The Relationship between Relative Risk Aversion and Survivability
As a follow-up to the work of  and , this paper continues to explore the relationship between wealth share dynamics and risk preferences in the context of an agent-based multi-asset artificial stock market. We simulate a multiasset agent-based artificial stock market composed of heterogeneous agents with different degrees of relative risk aversion (RRA). A wide range of RRA coefficients has been found in the literature, and so far no unanimous conclusion has been reached. The agent-based computational approach as demonstrated in this paper proposes the possibility that in reality there may be such a wide survival range of the RRA coefficient. In addition, the time series plot of the wealth share dynamics indicates that the higher the risk aversion coefficient, the higher the wealth share. This result combined with our earlier result () well articulates the contribution of risk aversion to survivability.
KeywordRisk Preferences CRRA (Constant Relative Risk Aversion) Blume-Easley Theorem Agent-Based Artificial Stock Markets Genetic Algorithms
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