Cardiff Fintech Research Group
We aim to become an internationally leading institute that promotes interdisciplinary and innovative Fintech research.
Financial technology (Fintech) combines innovative business models and computer technology to improve financial service. Since its emergence, it brings a wave of creative destruction that substantially changes the landscape of finance and have significant implications for the economy.
For example, the sudden rise of cryptocurrencies (eg Bitcoin), which compete with the fiat currencies and disrupt the existing payment system, poses great challenges to central banks and commercial banks.
- Raise Cardiff Business School’s reputation as a national and international centre for Fintech research.
- Facilitate cross-disciplinary Fintech research among members of the research group and across sections and schools.
- Engage in innovative and industrially relevant research and provide our expertise to public and private sectors in Wales and beyond.
Our members’ research interests in Fintech include:
- Banking (eg digital banking, open banking)
- Insurance (insuretech)
- Personal Finance (eg robo-advisors)
- Payments (digital payment systems)
- Lending (crowdfunding, P2P lending etc.)
- Capital Markets (algorithmic and high frequency trading)
- Wealth Management
- Machine Learning and AI
- Computer-assisted Textual Analysis
- Wang, Y. 2021. Blockchain applications in logistics. In: Vickerman, R. , Noland, R. B. and Ettema, D. eds. International Encyclopedia of Transportation. Elsevier
- Fang, Y. et al. 2020. Optimal forecast combination based on ensemble empirical mode decomposition for agricultural commodity futures prices. Journal of Forecasting 39 (6), pp.877-886. Volume39, Issue6 September 2020 Pages 877-886. (10.1002/for.2665)
- Fang, Y. et al., 2019. Foreign ownership, bank information environments, and the international mobility of corporate governance. Journal of International Business Studies 50 (9), pp.1566-1593. (10.1057/s41267-019-00240-w)
- Aretz, K. , Banerjee, S. and Pryshchepa, O. 2019. In the path of the storm: does distress risk cause industrial firms to risk-shift?. Review of Finance 23 (6), pp.1115-1154. (10.1093/rof/rfy028)
- Wang, Y. et al. 2019. Making sense of blockchain technology: How will it transform supply chains?. International Journal of Production Economics 211 , pp.221-236. (10.1016/j.ijpe.2019.02.002)
- Hewett, N. , Lehmacher, W. and Wang, Y. 2019. Inclusive deployment of blockchain for supply chains.
- Silva, E. S. et al., 2019. Forecasting tourism demand with denoised neural networks. Annals of Tourism Research 74 , pp.134-154. (10.1016/j.annals.2018.11.006)
- Wang, Y. , Han, J. H. and Beynon-Davies, P. 2019. Understanding blockchain technology for future supply chains: a systematic literature review and research agenda. Supply Chain Management: An International Journal 24 (1), pp.62-84. (10.1108/SCM-03-2018-0148)
- Wang, Y. , Touboulic, A. and O'Neill, M. 2018. An exploration of solutions for improving access to affordable fresh food with disadvantaged Welsh communities. European Journal of Operational Research 268 (3), pp.1021-1039. (10.1016/j.ejor.2017.11.065)
- Nguyen, D. . D. , Hagendorff, J. and Eshraghi, A. 2018. Does a CEO's cultural heritage affect performance under competitive pressure?. Review of Financial Studies 31 (1), pp.97-141. (10.1093/rfs/hhx046)
- Song, Q. , Liu, A. and Yang, S. 2017. Stock portfolio selection using learning-to-rank algorithms with news sentiment. Neurocomputing 264 , pp.20-28. (10.1016/j.neucom.2017.02.097)
- Yang, S. Y. et al., 2017. Genetic programming optimization for a sentiment feedback strength based trading strategy. Neurocomputing 264 , pp.29-41. (10.1016/j.neucom.2016.10.103)
- Taffler, R. J. , Spence, C. and Eshraghi, A. 2017. Emotional economic man: Calculation and anxiety in fund management. Accounting, Organizations and Society 61 , pp.53-67. (10.1016/j.aos.2017.07.003)
- Rogers, A. et al. 2017. Examining the existence of double jeopardy and negative double jeopardy within Twitter. European Journal of Marketing 51 (7/8), pp.1224-1247. (10.1108/EJM-03-2015-0126)
- ap Gwilym, O. et al., 2016. In search of concepts: the effects of speculative demand on stock returns. European Financial Management 22 (3), pp.427-449. (10.1111/eufm.12067)
- Nguyen, D. , Hagendorff, J. and Eshraghi, A. 2016. Can bank boards prevent misconduct?. Review of Finance 20 (1), pp.1-36. (10.1093/rof/rfv011)
- Yang, S. Y. , Mo, S. Y. K. and Liu, A. 2015. Twitter financial community sentiment and its predictive relationship to stock market movement. Quantitative Finance 15 (10), pp.1637-1656. (10.1080/14697688.2015.1071078)
- Kuang, P. , Schröder, M. and Wang, Q. 2014. Illusory profitability of technical analysis in emerging foreign exchange markets. International Journal of Forecasting 30 (2), pp.192-205. (10.1016/j.ijforecast.2013.07.015)
- Pryshchepa, O. , Aretz, K. and Banerjee, S. 2013. Can investors restrict managerial behavior in distressed firms?. Journal of Corporate Finance 23 , pp.222-239. (10.1016/j.jcorpfin.2013.08.006)
Professor of Finance and Investment
- +44 (0)29 2251 0880
Professor of Quantitative Analysis
- +44 (0)29 2087 5727