EDA: A Survey into Market Risk Premium
Feb 23, 2020 #finance
This is an exploratory analysis based on the paper cited below. I am interested to explore the relationship of coefficient of variation (CV) between developed and developing countries.
Fernandez, Pablo and Martinez, Mar and Fernández Acín, Isabel, Market Risk Premium and Risk-Free Rate Used for 69 Countries in 2019: A Survey (March 23, 2019). Available at SSRN: https://ssrn.com/abstract=3358901 or http://dx.doi.org/10.2139/ssrn.3358901
To classify countries into developed or developing status, I use a general rough guide where country with GDP per capita above 24000 is considered developed. Alternatively, I could use human development index (HDI) but the former is commonly used among many economists.
hl.this = c("China", "United States of America", "Germany", "Japan") df %>% ggplot(aes(median, cv, col = log(answers))) + geom_point() + scale_y_continuous(limits = c(0, 50)) + geom_mark_circle(aes(description = country, filter = country %in% hl.this), col = "darkgray", con.colour = "darkgray") + labs(x = "Median of MRP", y = "Coefficient of Variation", col = "Sample Size (log)", title = "Market Risk Premium: A Survey (Fernandez, 2019)")
Developed or not does not seem to exhibit any relationship to variation.
df %>% filter(!is.na(developed)) %>% ggplot(aes(factor(developed), cv)) + geom_point(position = position_jitter(width = 0.2, height = 0)) + scale_x_discrete(labels = c(`0` = "false", `1` = "true")) + labs(x = "Developed Country", y = "Coefficient of Variation")