The Development of the Risky Financial Behavior Scale: A Measure of Financial Risk Tolerance

<p>There is an increasing need for a more comprehensive instrument to measure risk tolerance in human financial decision making studies. The traditional economic method and the more recent psychometric method of examining risk tolerance were both reviewed in the study. The purpose of this thesis was the initial development and validation of the Risky Financial Behavior Scale (RFBS), with items taken from four different domains noted in previous studies. Phase I and II consisted of item pool generation, construct determination from content experts' review and cognitive interviews. Data from these stages were collected and used for item revision prior to final data collection. Phase III consisted of quantitative evaluation of the field administration data using factor analysis, item analysis, Rasch analysis, and final revision based on item meanings and factor loadings. Phase IV tested convergent validity and relationships with demographic variables. A final version of the 20-item survey showed low but acceptable internal consistency reliability for each of the subscales, and moderate convergent validity was found between RFBS scale and a commonly used risk tolerance measure, the GL-RTS. Reasons for lower than expected reliability and validity are discussed. Suggestions for improvement, implications for use, and future research are also discussed.</p>

Name thesis:degree_name

M.A.

Level thesis:degree_level

Masters Thesis

Year dc:date.available

2013

Author dc:creator

• Zheng, Yilong

Contributors dc:contributor

• Pablo Antonio Olmos-Gallo, Ph.D.
• Kathy Green, Ph.D.
• Donald Bacon

• Risky financial behavior scale
• Human financial decision making
• Research methods
• Decision making
• Economics
• Finance

Statement dc:rights

• <p>Copyright is held by the author. User is responsible for all copyright compliance.</p>

Language dc:language

en

Repository record dc:identifier

https://digitalcommons.du.edu/etd/734

OAI identifier oai:identifier

oai:digitalcommons.du.edu:etd-1733