Min Joon Lee
Biographic Data
| ID | 7953833 |
|---|---|
| NAME | Min Joon Lee |
| GIVEN NAMES | Min Joon |
| FAMILY NAME | Lee |
| SIGNATURE | LEE M J |
| AFFILIATIONS | Korea University |
| ORCID | 0000-0003-2722-8526 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 0 |
Heterogeneity in Expectations, Risk Tolerance, and Household Stock Shares
This paper jointly estimates the relationship between stock share and expectations and risk preferences. The survey allows individual-level, quantitative estimates of risk tolerance and of the perceived mean and variance of stock returns. These estimates have economically and statistically significant association for the distribution of stock shares with relative magnitudes in proportion with the predictions of theories. Incorporating survey meas…
Machine Learning-Based Data Mining Method for Sentiment Analysis of the Sewol Ferry Disaster's Effect on Social Stress
The Sewol Ferry Disaster which took place in 16th of April, 2014, was a national level disaster in South Korea that caused severe social distress nation-wide. No research at the domestic level thus far has examined the influence of the disaster on social stress through a sentiment analysis of social media data. Data extracted from YouTube, Twitter, and Facebook were used in this study. The population was users who were randomly selected from the …
No prominent works on this page.
Heterogeneity in Expectations, Risk Tolerance, and Household Stock Shares
This paper jointly estimates the relationship between stock share and expectations and risk preferences. The survey allows individual-level, quantitative estimates of risk tolerance and of the perceived mean and variance of stock returns. These estimates have economically and statistically significant association for the distribution of stock shares with relative magnitudes in proportion with the predictions of theories. Incorporating survey meas…
Machine Learning-Based Data Mining Method for Sentiment Analysis of the Sewol Ferry Disaster's Effect on Social Stress
The Sewol Ferry Disaster which took place in 16th of April, 2014, was a national level disaster in South Korea that caused severe social distress nation-wide. No research at the domestic level thus far has examined the influence of the disaster on social stress through a sentiment analysis of social media data. Data extracted from YouTube, Twitter, and Facebook were used in this study. The population was users who were randomly selected from the …
Actuarial science (1 work) · Advertising (1 work) · Artificial Intelligence (1 work) · Big data (1 work) · Business (1 work) · Computer Science (1 work) · Data mining (1 work) · Demography (1 work) · Demography (1 work) · Diverse Approaches in Healthcare and Education Studies (1 work)