This paper presents a stochastic model for simulating the dynamic evolution of individual well-being, or happiness. Happiness is conceptualized as an emergent property of an interconnected system of key life domains, including income, mental health, physical health, stress, coping strategies, relationships, and voluntary actions. Each domain is modeled as a stochastic differential equation (SDE), capturing inherent randomness, mean-reversion, and specific influences such as expectation gaps and inter-domain feedback. We develop a composite SDE for overall happiness, driven by the states and changes in these underlying domains. The model incorporates fractional Brownian motion for smooth, persistent randomness and jump processes for significant life events. We discuss the formulation of these SDEs, focusing on clarity and psychological plausibility. Finally, we present simulated happiness trajectories under illustrative scenarios, demonstrating the model’s capacity to generate rich, dynamic patterns of well-being and highlight the complex interplay between various life factors and individual happiness over time.
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