Mohammad Hadi Sehatpour
Contact: mohammadhadi.sehatpour@student.uts.edu.au
Entered PhD Program: November 2022
Principal Supervisors: Dr Christina Nikitopoulos Sklibosios
Co-supervisor: Dr Kylie-Anne Richards and Professor Gareth W. Peters
Research topics:
- Computational Finance
- Econometrics and Time Series Analysis
- Financial Machine Learning
- Sustainable Finance
- Quantitative Trading
Academic Background and Work Experience:
Hadi is a PhD Candidate in Finance at the UTS Business School Finance Discipline Group, with research and teaching interests in financial econometrics, time series analysis, interest rate modelling, financial machine learning, and quantitative trading. He has nearly ten years of experience as a financial market analyst and portfolio manager across diverse institutions. Hadi has instructed courses on derivatives pricing, capital markets fundamentals, and market microstructure analysis in both financial and educational settings. Holding a master's degree in industrial management and operations research from the University of Tehran and a bachelor's degree in mechanical engineering from Shiraz University, he is currently focused on applying statistical machine learning techniques to explore the dynamics of the green bonds market.
Publications:
Sehatpour, M.H., Abedin, B. and Kazemi, A., 2022, "Talent Management in Government Organizations: Identification of Challenges and Ranking the Solutions to Address Them", International Journal of Productivity and Performance Management, 71(4), 1444-1468.
Basirian E. and Sehatpour, M. H., 2021, "Study of Factors Affecting the Liquidity of Futures Contracts, Regarding Order-Based Criteria", Journal of Contemporary Issues in Business and Government, 27, 2444-2454.
Sehatpour, M. H. and Kazemi, A., 2018, "Sustainable Fuel Portfolio Optimization: Integrated Fuzzy Multi-Objective Programming and Multi-Criteria Decision Making", Journal of Cleaner Production, 176, 304-319.
Sehatpour, M. H., Kazemi, A. and Sehatpour, H. E., 2017, "Evaluation of Alternative Fuels for Light-Duty Vehicles in Iran Using a Multi-Criteria Approach", Renewable and Sustainable Energy Reviews, 72, 295-310.
