Nonlinear linkages between financial risk tolerance and demographic characteristics

2009 ◽  
Vol 16 (13) ◽  
pp. 1329-1332 ◽  
Author(s):  
Robert Faff ◽  
Terrence Hallahan ◽  
Michael McKenzie
Keyword(s):  
Financial Risk ◽  
Demographic Characteristics ◽  
Risk Tolerance ◽  
Financial Risk Tolerance

scholarly journals Financial Literacy and Financial Risk Tolerance of Individual Investors: Multinomial Logistic Regression Approach

SAGE Open ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 215824402094571
Author(s):  
Yılmaz Bayar ◽  
H. Funda Sezgin ◽  
Ömer Faruk Öztürk ◽  
Mahmut Ünsal Şaşmaz
Keyword(s):  
Logistic Regression ◽  
Financial Literacy ◽  
Financial Risk ◽  
Multinomial Logistic Regression ◽  
Demographic Characteristics ◽  
Risk Tolerance ◽  
Financial Investment ◽  
Multinomial Logistic Regression Analysis ◽  
The Impact ◽  
Financial Risk Tolerance

Financial risk tolerance is one of the important factors affecting the financial investment decisions of individuals and institutional investors and a crucial factor of financial planning and financial counseling. It is therefore necessary to determine the major determinants of risk tolerance. In this article, we researched the impact of financial literacy level and demographic characteristics on the financial risk tolerance of the individuals in the sample of Usak University staff, using a multinomial logistic regression analysis and retrieving data through the questionnaire method. Multinomial logistic regression is an extension of binary logistic regression, allowing for three or more categories of the dependent variable. The findings of the empirical analysis reveal that financial literacy and demographic characteristics of age, gender, education, and income levels are significant determinants of financial risk tolerance. In this regard, the improvements in the financial literacy of the individuals through various education programs will probably raise the demand of financial products with different risk characteristics and in turn contribute to the development of financial sector.

Demographic Variables, Delay Discounting Models and Dysfunctional Personality Traits as Predictors of Financial Risk-Tolerance Among Community-Dwelling Italian Adults

2021 ◽  
pp. 026010792110321
Author(s):  
Antonella Somma ◽  
Rebecca Sergi ◽  
Chiara Pagliara ◽  
Clelia Di Serio ◽  
Andrea Fossati
Keyword(s):  
Personality Traits ◽  
Linear Combination ◽  
Delay Discounting ◽  
Financial Risk ◽  
Short Form ◽  
Demographic Variables ◽  
Risk Tolerance ◽  
Community Dwelling ◽  
Self Report ◽  
Financial Risk Tolerance

To evaluate the effect of demographic variables, delay discounting and dysfunctional personality traits on financial risk tolerance (FRT), 281 community-dwelling adults were administered the Italian translations of the Risk-Tolerance Scale (RTS), Monetary Choice Questionnaire, Probability Discounting Questionnaire, and Personality Inventory for DSM-5-Short Form (PID-5-SF) self-report questionnaires through an online platform. Hierarchical robust regression results showed that the linear combination of demographic variables (gender and active worker status), delay discounting measures and selected PID-5-SF trait scale scores (i.e., Attention Seeking and Risk Taking) explained roughly 39% of the RTS total score. As a whole, our findings underscore the role of demographic characteristics, dysfunctional personality traits and delay discounting in FRT expression. As a result, FRT is likely to represent the linear combination of several factors that should be assessed in order to understand FRT and prevent erroneous choices among lay investors.

Personality, risk tolerance and social network use: an exploratory study

2016 ◽  
Vol 42 (6) ◽  
pp. 536-552 ◽  
Author(s):  
Shaista Wasiuzzaman ◽  
Siavash Edalat
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Financial Risk ◽  
Ordinary Least Squares ◽  
Risk Tolerance ◽  
Network Activity ◽  
Least Squares Regression ◽  
Content Type ◽  
Financial Risk Tolerance

Purpose – The vast amount of information available via online social networks (OSN) makes it a very good avenue for understanding human behavior. One of the human characteristics of interest to financial practitioners is an individual’s financial risk tolerance. The purpose of this paper is to look at the relationship between an individual’s OSN behavior and his/her financial risk tolerance. Design/methodology/approach – The study uses data collected from a sample of 220 university students and the backward variables selection ordinary least squares regression analysis technique to achieve its objective. Findings – The results of the study find that the frequency of logging on to social network sites indicates an individual who has higher financial risk tolerance. Additionally, the increasing use of social networks for social connection is found to be associated with lower financial risk tolerance. The results are mostly consistent when the sample is split based on prior financial knowledge. Originality/value – To the authors’ knowledge this is the first study which documents the possibility of understanding an individual’s financial risk tolerance via his/her social network activity. This provides investment/financial consultants with more avenues for gathering information in order to understand their current or potential clients hence providing better services.

Impact of Behavioral Biases in Financial Risk Tolerance Ability of Mutual Fund Investors

2021 ◽  
Vol 7 (5) ◽  
pp. 2748-2765
Author(s):  
Nidhi Jain ◽  
Bikrant Kesari
Keyword(s):  
Mutual Fund ◽  
Financial Risk ◽  
Positive Impact ◽  
Investment Decision ◽  
Central India ◽  
Risk Tolerance ◽  
Behavioral Biases ◽  
Asset Class ◽  
Level Of Knowledge ◽  
Financial Risk Tolerance

Objective: The Behavioral bias is the term that deals with the investors’ psychology about their investment decision with their investment expertise. Every individual is biased, according to standard economic theory by his behavior and experiences which are rational. Methods: This research seeks to segregate mutual fund holders into various groups (persons and professionals) based on Behavioral biases and then investigates whether these Behavioral biases are influencing the level of knowledge of investors and the financial risk tolerance of certain mutual funds. Statistical tools compare investors characteristics and analyse how Behavioral biases are associated. Results: The factors analysed are financial circumstance, Type of Investors, Asset class preference, Time Horizon and Purpose of Investment. The primary information was gathered from 250 Central India mutual fund investors dependent on Judgment sampling. CFA, Correlation, MANOVA and Regression. Conclusions: Findings shows the effect of the behavior bias has positive impact on mutual fund investor awareness and financial risk tolerance.

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