README.Rmd

---
output: github_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(
  comment = "#>",
  collapse = TRUE,
  out.width = "70%",
  fig.align = "center",
  fig.width = 6,
  fig.asp = .618
  )
options(digits = 3)
pander::panderOptions("round", 3)
```

# nonparam-cvar

This is a project perfomed in SKKU **Nonparametric statistics course ([STA5015](https://sites.google.com/site/eunryungleestat/))**. It aims at:

- intensive review on existing statistical methods for an advanced topic not covered in the course
- own simulation or real data simulation
- development of new statistical methodology related to the course
- new analysis of a real data set

## Overview

I reviewed

[Cai, Z., & Wang, X. (2008). *Nonparametric estimation of conditional VaR and expected shortfall*. Journal of Econometrics, 147(1), 120-130.](https://www.sciencedirect.com/science/article/abs/pii/S0304407608001292)

- My [ygeunkim/ceshat](https://github.com/ygeunkim/ceshat) development package is the one to carry out this project.
- If you are interested in this, check it out.

## Results

There will be two presentations and one report.

1. [Brief slide](https://github.com/ygeunkim/nonparam-cvar/blob/master/static/slides/younggeunslide1.pdf)
2. [Final presentation slide](https://github.com/ygeunkim/nonparam-cvar/blob/master/static/slides/younggeunslide2.pdf)
3. [Final Report](https://github.com/ygeunkim/nonparam-cvar/blob/master/static/report/report_text/younggeunreport.pdf)