Evolutionary Finance (EF) explores financial markets as evolving biological systems. Investors pursuing diverse investment strategies compete for the market capital. Some survive and some become extinct. A central goal of the study is to identify investment strategies guaranteeing survival. The problem is examined within a non-traditional game-theoretic framework combining stochastic dynamic games and evolutionary game theory. Models analysed in this area employ only objectively observable market data, in contrast to traditional neoclassical settings relying upon unobservable agents' characteristics: individual utilities and beliefs. The main results provide effective constructions of survival strategies. The thesis contributes to EF in three respects: (i) the most general EF model with long-lived dividend-paying assets is developed; (ii) a new model with endogenous asset dividends is proposed; (iii) a systematic study of the notion of an unbeatable strategy (a game solution concept playing a key role in EF) is conducted.
|Date of Award||31 Dec 2022|
- The University of Manchester
|Supervisor||Igor Evstigneev (Supervisor) & Goran Peskir (Supervisor)|
- Dynamic Games
- Evolutionary Behavioural Finance