocks. International Review of Financial Analysis. https://doi.org/10.1016/j.irfa.2023.102948 . Dataset.
Wali Ullah, G.M., Khan, I. & Abdullah, M. (2023). Managerial ability and climate change exposure. International Journal of Managerial Finance. https://doi.org/10.1108/IJMF-12-2022-0551
Chowdhury, M. A. F., Abdullah, M., Nazia, N. N. C., & Roy, D. (2023). The nonlinear and threshold effects of IT investment on the banking sector of Bangladesh. Economic Change and Restructuring, 1-31. https://doi.org/10.1007/s10644-023-09541-5
Abdullah, M., Adeabah, D., Abakah, E. J. A., & Lee, C. C. (2023). Extreme return and volatility connectedness among real estate tokens, REITs, and other assets: The role of global factors and portfolio implications. Finance Research Letters, 104062. https://doi.org/10.1016/j.frl.2023.104062
Abakah, E. J. A., Ullah, G. M. W., Adekoya, O. B., Bonsu, C. O., & Abdullah, M. (2023). Blockchain market and eco-friendly financial assets: Dynamic price correlation, connectedness and spillovers with portfolio implications. International Review of Economics & Finance, 87, 218-243. https://doi.org/10.1016/j.iref.2023.04.028
Chowdhury, M. A. F., Abdullah, M., Alam, M., Abedin, M. Z., & Shi, B. (2023). NFTs, DeFi, and Other Assets Efficiency and Volatility Dynamics: An Asymmetric Multifractality Analysis. International Review of Financial Analysis, 81, 102642. https://doi.org/10.1016/j.irfa.2023.102642
Abdullah, M., Chowdhury, M. A. F., Uddin, A., & Moudud-Ul-Huq, S. (2023). Forecasting nonperforming loans using machine learning. Journal of Forecasting, 1– 26. https://doi.org/10.1002/for.2977
Alam, M., Chowdhury, M. A. F., Abdullah, M., & Masih, M. (2023). Volatility spillover and connectedness among REITs, NFTs, cryptocurrencies and other assets: Portfolio implications. Investment Analysts Journal. https://doi.org/10.1080/10293523.2023.2179161
Abdullah, M., Chowdhury, M. A. F., & Sulong, Z. (2023). Asymmetric efficiency and connectedness among green stocks, halal tourism stocks, cryptocurrencies, and commodities: Portfolio hedging implications. Resources Policy, 81, 103419. https://doi.org/10.1016/j.resourpol.2023.103419
Chowdhury, M. A. F., Abdullah, M., & Masih, M. (2022). COVID-19 Government Interventions and Cryptocurrency Market: Is There Any Optimum Portfolio Diversification? Journal of International Financial Markets. Institutions & Money, 81, 101691. https://doi.org/10.1016/j.intfin.2022.101691
Sulong, Z., Abdullah, M., & Chowdhury, M. A. F. (2022). Halal tourism demand and firm performance forecasting: New evidence from machine learning. Current Issues in Tourism. https://doi.org/10.1080/13683500.2022.2145458
Abdullah, M., Wali Ullah, G. M., & Chowdhury, M. A. F. (2022). The asymmetric effect of COVID-19 government interventions on global stock markets: New evidence from QARDL and threshold regression approaches. Investment Analysts Journal, 51(4), 268-288. https://doi.org/10.1080/10293523.2022.2112665
Ahmed, S. U., Ahmed, S. P., Abdullah, M., & Karmaker, U. (2022). Do socio-political factors affect investment performance?. Cogent Economics & Finance, 10(1), 2113496. https://doi.org/10.1080/23322039.2022.2113496
Abdullah, M. (2021). The implication of machine learning for financial solvency prediction: an empirical analysis on public listed companies of Bangladesh. Journal of Asian Business and Economic Studies, 28(4), 303-320. https://doi.org/10.1108/JABES-11-2020-0128
Ahmed, S. U., Abdullah, M., & Ahmed, S. P. (2017). Linkage between corporate social performance and stock return: An evidence from financial sector of Bangladesh. The Journal of Developing Areas, 51(2), 287-299. https://doi.org/10.1353/jda.2017.0045
Book Chapters
Tiwari, A. K., Abakah, E. J. A., Abdullah, M., & Sulong, Z. (2023). What investors need to know about forecasting stock market return volatility using artificial intelligence. Reference Module in Social Sciences. https://doi.org/10.1016/B978-0-44-313776-1.00143-4
Working Papers
Sulong, Z., and Chowdhury, M. A. F. , Abdullah, M., Hall C.M. (2024). Constructing sustainable halal tourism composite performance index for the global halal tourism industry. Available at SSRN: https://ssrn.com/abstract=4711328 or http://dx.doi.org/10.2139/ssrn.4711328. Dataset
Abdullah, M., and Chowdhury, M.A.F., Sulong, Z., & Masih, R. (2023) Explainable Sentiment-Based Tail Risk Connectedness Portfolio Optimization Using Deep Reinforcement Learning. Available at SSRN: https://ssrn.com/abstract=4627988 or http://dx.doi.org/10.2139/ssrn.4627988
Bakather, A. A., Chowdhury, M.A.F., Al-Bashrawi, M. A., & Abdullah, M. (2023). Time-Frequency Dynamics of Public Sentiment Transmission in GCC Equity Markets: Evidence from Textual Analysis. Available at SSRN: https://ssrn.com/abstract=4596124 or http://dx.doi.org/10.2139/ssrn.4596124
Abakah, E.J.A., Chowdhury, M.A.F., Abdullah, M., & Hammoudeh, S. M. (2023). Energy Tokens and Green Energy Markets Under Crisis Periods: a Quantile Downside Tail Risk Dependence Analysis. Available at SSRN: https://ssrn.com/abstract=4593849 or http://dx.doi.org/10.2139/ssrn.4593849
Abdullah, M., Sulong, Z., and Chowdhury, M. A. F. (2023). Explainable Deep Learning Model for Stock Price Forecasting Using Textual Analysis. Available at SSRN: https://ssrn.com/abstract=4355596 or http://dx.doi.org/10.2139/ssrn.4355596. Dataset.
Abakah, E. J. A., Adeabah, D., Tiwari, A. K., & Abdullah, M. (2023). Analyzing the Effect of Public Sentiment Towards Economic Sanctions News during Russia-Ukraine Conflict on Blockchain Market and Fintech Industry . Available at SSRN: https://ssrn.com/abstract=4359071 or http://dx.doi.org/10.2139/ssrn.4359071. Dataset.
Abdullah, M. (2022). Tail risk diversification using deep path integrals reinforcement learning . Available at SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4290075
Grants
Barriers and drivers of blockchain adoption in emerging markets. Funder: Ethereum Foundation [Grant ID: FY23-1025]. Ongoing.
Social Media and Equity Market: Twitter- Based Sentiment Index for GCC Region. Funder: IRC for Finance & Digital Economy, King Fahd University of Petroleum & Minerals [Project No: INFE2202]. Completed.
A proposed framework for state level tourism income forecasting model using multi-source big data analytics: A case of Terengganu. Funder: Universiti Sultan Zainal Abidin, Malaysia [Project No: RR428]. Completed.