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.
Alexander, Carol, Choi, Jaehyuk, Massie, Hamish R A and Sohn, Sungbin (2020) Price discovery and microstructure in ether spot and derivative markets. International Review of Financial Analysis. ISSN 1057-5219 (Accepted)
Alexander, Carol, Choi, Jaehjuk, Park, Heungji and Sohn, Sungbin (2020) BitMEX Bitcoin derivatives: price discovery, informational efficiency and hedging effectiveness. Journal of Futures Markets, 40 (1). pp. 23-43. ISSN 0270-7314
Alexander C. and M. Dakos (2020) ‘A Critical Investigation of Cryptocurrency Data and Analysis ’ Quantitative Finance. 20:2, 173-188, ISSN 1469-7688
Tzouvanas, Panagiotis, Kizys, Renatas and Tsend-Ayush, Bayasgalan (2019) Momentum trading in cryptocurrencies: short-term returns and diversification benefits. Economics Letters. ISSN 0165-1765