Behavioral Financial Approach to Working Capital Management

An analytical Study For a Sample of Decision Makers in Iraqi Companies Listed In Iraq Stock Exchange

A Thesis Submitted to The Board of The College of Management and Economics, As a Part of the Requirements For Obtaining a Master’s     Degree in Finance and Banking Sciences

Presented By

Maryim Ameer

Supervised By

Asst. Prof. Dr. Noor S. Al-Dahan

Abstract

This study aims to understand and clarify the behavior of decision makers in companies who participate in the financial and administrative decision-making process for managing working capital and its components. The self-attribution, mental accounting, and emotional biases associated with probability theory, such as loss avoidance, self-control, and the status quo, and how these biases may influence working capital management decisions. The data were collected by means of a questionnaire consisting of (37) questions asked to (103) of the managers who were selected from (22) companies listed in the Iraqi Stock Exchange, depending on the descriptive and inferential method of the sample and hypotheses of the study by using two statistical tools represented by the correlation matrix ( Pearson’s correlation coefficients) for the purpose of verifying the strength of the existing correlation relationships between the dimensions of the study variables and simple regression analysis to test the effect relationships between the dimensions of the main study variables.

The results show that behavioral finance is a complementary theory to traditional finance with the aim of better understanding the behavior of individuals to explain anomalies when making financial decisions. They should not rely completely on the psychological and emotional motives for them in the decision-making process, and this does not cancel the important role of behavioral finance, but rather they must work according to a double work system and not rely on one without the other.

Keywords: Behavioral Finance, Cognitive biases, Emotional biases, Working Capital Management