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Investigating the impact of behavioral biases and financial literacy on investment decisions using the structural equation model: a case study of Kerman households

Year: 2024
Type: article
Abstract: The purpose of this study is to investigate the impact of behavioral biases and financial literacy on the investment decisions of households in the city of Kerman. To achieve this goal, after reviewing the relevant literature, the effects of behavioral biases such as heuristic biases (including anchoring, representativeness, and overconfidence), framing biases (including mental accounting, the disposition effect, and regret avoidance), cognitive biases (including conservatism, confirmation, and hindsight), and herding behavior (including information processing, the bandwagon effect, and social group influence), as well as the impact of financial literacy on investors' decisions, were examined. The statistical population of the study consists of residents of Kerman who have experience in investing in financial markets. The required data were collected using a two-stage random sampling method from 388 residents of different areas of Kerman. Statistical techniques and structural equation modeling, utilizing software such as LISREL, SPSS 26, and Smart PLS3, were employed to analyze the data and test the hypotheses. The study's findings indicate that heuristic biases, framing biases, cognitive illusions, and herding behavior have a significant negative impact on investors' decisions. In contrast, financial literacy has a significant positive impact on investors' decisions. Investors are advised to acquire the necessary knowledge about financial markets before investing and to avoid making transactions based on herd behavior. It is also recommended that financial market policymakers while reforming the market's structural system to enhance its efficiency and information transparency, plan necessary measures to raise the level of financial literacy among the general public.
Authors: Mohammadali Maghsoudpour, Behnam Karamshahi
Language: English
Subfield: Accounting
Open Access status: green
OpenAlex ID: W6926211444
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