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kwoongbae committed Jul 14, 2024
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22 changes: 11 additions & 11 deletions README.md
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- **보험사 규제모형 관련 문헌**

- | Reference | Journal | Study |
| ------------------------------------------------------------ | -------------------- | :----------------------------------------------------------- |
| [Alm (2015)](https://www.tandfonline.com/doi/abs/10.1080/03461238.2013.787367) | ***SAJ*** | [review](https://github.com/kwoongbae/risk-management-papers/issues/36) / [seminar file](./review/Seminar_20240626.pdf) |
| [Bermúdez et al. (2013)](https://www.cambridge.org/core/journals/astin-bulletin-journal-of-the-iaa/article/correlation-sensitivity-analysis-of-nonlife-underwriting-risk-in-solvency-capital-requirement-estimation/8C16299AF4E9DFCD13C5C7EA3697705E) | ***ASTIN Bulletin*** | [review](https://github.com/kwoongbae/risk-management-papers/issues/37) |
| [Eling and Schnell (2020)](https://www.tandfonline.com/doi/abs/10.1080/10920277.2019.1641416) | ***NAAJ*** | [review](https://github.com/kwoongbae/risk-management-papers/issues/32) / [code](./code/Eling_and_Schnell_NAAJ_2020.r) |
- | Reference | Journal | Review | Supplementary review |
| ------------------------------------------------------------ | -------------------- | :----------------------------------------------------------- | ------------------------------------------------------------ |
| [Alm (2015)](https://www.tandfonline.com/doi/abs/10.1080/03461238.2013.787367) | ***SAJ*** | [review](https://github.com/kwoongbae/risk-management-papers/issues/36) / [seminar file](./review/Seminar_20240626.pdf) | |
| [Bermúdez et al. (2013)](https://www.cambridge.org/core/journals/astin-bulletin-journal-of-the-iaa/article/correlation-sensitivity-analysis-of-nonlife-underwriting-risk-in-solvency-capital-requirement-estimation/8C16299AF4E9DFCD13C5C7EA3697705E) | ***ASTIN Bulletin*** | [review](https://github.com/kwoongbae/risk-management-papers/issues/37) | [Internal-approach-summary](./review/Bermúdez et al., 2013 suppl.pdf) |
| [Eling and Schnell (2020)](https://www.tandfonline.com/doi/abs/10.1080/10920277.2019.1641416) | ***NAAJ*** | [review](https://github.com/kwoongbae/risk-management-papers/issues/32) | [code](https://github.com/kwoongbae/risk-management-papers/blob/main/code/Eling_and_Schnell_NAAJ_2020.r) |

- **(시스템적) 사이버 리스크 관련 문헌**

- | Reference | Journal | Study |
| ------------------------------------------------------------ | ------------------- | --------------------------------------------- |
| [Aldasoro et al. (2022)](https://www.sciencedirect.com/science/article/abs/pii/S1572308922000171) | ***JFS*** | [review](./review/Aldasoro_JRS_2022.pdf) |
| [Awiszus et al. (2023)](https://arxiv.org/abs/2211.04762) | ***JRI*** | [seminar file](./review/Seminar_20240125.pdf) |
| [Bobtcheff et al. (2016)](https://link.springer.com/article/10.1057/grir.2016.1) | ***GPRI*** | [seminar file](./review/Seminar_20240524.pdf) |
| [Welburn and Strong (2021)](https://onlinelibrary.wiley.com/doi/abs/10.1111/risa.13715) | ***Risk Analysis*** | [seminar file](./review/Seminar_20240321.pdf) |
- | Reference | Journal | Review | Supplementary review |
| ------------------------------------------------------------ | ------------------- | --------------------------------------------- | -------------------- |
| [Aldasoro et al. (2022)](https://www.sciencedirect.com/science/article/abs/pii/S1572308922000171) | ***JFS*** | [review](./review/Aldasoro_JRS_2022.pdf) | |
| [Awiszus et al. (2023)](https://arxiv.org/abs/2211.04762) | ***JRI*** | [seminar file](./review/Seminar_20240125.pdf) | |
| [Bobtcheff et al. (2016)](https://link.springer.com/article/10.1057/grir.2016.1) | ***GPRI*** | [seminar file](./review/Seminar_20240524.pdf) | |
| [Welburn and Strong (2021)](https://onlinelibrary.wiley.com/doi/abs/10.1111/risa.13715) | ***Risk Analysis*** | [seminar file](./review/Seminar_20240321.pdf) | |

