Behavioral Finance Theory

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Behavioral Finance theory has been emerged based on the limitations of traditional finance theory I-e investors behave rationally (Statman, 1995). Barberis & Thaler (2003) noted that behavioral finance theory explains irrationality and decision making process by drawing evidence from the cognitive psychology and biases associated by, the way people make believes and preferences. Behavioral biases have been considered as a main driving force in investment portfolio choice. People are subject to behavioral biases when they make decision making. These biases prevent people from making rational and normal decisions. Many researchers in the field of behavioral finance conducted research and suggest that investors do not always behave rationally when making investment decisions (Babajide & Adetiloye, 2012). Many behavioral Finance models motivate irrational investment behavior using overconfident investors. Overconfidence refers to the habit of overestimating own ability to perform in given tasks. Barner & Odean (2000) submits that overconfidence causes excess trading which can be risky to financial well-being. Some of the key biases that affect financial decisions include investing with overconfidence, which can lead to inappropriate or risky investments. Loss aversion is, investing to avoid loss or regret, at all costs, which can mean we don’t invest in way that will truly help us reach our investment objectives. Loss aversion is also acknowledged as risk aversion. Investing with self-attribution bias refers to a tendency to overestimate the degree which leads to risky investments. Ofir and Wiener (2008) study show the result that even professional investors are not really protected to behavioral biases and there are certain personal... ... middle of paper ... ...that which type of decision they will take and through their responses to the questions study judged the behavioral biases prevalent among their decision. Data analysis technique After data collection, questionnaires will be coded and checked for coding errors and omissions and coded data will process in the SPSS software Package. Statistical techniques, which are used for the data to achieve the research objectives, include Descriptive Statistics, Correlation coefficient. Descriptive Statistics (mode, median, mean, variance, standard deviation) are used to describe respondents’ personal information. Correlation coefficient was used to find out the relationship between over confidence bias, self-attribution and loss aversion bias and investment. Using linear regression, independent variables that demonstrated to explain better the affects over the dependent ones.

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