Integrating behavioral finance and agent-based modeling (ABM)

Reflection Paper Your Name Subject and Section Professor’s Name September 26, 2024 Reflection on Integrating Behavioral Finance and Agent-Based Modeling (ABM) Both behavioral finance and agent-based modeling (ABM) provide valuable resources for understanding complex and uncertain economic systems in current economic analysis. This review examines the different ways these ideas appear in the readings and their potential for use in economic analysis, notably regarding financial systems. This reflection will analyze the foundational principles of each approach while analyzing their supportive nature for understanding actual world phenomena, such as financial instability and market behavior. Behavioral Finance: Rethinking Rationality Based on the readings I read, it is clear that behavioral finance operates from the idea that human activity is inconsistent with the standard rational actor model usually applied by neoclassical economics. In their extract, some of the things that resonated with me were Delli Gatti and Gallegati's arguments that behavioral finance contradicts the assumption of wholly rational agents who can make decisions to raise their utility reliably. According to the authors, problems with traditional DSGE models lead to their inability to integrate financial distress, excessive debt, and systematic risk. This omission reflects a broader critique of neoclassical models: they deliver an overly explicit illustration of the diverse complexities found in functional economies. The third segment addresses how behavioral finance combines psychological, sociological, and cognitive neuroscience to clarify economic behaviors. In decision settings, it points out the common mistakes people keep making. Combining psychological and emotional learning with economic models dramatically increases their effectiveness in addressing decision-making factors, such as impulsivity, overconfidence, and loss aversion. Drawn from an understanding of these human characteristics, behavioral finance presents a wiser interpretation of problems, such as market bubbles and crashes, together with sustainable solutions, creating a model to help us understand why people frequently behave irrationally in the face of explicit financial incentives. In opposition to standard neoclassical economic models, behavioral finance suggests that people typically employ heuristics, or essential memories, and are influenced by biases in their judgment processes. Such insights are particularly notable as one investigates financial crises, including the Global Financial Crisis 2008, where herd behavior and exaggerated optimism contributed to increased risk. According to Thaler (2017) and behavioral economists of the past, we have to consider human traits in our economic models to predict better and manage financial instability. Agent-Based Modeling: Simulating C...