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• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 金融代写|金融风险管理代写Financial Risk Management代考|DATA AND METHODOLOGY

As mentioned before, this research follows the standard survey method. The questionnaires were administered to students of the Master in Finance and Master in Management at the School of Economics and Management of the University of Porto (FEP) in Portugal. The questionnaire was written in English the language in which the referred masters were taught – and was made available in three consecutive academic years (2018/2019, 2019/2020, and 2020/2021).

The choice of finance students as an object of inquiry is not new in the literature. For example, Sjöberg and Engelberg (2009) used a survey with 93 students to conclude that individuals expressed a positive attitude towards risk-taking and gambling behaviors. And Cagle and Baucus (2006) and Friehs and Craig (2008) conducted surveys to Finance students using the responses of 86 individuals and 140 individuals, respectively.

A total of 272 survey responses were gathered, of which $112(=41.2 \%$ of the total) were completed by males and $160(=58.8 \%)$ by females. The survey form which was developed to gather research data is comprised of two parts. In part A of the survey, the respondents were asked a variety of control questions, including their age, chosen major, and their parents’ economic status and education level. In part B of the survey, the students were asked to answer the 13-item risk tolerance assessment instrument developed by Grable and Lytton (1999). For reference, the survey used in this study is included in the Appendix to this chapter.

The next step after the gathering of the surveys is the computation of the numerical value in the risk tolerance scale provided by Grable and Lytton (1999). These authors recurred to a principal component factor analysis to develop their scale, being able to extract three relevant constructs: a) investment risk (items $4,5,8,11$, and 12 ), b) risk comfort and experience (items 1,3,6,7 and 13), and c) speculative risk (items 2,9 and 10). These constructs reflect the multidimensional nature of the financial risk tolerance as emphasized by the authors. The risk tolerance scale varies from zero to 47 . Higher values in the scale imply a higher risk tolerance. The external validity of the instrument was assessed by comparing scale scores to the Survey of Consumer Finances risk-assessment item. The validity was confirmed since it was found that individuals who were categorized as having low risk tolerance were, in general, less confident and more likely to avoid making risky financial decisions than those who were categorized in higher risk tolerance categories. In a follow-up study, Grable and Lytton (2003) corroborated their scale’s validity showing a significant positive relationship between the scores of risk tolerance measured by the instrument and the level of equity assets owned by individuals. Moreover, lower scale scores were negatively associated with fixed income and cash ownership. Grable and Lytton (1999) and Gilliam et al (गni0) show that the ahovementioned survey is hefter at accurately assessing risk tolerance than the single question asked in the context of the Survey of Consumer Finances.

## 金融代写|金融风险管理代写Financial Risk Management代考|EMPIRICAL FINDINGS

Table 1 presents summary statistics for the entire sample, as well as subsamples for the male and female respondents. The data includes 272 responses, of which 112 were from male students and 160 from female students. The mean age of the respondents was $21.67$ years. Of the students surveyed, $63 \%$ reported having completed their undergraduate degree in the field of Management (this included courses on Management, Finance, and Marketing) and 32\% had obtained a degree in Economics. Almost half of the individuals (46\%) report having a mother with at least an undergraduate degree. This figure is somewhat similar in the case of the respondents’ fathers. The individuals whose paremts hold an undergraduate degree are about $30 \%$. For about one-third of the individuals, neither the father nor the mother holds at least an undergraduate degree, but in $21 \%$ of the cases at least one of the parents holds more than an undergraduate degree. The vast majority of students $(81 \%)$ reported having parents who earned less than 50,000 euros in annual income. Only $5 \%$ of respondents indicate having parents who earned more than 100,000 euros per year.

Table 1 presents the summary statistics for the whole sample, as well as subsamples segmented by gender. The final column presents the p-values from associated difference tests. The z-test was used to assess the statistical significance of the difference between the proportions of respondents in the two subsamples. The t-test was used to assess the statistical significance of the difference in the mean age of the respondents of the two subsamples. Age represents the mean age of the respondents. Economics (Management) is the proportion of respondents with a major in the field of Economics (Management, Finance or Marketing). Others stand for the percentage of respondents with majors in other fields of study. Dad_CollPlus (Mom_CollPlus) is the proportion of respondents whose father (mother) holds at least an undergraduate degree. Dad_Grad (Mom_Grad) is the proportion of respondents whose father (mother) holds a graduate degree. Parent_LowEd is the proportion of respondents in which neither their father nor mother holds at least an undergraduate degree. Parent_HighEd is the proportion of respondents in which either their father or mother holds more than an undergraduate degree. High_Income is the proportion of respondents whose parents earned more than 100,000 euros. Low_Income is the propor-tion of respondents whose parents earned less than 50,000 euros. ** and *** represent significance at the $5 \%$ and $1 \%$ levels, respectively.

# 金融风险管理代考

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