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Reconciling Self-Assessed with Psychometric Risk Tolerance: A New Framework for Profiling Risk among Investors.

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Title: Reconciling Self-Assessed with Psychometric Risk Tolerance: A New Framework for Profiling Risk among Investors.
Authors: Mazzoli, Camilla (AUTHOR), Palmucci, Fabrizio (AUTHOR)
Source: Journal of Behavioral Finance. Apr-Jun2025, Vol. 26 Issue 2, p201-214. 14p.
Subjects: Investors, Financial risk, Financial planners, Portfolio management (Investments), Investment risk, Individual investors, Investment advisors
Abstract: Financial advisors need to assess their clients' risk profile to properly manage their portfolio risk and comply with regulatory provisions. Assessing an investor's financial risk tolerance (FRT) is a challenge in the advisory process and none of the existing measures can be easily employed on a large scale. Previous literature has revealed a gap between self-assessed and psychometrically assessed measures of FRT (PA_FRT) but has not yet offered a solution to fill this gap. Thus, we propose a model that consistently estimates the PA_FRT by leveraging retail investors' self-assessment and other information typically submitted in standard bank questionnaires. Our model represents a promising tool for financial advisors looking to improve their customers' risk profiling. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Behavioral Finance is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Reconciling Self-Assessed with Psychometric Risk Tolerance: A New Framework for Profiling Risk among Investors.
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  Data: <searchLink fieldCode="AR" term="%22Mazzoli%2C+Camilla%22">Mazzoli, Camilla</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Palmucci%2C+Fabrizio%22">Palmucci, Fabrizio</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Behavioral+Finance%22">Journal of Behavioral Finance</searchLink>. Apr-Jun2025, Vol. 26 Issue 2, p201-214. 14p.
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  Data: <searchLink fieldCode="DE" term="%22Investors%22">Investors</searchLink><br /><searchLink fieldCode="DE" term="%22Financial+risk%22">Financial risk</searchLink><br /><searchLink fieldCode="DE" term="%22Financial+planners%22">Financial planners</searchLink><br /><searchLink fieldCode="DE" term="%22Portfolio+management+%28Investments%29%22">Portfolio management (Investments)</searchLink><br /><searchLink fieldCode="DE" term="%22Investment+risk%22">Investment risk</searchLink><br /><searchLink fieldCode="DE" term="%22Individual+investors%22">Individual investors</searchLink><br /><searchLink fieldCode="DE" term="%22Investment+advisors%22">Investment advisors</searchLink>
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  Data: Financial advisors need to assess their clients' risk profile to properly manage their portfolio risk and comply with regulatory provisions. Assessing an investor's financial risk tolerance (FRT) is a challenge in the advisory process and none of the existing measures can be easily employed on a large scale. Previous literature has revealed a gap between self-assessed and psychometrically assessed measures of FRT (PA_FRT) but has not yet offered a solution to fill this gap. Thus, we propose a model that consistently estimates the PA_FRT by leveraging retail investors' self-assessment and other information typically submitted in standard bank questionnaires. Our model represents a promising tool for financial advisors looking to improve their customers' risk profiling. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Behavioral Finance is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=185286508
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      – Type: doi
        Value: 10.1080/15427560.2023.2271108
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      – Code: eng
        Text: English
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        PageCount: 14
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      – SubjectFull: Investors
        Type: general
      – SubjectFull: Financial risk
        Type: general
      – SubjectFull: Financial planners
        Type: general
      – SubjectFull: Portfolio management (Investments)
        Type: general
      – SubjectFull: Investment risk
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      – SubjectFull: Individual investors
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      – SubjectFull: Investment advisors
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      – TitleFull: Reconciling Self-Assessed with Psychometric Risk Tolerance: A New Framework for Profiling Risk among Investors.
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              Text: Apr-Jun2025
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              Y: 2025
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