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          <name>Title</name>
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              <text>Investment Decisions : Behavioral Biases in Selected Less Volatile Asset Classes   </text>
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              <text>Commerce</text>
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              <text>This study investigates the behavioral biases in selected less volatile asset classes and their influence on investment decisions(IDs). This study compares and contrasts demographic factors(DF) that influence behavioral biases(BB), examines the relationship between behavioral biases(BB) and risk-taking newlinebehaviors (RTB), determines whether BBs can be used to predict RTB and IDs, and looks at covariance patterns between factors that influence BBs, RTB, and IDs.A comprehensive analysis was conducted, considering various DF such as age, gender, education, annual income, marital status, total annual savings newlinepercentage, and the number of dependents in the family. The findings revealed no statistically significant interaction effects between these demographic variables and the combined dependent variables. Additionally, no significant main effects of age, gender, annual income, education, marital status, or paying tax were observed on the combined dependent variables. The study identified several correlations among the behavioral biases examined, including overconfidence(OC), representativeness(R), anchoring(A), herding(H), mental accounting(MA), and conservatism bias(CB). Positive correlations were found between OC and R, A and OC, A and R, H and OC, H newlineand R, MA and OC, MA and R, CB and OC, CB and R, CB and A, CB and H, CB and MA, risk-taking behaviors and overconfidence, risk-taking behaviors and representativeness, risk-taking behaviors and anchoring, risk-taking newlinebehaviors and herding, risk-taking behaviors and mental accounting, and risktaking behaviors and conservatism bias. Furthermore, herding and conservatism bias was significantly associated with risk-taking behaviors, while anchoring, herding, mental accounting, and conservatism bias were associated considerably with IDs. As part of the assessment techniques utilized in this study, seven characteristics or latent constructs were examined using various observable variables or scale items.</text>
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              <text>Aneesha, K Shaji</text>
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              <text>Christ(Deemed to be University)</text>
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              <text>2024-01-01</text>
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              <text>V.R, Uma</text>
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              <text>Open Access</text>
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              <text>&lt;a href="http://hdl.handle.net/10603/603349" target="_blank" rel="noreferrer noopener"&gt;http://hdl.handle.net/10603/603349&lt;/a&gt;</text>
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