This thesis employs a behavioural finance and emotional finance approach to analyzing the effect of investor biases and emotions on trading behaviour and performance. Furthermore, it incorporates a network approach to consideration of herding and emotional contagion across financial markets. The research is undertaken to advance both academic understanding and, in the spirit of the Engineering Doctorate (EngD), practical investment product development for the sponsoring organization (CheckRisk, see https://check-risk.com). This thesis reviews the relevant literature in behavioural finance, emotional finance and neuro-finance, and delves into the nature of networks, and of risk, risk-management and decision-making under various states of emotion and uncertainty. Building upon this literature review, our main experimental contributions to the field concern the development of a market risk-profiling system, based around behavioural questionnaires and a novel neuro-finance trading game. We tested our trading game on students, which provided a ‘proof of concept’ for the product. Next, we discuss how CheckRisk could market this risk-profiling product towards real-world traders and independent financial advisers (IFAs). Our research initially focuses on biases and emotions of individual traders, and then moves on from the ‘micro’ (individual traders) to the wider ‘macro’ (market-wide effects of emotional contagion across investors) areas of interest, particularly herding behaviours in financial markets. To explore these cascading phenomena, we employed network analysis and agent-based modelling. We suggest that this approach provides a basis for future academic and practitioner research, combining biases at the individual level (from the market risk-profiling system) with market-wide emotional contagion.
|Date of Award||13 Feb 2019|
|Supervisor||Andreas Krause (Supervisor) & Richard Fairchild (Supervisor)|