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Biography

Mahdi Mousavi (PhD, MSc, MA and BA) is an Assistant Professor of Finance at the University of Bradford School of Management. He achieved a PhD in finance from the University of Edinburgh Business School, UK, an MSc in Finance from Essex Business School, UK, and a BA and MA in Financial Management from Iran. Mahdi received a PhD scholarship from the College of Humanities and Social Science of the University of Edinburgh, and an abroad PhD scholarship from the Ministry of Science, Research and Technology of Iran. 

His research interest consists of a variety of topics including the design and performance evaluation of bankruptcy prediction models, credit scoring, corporate finance, and international business. His work has been published in several peer-reviewed international journals, such as Journal of International Management, Expert Systems with Applications, Annals of Operation Research, International Review of Financial Analysis, Journal of Developing Areas, and Journal of Economics, Business and Management. His recent research outcome about the multi-criteria ranking of bankruptcy prediction models is published as a chapter of the book entitled "Advances in DEA Theory and Applications with Extensions to Forecasting Models" by Wiley.

Mahdi teaches a number of executive, postgraduate and undergraduate modules. He developed/leads the MSc FinTech programme at the University of Bradford. Prior to this post, Mahdi was an Assistant Professor of Finance at the American University of Kean in China and a Lecturer of Finance at the University of Economic Science in Iran.  

He has the industry experience and before entering the academic world, worked as a capital market analyst for a number of years. As a result, Mahdi is committed to linking his teaching and research to practice. 

Research

Risk Modelling and Analysis
  • Failure (bankruptcy and distress) prediction models and credit scoring
  • Design of forecasting models with application in finance for both continuous (e.g., stock price changes and volatility) and discrete variables (e.g., bankruptcy, takeover) 
Data Envelopment Analysis (DEA) Application
  • Design of performance evaluation and benchmarking methodologies and their application in areas such as forecasting, banking and investment
  • Corporate finance optimization: liquidity, capital structure and dividend policy 
International Business and Finance
  • Emerging markets’ export spillover: firm heterogeneity, institutional, cultural, geographic and technology related determinants 

Professional activities

  • 01-JAN-17: University of Edinburgh Business School - PhD
  • 01-JAN-11: University of Essex - MSC
  • 01-JAN-08: ISU - Tehran - MA
  • 01-JAN-06: ISU - Tehran - BSc

Publications

Peer Reviewed Journal
TitleThe application of PROMETHEE Multi-criteria Decision Aid in Financial Decision Making: Case of Distress Prediction Models Evaluation (2020)
AuthorsMousavi, MM; Lin, J.
JournalExpert Systems with Applications
 
TitleA Comparative Analysis of Two-Stage Distress Prediction Models (2019)
AuthorsMousavi, M. M., Ouenniche, J., Tone, K
JournalExpert Systems with Applications
DOIhttps://doi.org/10.1016/j.eswa.2018.10.053
 
TitleMulti-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions (2018)
AuthorsMousavi M.;Ouenniche J.
JournalAnnals of Operations Research
PublisherSpringer
DOI10.1007/s10479-018-2814-2
 
TitlePerformance evaluation of bankruptcy prediction models: An orientation-free super-efficiency DEA-based framework (2015)
AuthorsMousavi M.;Ouenniche J.;Xu B.
JournalInternational Review of Financial Analysis
DOI10.1016/j.irfa.2015.01.006
 
TitleThe impact of Mena conflicts (the Arab spring) on global financial markets (2014)
AuthorsMousavi M.;Ouenniche J.
JournalJournal of Developing Areas
 
Book Chapters
TitleRANKING OF BANKRUPTCY PREDICTION MULTIPLE CRITERIA1 MODELS UNDER (2017)
AuthorsOUENNICHE, JAMAL, MOHAMMAD M. MOUSAVI, BING XU, and KAORU TONE
JournalAdvances in DEA Theory and Applications: With Extensions to Forecasting Models
PublisherWiley