Complex networks theory during the last two decades has gained novel results and profound insights into many complex systems in engineering, social and biological and also financial fields. This proposed data-driven research programme will apply cross-disciplinary complex network and data science approaches to identify investor cliques in stock markets and to explain the impact of investor behaviour on asset price dynamics. My research extends current knowledge on investor networks by focusing on the identification of investor cliques to understand how different groups of investors (i.e. cliques) drive the market in certain direction.
This research helps to understand the mechanism between investor behaviour and transitions in stock markets, an important information to identify early warning signal and detect market manipulation. Also, it justifies regulators to get a better access for investor level transaction data, such unique data set we use in this project, to plan effective policies. Moreover, information diffusion in financial markets is a fundamental question, which will be addressed by this research, especially focusing on information transfer between and within investor cliques.
Principal Investigator: Dr. Le Viet Hung
Related PhD students: