(1) Import a CSV Data File in R:
library(quantmod)
library(PerformanceAnalytics)
Apple_CSV <- read.zoo("AAPL.csv",header = TRUE, sep =",",format="%m/%d/%Y")
(2) Clean Imported Data and Calculate Daily Return of AAPL:
AAPL_Prices <- as.xts(x = Apple_CSV$Adj.Close)
AAPL_Returns <- dailyReturn(AAPL_Prices)
(3) Summarize AAPL Daily Return Data:
head(AAPL_Returns)
## daily.returns
## 2015-01-02 0.000000e+00
## 2015-01-05 -2.817169e-02
## 2015-01-06 9.450198e-05
## 2015-01-07 1.402209e-02
## 2015-01-08 3.842243e-02
## 2015-01-09 1.072070e-03
tail(AAPL_Returns)
## daily.returns
## 2019-12-23 0.0163183658
## 2019-12-24 0.0009506422
## 2019-12-26 0.0198403820
## 2019-12-27 -0.0003795103
## 2019-12-30 0.0059351588
## 2019-12-31 0.0073064655
summary(AAPL_Returns)
## Index daily.returns
## Min. :2015-01-02 Min. :-0.0996074
## 1st Qu.:2016-04-04 1st Qu.:-0.0058529
## Median :2017-07-01 Median : 0.0008920
## Mean :2017-07-01 Mean : 0.0009755
## 3rd Qu.:2018-09-30 3rd Qu.: 0.0089108
## Max. :2019-12-31 Max. : 0.0704214
(4) Calculate Value at Risk (VaR) and Conditional Value at Risk (CVaR):
VaR(AAPL_Returns, p=0.95, method = "historical")
## daily.returns
## VaR -0.02499576
CVaR(AAPL_Returns, p=0.95, method = "historical")
## daily.returns
## ES -0.03617996