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Abstract
Purpose: The aim of the study was to analyze the modeling longevity risk in pension funds using population dynamics in Canada. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Modeling longevity risk in Canadian pension funds using population dynamics reveals improved accuracy in assessing risk exposure and forecasting life expectancy impacts on liabilities. It underscores the importance of demographic trends like increasing life expectancy and aging populations, and the need to consider regional mortality variations for refining models. Proactive risk management strategies based on these insights are crucial for mitigating financial uncertainties in pension fund management. Unique Contribution to Theory, Practice and Policy: Mortality modeling and population dynamics theory, financial economics and longevity risk theory & stochastic modeling and Monte carlo simulation theory may be used to anchor future studies on analyze the modeling longevity risk in pension funds using population dynamics in Canada. Implementing population dynamics in longevity risk modeling allows pension funds to develop more precise risk management strategies. Policymakers can leverage population dynamics models to inform retirement policy decisions.
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