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José Eduardo Medina Reyes

José Eduardo Medina Reyes

Email: j.e.medina-reyes@qmul.ac.uk

Project title

Thesis: Financial development and economic growth: A fuzzy modelling approach

Project Description

The objective of this research is to measure the impact of the stock market and banking on economic growth, considering the results of the United Kingdom, Germany, Mexico, and Peru. Specifically, the effect (positive or negative) of financial development on GDP will be determined through econometric models that capture the parameter and its transition dynamics between the countries' business cycle. From data analysed, it is possible estimate this effect through to the Stock Market Index (SMI), Loans Banking (LBA) and Savings Banking Aggregates (SBA). They can be estimated by maximum likelihood estimation and fuzzy Gaussian parameter estimation. As a short-term methodology, time series theory will be used, mainly the ARDL model and the Granger causality test. And fuzzy theory will be applied to capture other shades of the impact of financial development on economic growth by applying the Fuzzy-ARDL model. In conclusion, this research assesses the impact of financial development on economic growth. For all four economies examined there is statistical evidence that at least one aggregate of the financial system influences economic growth. It is noteworthy that for the UK, Peru, and Germany the stock market has an impact on economic growth, although this is not the case for Mexico. Furthermore, savings and credit indicators vary in their positive or negative effect depending on the type of financial institution. Where banks are the only financial institution present and statistically significant in the economies examined.

Supervision

  • 1st Supervisor: Prof. Sanghamitra Bandyopadhyay
  • 2nd Supervisor: Dr Michel Ferreira Cardia Haddad

Biography

José is a PhD candidate in Business and Management at Queen Mary University of London, focusing on financial development and economic growth via fuzzy modelling, he earned an MSc in Economics with honours from Instituto Politécnico Nacional (2019), specialising in Financial Economics, and a BSc in Economics with honours  from the same institution (2016). His education includes a CONACYT-funded research stay at Universidad Carlos III de Madrid (2018–2019) on statistical learning with big data.

With over eight years of experience in financial economics, data science, and risk consulting across Mexico, the UK, and Latin America (e.g., Colombia, Cuba, Bolivia), Medina Reyes co-founded Data Science Mexico as CEO, developing the AI platform CIDATMEX, which won the 2025 POSiBLE Award from Fundación Televisa for best agrobusiness and microfinance entrepreneurship. In 2025, he led a Bank of Mexico research project on digital financial inclusion, informing national strategy. As Data Science Consultant for German Sparkassenstiftung (2019–2022), he advanced business intelligence, market research for migrants and underserved communities, and risk planning for World Bank and Water.org projects. At Queen Mary, he serves as Teaching Assistant for Introduction to Economics and Research Assistant on economic development and COVID-19 data.

Key achievements include the 2020 IMEF-EY Financial Research Award (special mention, corporate finance), 2019 IMEF-EY Award (second place), 2020 Best Master's Thesis from Instituto Politécnico Nacional, and 2023 Best Presentation at CIEFAR. Leadership roles: Vice President, Society of Mexican Students UK (2024–2025); Treasurer, Queen Mary Mexican Society (2024–2025).

 

Centre and Group Membership

Centre for Globalisation Research (CGR)

 

Teach and Membership

Introduction to Economics

 

Area of Expertise

Finance and statistical models

Publications

Book Chapters: 

  • Castro Pérez J.J., Medina Reyes J.E., Cabrera Llanos A.I. (2021) Forecasting the Effects of the COVID-19 Crisis on Economic Growth and the Microfinance Sector in Latin America: An Approach with Fuzzy Neural Networks. In: Dávila-Aragón G., Rivas-Aceves S. (eds) The Future of Companies in the Face of a New Reality. Springer, Singapore. https://doi.org/10.1007/978-981-16-2613-5_5

 

  • Sistema de Control de Largo Plazo de la Política Monetaria en el Mercado Financiero Mexicano. Judith Jazmin Castro-Pérez, Agustín Ignacio Cabrera-Llanos y Salvador Cruz-Aké (2020). Miscelánea Científica en México, Tomo III, ISBN 978607-8358-89-2, Centro de Investigaciones en Óptica, Temacilli EDITORIAL. pp: 243-251.

Articles

  • Medina-Reyes, J. E., Castro-Pérez, J. J., & Cabrera-Llanos, A. I. (2020). Short-Term Causal Relationships between the Oil Sector and Economic Growth in the Mexican Economy: FG-ARDL Approach. Revista Mexicana de Economía y Finanzas Nueva Época REMEF, 15(4), 685-708. DOI: https://doi.org/10.21919/remef.v15i4.497
  • Medina-Reyes, J. E., Castro-Pérez, J. J., Cabrera-Llanos, A. I., & Cruz-Aké, S. C. (2020). Red neuronal autorregresiva difusa tipo Sugeno con funciones de membresía triangular y trapezoidal: una aplicación al pronóstico de índices del mercado bursátil. Estocástica: FINANZAS Y RIESGO, 10(1), 77-101. Url: http://estocastica.azc.uam.mx/index.php/re/article/view/130
  • Medina-Reyes, J. E., Cruz-Aké, S., & Cabrera-Llanos, A. I. (2021). A Hybrid Fuzzy Time Series and Fuzzy ARIMA Model for Forecasting the Foreign Exchange Market. Contaduría          y Administración, 66(3). DOI: https://doi.org/10.22201/fca.24488410e.2021.2623  
  • Castro-Pérez, J. J., & Medina-Reyes, J. E. (2021). Fuzzy Portfolio Selection with Sugeno Type Fuzzy Neural Network: Investing in the Mexican Stock Market. Revista Mexicana de Economía y Finanzas Nueva Época REMEF, 16, 583. DOI: https://doi.org/10.21919/remef.v16i0.583   
  • Reyes, J. E. M., Llanos, A. I. C., & Aké, S. C. (2023). Fuzzy Gaussian GARCH and Fuzzy Gaussian EGARCH Models: Foreign Exchange Market Forecast. Revista Mexicana de Economía y Finanzas Nueva Época REMEF, 18(3), 855. DOI: https://doi.org/10.21919/remef.v18i3.855
  • Medina-Reyes, J. E., Castro-Pérez, J. J. C., & Cruz-Aké, S. C. (2024). Credit risk management analysis: An application of fuzzy theory to forecast the probability of default in a financial institution. Contaduría y Administración, 69(1), 430. DOI: http://dx.doi.org/10.22201/fca.24488410e.2024.5014

Media

 

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