Exploring the Behavioral Portfolio Theory (BPT) in Investment Strategies: A Review of Investor Preferences

Abstract

Abstract: The objective of this review is to explore the role of Behavioral Portfolio Theory (BPT) in shaping investment strategies by focusing on investor preferences and behaviors. This article uses a scientific narrative review approach, incorporating a descriptive analysis of the literature on BPT and its applications. The materials examined include theoretical models, empirical studies, and case studies related to BPT, behavioral finance, and investment strategies. The review synthesizes insights from various sources to provide a comprehensive understanding of how BPT influences portfolio construction, asset allocation, and the management of behavioral biases. Key findings indicate that BPT offers a more realistic framework for portfolio management by recognizing that investors are not always rational and often make decisions influenced by cognitive biases such as loss aversion, overconfidence, and mental accounting. BPT allows for the segmentation of portfolios into layers that reflect different financial goals, such as wealth protection and aspiration for growth, making it more adaptable to individual investor preferences. Additionally, the integration of BPT with modern technological advancements, such as artificial intelligence and fintech, is enhancing its practical application in portfolio management by automating the process of adjusting investment layers according to market conditions and investor behavior. The review also highlights the challenges associated with implementing BPT, particularly its complexity and the persistence of behavioral biases that can still affect decision-making. However, compared to traditional models like Modern Portfolio Theory, BPT offers a more personalized and psychologically attuned approach to investment strategies. In conclusion, BPT provides a valuable framework for understanding and managing the complexities of investor behavior in financial markets, with potential for further evolution as research and technology continue to advance.