---

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100 changes: 100 additions & 0 deletions code/.Rhistory
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Expand Up @@ -98,3 +98,103 @@ df <- data.frame(x = sim[,1], y = sim[,2])
p <- ggplot(df, aes(x, y)) + geom_point() + theme(axis.text.x = element_text(size = 14), axis.text.y = element_text(size = 14)) +
xlab("X") + ylab("Y") + ggtitle(expression(paste(rho, "=0.5")))
ggExtra::ggMarginal(p, type = "histogram")
set.seed(1234)
rm(list=ls())
# Required packages
library(mvtnorm)
library(ggplot2)
library(ggExtra)
library(sn)
sim.GC <- function(n, rho, qmarg1, qmarg2){
R <- rbind(c(1,rho),c(rho,1)) #rho가 두 변수 간의 상관관계를 의미함.
dat <- rmvnorm(n, mean = c(0,0), sigma = R)
dat[,1] <- qmarg1(pnorm(dat[,1]))
dat[,2] <- qmarg2(pnorm(dat[,2]))
return(dat)
}
q1 <- function(p) qunif(p)
q2 <- function(p) qunif(p)
ns <- 1000; rho = 0.7
sim <- sim.GC(n = ns, rho = rho,q1,q2)
df <- data.frame(x = sim[,1], y = sim[,2])
p <- ggplot(df, aes(x, y)) + geom_point() + theme(axis.text.x = element_text(size = 14), axis.text.y = element_text(size = 14)) +
xlab("X") + ylab("Y") + ggtitle(expression(paste(rho, "=0.5")))
ggExtra::ggMarginal(p, type = "histogram")
df
plotdist(df)
plotdist(df$x)
library(fitdistrplus)
plotdist(df$x)
q1 <- function(p) qt(p, df = 4)
q2 <- function(p) qt(p, df = 4)
ns <- 1000; rho = 0.5
sim <- sim.GC(n = ns,rho = rho,q1,q2)
df <- data.frame(x = sim[,1], y = sim[,2])
p <- ggplot(df, aes(x, y)) + geom_point() + theme(axis.text.x = element_text(size = 14), axis.text.y = element_text(size = 14)) +
xlab("X") + ylab("Y") + ggtitle(expression(paste(rho, "=0.5")))
ggExtra::ggMarginal(p, type = "histogram")
sim.GC <- function(n, rho, qmarg1, qmarg2){
R <- rbind(c(1,rho),c(rho,1)) #rho가 두 변수 간의 상관관계를 의미함.
dat <- rmvnorm(n, mean = c(0,0), sigma = R)
dat[,1] <- qmarg1(pnorm(dat[,1]))
dat[,2] <- qmarg2(pnorm(dat[,2]))
return(dat)
}
q1 <- function(p) qunif(p)
q2 <- function(p) qunif(p)
ns <- 1000; rho = 0.7
sim <- sim.GC(n = ns, rho = rho,q1,q2)
df <- data.frame(x = sim[,1], y = sim[,2])
plotdist(df$x)
p <- ggplot(df, aes(x, y)) + geom_point() + theme(axis.text.x = element_text(size = 14), axis.text.y = element_text(size = 14)) +
xlab("X") + ylab("Y") + ggtitle(expression(paste(rho, "=0.5")))
ggExtra::ggMarginal(p, type = "histogram")
grid::grid.newpage()
sim.GC <- function(n, rho, qmarg1, qmarg2){
R <- rbind(c(1,rho),c(rho,1)) #rho가 두 변수 간의 상관관계를 의미함.
dat <- rmvnorm(n, mean = c(0,0), sigma = R)
dat[,1] <- qmarg1(pnorm(dat[,1]))
dat[,2] <- qmarg2(pnorm(dat[,2]))
return(dat)
}
q1 <- function(p) qunif(p)
q2 <- function(p) qunif(p)
ns <- 1000; rho = 0.7
