for loop compute historical volatility select lines per year

Question

i am a beginner on R and i am currently trying to compute the historical volatility per year. My dataset looks like this :

date           prices

01/01/2000     100

03/01/2000     98

05/10/2000     103

08/03/2001     102

08/04/2001     110

i would like to create a for loop in order to compute quickly the historical volatility i have been computing "manually" as follows :

data_hv <- read.csv("file")
data_hv_2000 <- data_hv[(1:259),]
data_hv_2001 <- data_hv[(260:518),]
data_hv_2002 <- data_hv[(519:778),]
data_hv_2003 <- data_hv[(779:1038),]

and then, computing the historical volatility once i have grouped per year the data in subsets of data :

price = data_hv_2000$price
ret <- log(lag(price)) - log(price)
print(ret)
vol <- sd(ret, na.rm = TRUE) * sqrt(259) * 100
vol

price_2001 = data_hv_2001$price
ret <- log(lag(price_2001)) - log(price_2001)
vol_2001 <- sd(ret, na.rm = TRUE) * sqrt(260) * 100
vol_2001

260 and 259 being the number of rows of each subset.

i have tried to start doing a for loop :

data_hv %>%
  for (i in 2000:2022) {
    filter(contains(i)) %>%
    price_i = data_hv_i$Wheat
    ret <- log(lag(price_i)) - log(price_i)
    vol_i <- sd(ret, na.rm = TRUE) * sqrt(nrows(data_hv_i)) * 100
    vol_i 
}

but it doesn't work and im a bit lost. I would finally like to store these values in a list (one value - the historical volatility - per year). Could anyone help me ?

score 0 · Accepted Answer · answered Jun 20 '22 at 17:04

There are a couple things you want to remember when running for loops and one of them is to create a empty object of desired type before running the loop. Also, you are piping into a for-loop and into an object, which is probably causing an error.

data_hv %>%
  for (i in 2000:2022) {
    filter(contains(i)) %>%
    price_i = data_hv_i$Wheat
    ret <- log(lag(price_i)) - log(price_i)
    vol_i <- sd(ret, na.rm = TRUE) * sqrt(nrows(data_hv_i)) * 100
    vol_i 
}

Try this:

# when doing a for-loop save to an empty object first
vol_final <- list()

# then iterate over what you want

  for (i in 2000:2022) {
      
      # do work
      data_hv_i <- data_hv %>% filter(year == i)
      
      price_i = data_hv_i$prices
      ret <- log(lag(price_i)) - log(price_i)
      vol_i <- sd(ret, na.rm = TRUE) * sqrt(nrow(data_hv_i)) * 100
      
      #finally save to a list by appending a list to a list, e.g. vol_i -> vol_final
      vol_final  <- append(vol_final, list(data.frame(year = i, vol_i)))
  }

vol_final
#

Final Solution

library(clock)
#> Warning: package 'clock' was built under R version 4.1.3
library(tidyverse)
library(lubridate)
#> 
#> Attaching package: 'lubridate'
#> The following object is masked from 'package:clock':
#> 
#>     as_date
#> The following objects are masked from 'package:base':
#> 
#>     date, intersect, setdiff, union

data_hv <- tibble(date = rep(date_build(2000:2022), 263),
                  prices = rnorm(6049, 100, 2),
                  year = year(date))

# when doing a for-loop save to an empty object first
vol_final <- list()

# then iterate over what you want

  for (i in 2000:2022) {
      
      # do work
      data_hv_i <- data_hv %>% filter(year == i)
      
      price_i = data_hv_i$prices
      ret <- log(lag(price_i)) - log(price_i)
      vol_i <- sd(ret, na.rm = TRUE) * sqrt(nrow(data_hv_i)) * 100
      
      #finally save to a list by appending a list to a list, e.g. vol_i -> vol_final
      vol_final  <- append(vol_final, list(data.frame(year = i, vol_i)))
  }

vol_final
#> [[1]]
#>   year    vol_i
#> 1 2000 44.07769
#> 
#> [[2]]
#>   year    vol_i
#> 1 2001 43.39855
#> 
#> [[3]]
#>   year    vol_i
#> 1 2002 41.52856
#> 
#> [[4]]
#>   year   vol_i
#> 1 2003 43.0145
#> 
#> [[5]]
#>   year    vol_i
#> 1 2004 46.15526
#> 
#> [[6]]
#>   year    vol_i
#> 1 2005 49.52201
#> 
#> [[7]]
#>   year    vol_i
#> 1 2006 49.14017
#> 
#> [[8]]
#>   year    vol_i
#> 1 2007 46.17739
#> 
#> [[9]]
#>   year    vol_i
#> 1 2008 46.81863
#> 
#> [[10]]
#>   year    vol_i
#> 1 2009 43.77617
#> 
#> [[11]]
#>   year    vol_i
#> 1 2010 47.30922
#> 
#> [[12]]
#>   year    vol_i
#> 1 2011 47.00433
#> 
#> [[13]]
#>   year    vol_i
#> 1 2012 45.93459
#> 
#> [[14]]
#>   year    vol_i
#> 1 2013 40.46577
#> 
#> [[15]]
#>   year    vol_i
#> 1 2014 48.49482
#> 
#> [[16]]
#>   year    vol_i
#> 1 2015 44.76563
#> 
#> [[17]]
#>   year    vol_i
#> 1 2016 45.18651
#> 
#> [[18]]
#>   year    vol_i
#> 1 2017 49.04513
#> 
#> [[19]]
#>   year   vol_i
#> 1 2018 45.6688
#> 
#> [[20]]
#>   year    vol_i
#> 1 2019 43.08453
#> 
#> [[21]]
#>   year    vol_i
#> 1 2020 46.07952
#> 
#> [[22]]
#>   year    vol_i
#> 1 2021 47.65877
#> 
#> [[23]]
#>   year    vol_i
#> 1 2022 45.06297

^{Created on 2022-06-20 by the reprex package (v2.0.1)}

thanks, im gonna try this ! why did you choose "263" tho when creating data_hv ? — user19304348, Jun 21 '22 at 08:24
i have understood that 263 is the number of lines per year. Yet in my dataset there are actually less, and the number of observation per years varies from year to year... having tried the for loop of the code instead after manually adding to my csv a column "year" for each price, i get a message of error : "Error in `vec_slice()`: ! `x` must be a vector, not NULL" after "vol_final"... do you know how i could fix this ? — user19304348, Jun 21 '22 at 08:56
If you could provide a reprex of the error and then add to your question that would help diagnose the issue. I'm guessing (without seeing your csv) that something might be wrong with your csv. Also, no need to manually enter 'year' to your csv. Instead, use your date column to do the work for you, `df %>% mutate(year = lubridate::year(date))`. — Josh Erickson, Jun 21 '22 at 12:26
Ahhh, I think it's you forgot to change the code from `price_i = data_hv_i$Wheat` to `price_i = data_hv_i$prices`. — Josh Erickson, Jun 21 '22 at 12:44

for loop compute historical volatility select lines per year

and then, computing the historical volatility once i have grouped per year the data in subsets of data :

260 and 259 being the number of rows of each subset.

i have tried to start doing a for loop :

but it doesn't work and im a bit lost. I would finally like to store these values in a list (one value - the historical volatility - per year). Could anyone help me ?

1 Answers1