Dynamical Systems Approach to Distributed Finance: challenges and new perspectives
Lead Research Organisation:
University of Sussex
Department Name: Sch of Mathematical & Physical Sciences
Abstract
The main focus of the project is the application of mathematical modelling and techniques of nonlinear dynamics and time-delayed systems to the analysis of complex networks of a wide range of financial interactions, such as P2P lending, information sharing through targeted advertising, reward schemes and so forth. This will allow us to gain new insights into the intricacies of human behaviour, such as the spread of information to groups of followers on Twitter, Facebook and similar at a local level, in combination with global awareness and its influences on the overall market behaviour. Furthermore, it will deliver specific methodologies for optimising the performance of P2P lending networks and advertising strategies. Some specific areas to be covered by the project include, but are not limited to
- Self-organisation of agents --- why 'contagion' spreads in some cases and not in others
- Synchronisation and control in emerging currency markets: from Bristol Pound (local) to Bitcoin (global) to general crypto-currency uptake and usage
- delayed effects in advertising: understanding optimal targeting of resources through goodwill (average past advertising expenditure) and forgetting time
- Self-organisation of agents --- why 'contagion' spreads in some cases and not in others
- Synchronisation and control in emerging currency markets: from Bristol Pound (local) to Bitcoin (global) to general crypto-currency uptake and usage
- delayed effects in advertising: understanding optimal targeting of resources through goodwill (average past advertising expenditure) and forgetting time
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/N509784/1 | 01/10/2016 | 30/09/2021 | |||
| 1811415 | Studentship | EP/N509784/1 | 01/10/2016 | 31/08/2020 | Aleksandra Ross |
| Description | Various cryptocurrencies have emerged as possible competitors to fiat currencies, with the underlying blockchain technology spreading and gaining recognition. We analysed and estimated the proliferation of such cryptocurrencies. SIR type model was adapted to describe the take-up and abandonment of the blockchain-based technology by the general population. Publicly available Google Trends data was used for model validation and prediction testing, reflecting the interest generated by the cryptocurrencies discussed. We used the least-squares method to find the best fit for parameters, such as the take-up rates reflecting the interest in cryptocurrencies and blockchain technology amongst the population, and well as the subsequent loss of interest. The adapted model yields results that are comparable with the observed Google Trends patterns of the reviewed cryptocurrencies, this is a good first-hand indication that the model is useful for data validations and predictions, further model improvement would allow greater understanding of the mathematics underlying the dynamics of cryptocurrencies and blockchain technology. |
| Exploitation Route | Further analysis of real-life data, as well as model improvement taking into account extra variables and delay parameters. |
| Sectors | Creative Economy,Financial Services, and Management Consultancy |