Nonlinear Dynamic Positive Feedback Trading and the Complexity of Stock Price

Abstract

This thesis has applied the theory from behavioural finance theory
and by merging with the concept of chaos theory from natural science, this thesis focuses on the impact of positive feedback trading on the price formation process. By using the Hurst exponent estimation and calculating the correlation dimension value, the market index and individual firms from China have presented the nonlinearity and chaotic characteristics, thus demonstrating the source of complexity.

This thesis proposes a new model that uses the Hurst exponent
as the signal for thresholds to indicate changes in market conditions. The result suggested, by combining the threshold and assumptions from the positive feedback model, that the new model offers a better explanation for the complexity of the stock market which presents chaos. The model is found to be statistically significant and superiorin all comparative testing.

Date of Award	2020
Original language	English
Awarding Institution	Coventry University
Supervisor	Karl Shutes (Supervisor)