Between 2015 and 2018, investment in the UK high-growth Fintech firms was £4.5 billion. Fintech is one of the UK’s strongest tech sub-sectors, ranked as No. 1 in the world. (TECH NATION REPORT 2019). The University of Sussex has a pool of experts who have been working in the areas, directly and indirectly, underpinning the theory, framework and development of Fintech.
Currently, most of our FinTech research is on (i) markets for crypto assets and their derivatives and (ii) the evolution of shadow banking, with particular emphasis on peer-to-peer lending.
In crypto asset spot markets we examine data used for reference rates, which is particularly relevant for hedge funds and exchange-traded funds requiring indicative crypto asset values and a sentiment index which we call the ‘greed index’ for crypto markets using machine learning techniques applied to Reuters news and to other sources like Google and Facebook; in derivatives markets we examine crypto market microstructure using very high frequency data. We also have a unique data set on crypto options markets and the variance risk premium, providing time series on the VIX equivalent, “the crypto investor’s fear gauge” at the 15-minute frequency. This helps financial institutions monitor the development of crypto asset markets as they become more established.
We also have projects on determinants of crowdfunding success using criteria required by P2P platforms and entrepreneurs’ information as well as data from ICO bench for funding based on tokenisation. Further, we examine links between various aspect of financial and technical literacy and consumer decisions regarding P2P products.
- Crypto asset and derivatives markets
- P2P lending
- Blockchain protocols
Alexander, C., Deng, J. and Zou, B. (2022) Hedging with automatic liquidation and leverage selection on bitcoin futures. European Journal of Operational Research, 306(1), 478-493.
Alexander, C., Deng, J., Feng, J. and Wan, H. (2022) Net buying pressure and the information in bitcoin option trades. Journal of Financial Markets. a100764. ISSN 1386-4181
Alexander, C., Heck, D. and A. Kaeck (2022) The role of binance in bitcoin volatility transmission. Applied Mathematical Finance, 29(1), 1-32.
Alexander, C. and M. Dakos (2022). Assessing the accuracy of exponentially weighted moving average models for Value-at-Risk and Expected Shortfall of crypto portfolios. Quantitative Finance. ISSN 1469-7688
Alexander, C., and Imeraj A. The Bitcoin VIX and Its Variance Risk Premium. The Journal of Alternative Investments 23.4 (2021): 84-109.
Christian, J., and Vu, A. N. Task‐based structures in open source software: revisiting the onion model. R&D Management 51.1 (2021): 87-100.
Alexander, C., Choi, J., Massie, H. R., and Sohn, S. Price discovery and microstructure in ether spot and derivative markets. International Review of Financial Analysis, 71 (2020): 101506.
Alexander, C, and Heck, D. Price discovery in Bitcoin: The impact of unregulated markets. Journal of Financial Stability 50 (2020): 100776.
Alexander, C., Choi, J., Park, H. and Sohn, S. BitMEX Bitcoin derivatives: price discovery, informational efficiency and hedging effectiveness. Journal of Futures Markets, 40.1 (2020): 23-43.
Alexander, C. and Dakos, M. ‘A Critical Investigation of Cryptocurrency Data and Analysis ’ Quantitative Finance. 20:2 (2020): 173-188.
Tzouvanas, P., Kizys, R. and Tsend-Ayush, B. Momentum trading in cryptocurrencies: short-term returns and diversification benefits. Economics Letters, 191, (2020): 108728.