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Finance (Informatics)

Financial markets are increasingly being underpinned by information technology to the extent that financial markets can be seen as instances of distributed systems technology, and in turn economic and financial incentives are increasingly understood to play an important role in conventional distributed systems technology such as the internet protocols. The Finance Hub conducts fundamental and applied research at the intersection of finance and computation, a sector which is colloquially known as FinTech. We apply techniques such as network analysis, scientific and high-performance computing, time-series analysis, big-data analytics and agent-based modelling to problems in market micro-structure, risk management, portfolio construction, and the design of crypto-finance and distributed-ledger protocols. The Hub has established collaborations with other departments at King's, such as the Maths department and the King's Business School, and also key financial institutions, including the Financial Conduct Authority.


Research Questions

The financial markets present a unique opportunity for studying complex-adaptive systems with the availability of high-frequency tick-data, and entries in the block-chain, which record every transaction in the financial markets, and can run to many billions of events per exchange per annum. We are developing methods for using these big data sets to systematically calibrate models in order to try and better understand the role of learning and adaptation in financial markets. The key research questions we address are: firstly, whether behavioural and evolutionary models provide a better fit to the data than models based on the efficient markets hypothesis; secondly, whether these systems can maintain homeostatic behaviour, despite the fact that there is often an incentive for individual agents to disrupt the system for their own gain; and finally, how protocols underpinning distributed financial systems such as the block-chain can be designed to mitigate these risks.