sim <- sim.GC(n = ns, rho = rho,q1,q2)
df <- data.frame(x = sim[,1], y = sim[,2])
df <- data.frame(x = sim[,1], y = sim[,2])/
#plotdist(df$x)
p <- ggplot(df, aes(x, y)) + geom_point() + theme(axis.text.x = element_text(size = 14), axis.text.y = element_text(size = 14)) +
xlab("X") + ylab("Y") + ggtitle(expression(paste(rho, "=0.5")))
df <- data.frame(x = sim[,1], y = sim[,2])
#plotdist(df$x)
p <- ggplot(df, aes(x, y)) + geom_point() + theme(axis.text.x = element_text(size = 14), axis.text.y = element_text(size = 14)) +
xlab("X") + ylab("Y") + ggtitle(expression(paste(rho, "=0.5")))
ggExtra::ggMarginal(p, type = "histogram")
ns <- 1000; rho = 0.75
sim <- sim.GC(n = ns,rho = rho,q1,q2)
df <- data.frame(x = sim[,1], y = sim[,2])
p <- ggplot(df, aes(x, y)) + geom_point() + theme(axis.text.x = element_text(size = 14), axis.text.y = element_text(size = 14)) +
xlab("X") + ylab("Y") + ggtitle(expression(paste(rho, "=0.75")))
ggExtra::ggMarginal(p, type = "histogram")
# ===================================================
# Student-t with 4 degrees of freedom marginal for X
# Standard normal for Y
# ===================================================
q1 <- function(p) qt(p, df = 4)
q2 <- function(p) qnorm(p)
ns <- 1000; rho = 0.5
sim <- sim.GC(n = ns,rho = rho,q1,q2)
df <- data.frame(x = sim[,1], y = sim[,2])
p <- ggplot(df, aes(x, y)) + geom_point() + theme(axis.text.x = element_text(size = 14), axis.text.y = element_text(size = 14)) +
xlab("X") + ylab("Y") + ggtitle(expression(paste(rho, "=0.5")))
ggExtra::ggMarginal(p, type = "histogram")
p
q1 <- function(p) qlogis(p)
q2 <- function(p) qlogis(p)
ns <- 1000; rho = 0.5
sim <- sim.GC(n = ns,rho = rho,q1,q2)
df <- data.frame(x = sim[,1], y = sim[,2])
p <- ggplot(df, aes(x, y)) + geom_point() + theme(axis.text.x = element_text(size = 14), axis.text.y = element_text(size = 14)) +
xlab("X") + ylab("Y") + ggtitle(expression(paste(rho, "=0.5")))
ggExtra::ggMarginal(p, type = "histogram")
2 changes: 2 additions & 0 deletions code/Copula.r
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library(ggplot2)
library(ggExtra)
library(sn)
library(fitdistrplus)

# ===================================================
# normal margins
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ns <- 1000; rho = 0.7
sim <- sim.GC(n = ns, rho = rho,q1,q2)
df <- data.frame(x = sim[,1], y = sim[,2])
#plotdist(df$x)
p <- ggplot(df, aes(x, y)) + geom_point() + theme(axis.text.x = element_text(size = 14), axis.text.y = element_text(size = 14)) +
xlab("X") + ylab("Y") + ggtitle(expression(paste(rho, "=0.5")))
ggExtra::ggMarginal(p, type = "histogram")
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