hw31122021

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library(tidyverse)

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──

## ✓ ggplot2 3.3.5     ✓ purrr   0.3.4
## ✓ tibble  3.1.5     ✓ dplyr   1.0.7
## ✓ tidyr   1.1.4     ✓ stringr 1.4.0
## ✓ readr   2.0.2     ✓ forcats 0.5.1

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(dplyr)
library(tidyquant)

## Loading required package: lubridate

## 
## Attaching package: 'lubridate'

## The following objects are masked from 'package:base':
## 
##     date, intersect, setdiff, union

## Loading required package: PerformanceAnalytics

## Loading required package: xts

## Loading required package: zoo

## 
## Attaching package: 'zoo'

## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric

## 
## Attaching package: 'xts'

## The following objects are masked from 'package:dplyr':
## 
##     first, last

## 
## Attaching package: 'PerformanceAnalytics'

## The following object is masked from 'package:graphics':
## 
##     legend

## Loading required package: quantmod

## Loading required package: TTR

## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo

## ══ Need to Learn tidyquant? ════════════════════════════════════════════════════
## Business Science offers a 1-hour course - Learning Lab #9: Performance Analysis & Portfolio Optimization with tidyquant!
## </> Learn more at: https://university.business-science.io/p/learning-labs-pro </>

library(timetk)
library(readr)
test_tej <- read_csv("test_tej.csv")

## Rows: 980 Columns: 4

## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): CoName
## dbl (3): CO_ID, Date, Close

## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

test_tej$CO_ID<-as.character(test_tej$CO_ID)
test_tej$Date<-as.character(test_tej$Date)
test_tej$Date<-as.Date(test_tej$Date, '%Y%m%d')
test_tejin<-select(test_tej,CO_ID,Date,Close,CoName)
ret_day <- test_tejin  %>% tk_xts(select = -Date, date_var = Date) %>% Return.calculate(method = "log")

## Warning: Non-numeric columns being dropped: CO_ID, CoName

head(ret_day,10)

##                 Close
## 2020-12-30         NA
## 2020-12-30 -1.4399463
## 2020-12-30  0.2940439
## 2020-12-30 -0.1587541
## 2020-12-31  1.3099875
## 2020-12-31 -1.4395834
## 2020-12-31  0.3033404
## 2020-12-31 -0.1756096
## 2021-01-04  1.3288841
## 2021-01-04 -1.4569473

ret_mon <- test_tej %>%tk_xts(select = -Date, date_var = Date) %>%to.period(period  = "months",indexAt = "lastof",OHLC    = FALSE)  %>% Return.calculate(method = 'log')

## Warning: Non-numeric columns being dropped: CO_ID, CoName

head(ret_mon,10)

##                   Close
## 2020-12-31           NA
## 2021-01-31 -0.006868588
## 2021-02-28  0.017083814
## 2021-03-31  0.063248037
## 2021-04-30  0.037451185
## 2021-05-31 -0.007266661
## 2021-06-30  0.029572419
## 2021-07-31  0.023150428
## 2021-08-31  0.027039316
## 2021-09-30 -0.026773253

hw31122021

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12/30/2021

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