Yaş ve bireylerin risk alma davranışlarına yeni bir yaklaşım

In this thesis, we use evolutionary game theory techniques to analyze the relation between risk taking behavior of agents and their ages. We suppose that risk aversion is the stable pattern for the old agents and risk seeking is the stable pattern for the young agents as it is commonly assumed so in economics literature. First, we solve a benchmark model without heterogeneity in terms of age differentiations. In such a case, we observe that mutation either increases or decreases with respect to the payoff levels, depending on the initial fitness levels of the population groups. In the second step, we introduce heterogeneous population frontier. The anticipated level of the initial mutant proportion provides incentives to trigger the evolution. Then, we analyze numerically the effects of the initial level of fitness, initial risk averse and risk seeking proportions on the pattern of the evolution process. Finally, we studied the inter-temporal effects of different risk averse and risk seeking population proportions on mutation.