BlackRock ESG ETF

# if you haven't installed the tidyverse yet, uncomment the next line and install it before loading the library: 
# install.packages("tidyverse")

library(tidyverse)

── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
✔ ggplot2 3.4.0      ✔ purrr   1.0.1 
✔ tibble  3.1.8      ✔ dplyr   1.0.10
✔ tidyr   1.3.0      ✔ stringr 1.5.0 
✔ readr   2.1.3      ✔ forcats 0.5.2 
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

#> ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
#> ✔ ggplot2 3.4.0      ✔ purrr   0.3.5 
#> ✔ tibble  3.1.8      ✔ dplyr   1.0.10
#> ✔ tidyr   1.2.1      ✔ stringr 1.4.1 
#> ✔ readr   2.1.3      ✔ forcats 0.5.2 
#> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag()    masks stats::lag()

install.packages("tidyverse")

Warning: package 'tidyverse' is in use and will not be installed

library(tidyverse)

install.packages("readr")

Warning: package 'readr' is in use and will not be installed

library(readr)

# assign the url to `github_raw_csv_url`
github_raw_csv_url <- "https://raw.githubusercontent.com/t-emery/sais-susfin_data/main/datasets/blackrock_etf_screener_2022-08-30.csv"

# read in the data, and assign it to the object `blackrock_etf_data`
blackrock_etf_data <- read_csv(github_raw_csv_url)

Rows: 393 Columns: 22
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (14): ticker, name, incept_date, net_assets_as_of, asset_class, sub_asse...
dbl  (8): gross_expense_ratio_percent, net_expense_ratio_percent, net_assets...

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.

# print out the tibble to take a look at the data
blackrock_etf_data

# A tibble: 393 × 22
   ticker name    incep…¹ gross…² net_e…³ net_a…⁴ net_a…⁵ asset…⁶ sub_a…⁷ region
   <chr>  <chr>   <chr>     <dbl>   <dbl>   <dbl> <chr>   <chr>   <chr>   <chr> 
 1 IVV    iShare… 5/15/00    0.03    0.03 297663. 8/30/22 Equity  Large … North…
 2 IEFA   iShare… 10/18/…    0.07    0.07  84222. 8/30/22 Equity  All Cap Global
 3 AGG    iShare… 9/22/03    0.04    0.03  82344. 8/30/22 Fixed … Multi … North…
 4 IJR    iShare… 5/22/00    0.06    0.06  66533. 8/30/22 Equity  Small … North…
 5 IEMG   iShare… 10/18/…    0.09    0.09  64920. 8/30/22 Equity  All Cap Global
 6 IWF    iShare… 5/22/00    0.18    0.18  61831. 8/30/22 Equity  Large/… North…
 7 IJH    iShare… 5/22/00    0.05    0.05  61424. 8/30/22 Equity  Mid Cap North…
 8 IWM    iShare… 5/22/00    0.19    0.19  53048. 8/30/22 Equity  Small … North…
 9 IWD    iShare… 5/22/00    0.18    0.18  51913. 8/30/22 Equity  Large/… North…
10 EFA    iShare… 8/14/01    0.32    0.32  44144. 8/30/22 Equity  Large/… Global
# … with 383 more rows, 12 more variables: market <chr>, location <chr>,
#   investment_style <chr>,
#   sustainability_characteristics_msci_esg_fund_ratings_msci_esg_fund_rating_aaa_ccc <chr>,
#   msci_esg_quality_score_0_10 <dbl>,
#   msci_weighted_average_carbon_intensity_tons_co2e_m_sales <dbl>,
#   msci_esg_percent_coverage <dbl>, sustainable_classification <chr>,
#   name_wo_ishares_etf <chr>, is_esg <chr>, years_from_inception <dbl>, …

# Uncomment (delete the #) to run the code below
 View(blackrock_etf_data)

install.packages("dplyr")

Warning: package 'dplyr' is in use and will not be installed

library(dplyr)

glimpse(blackrock_etf_data)

Rows: 393
Columns: 22
$ ticker                                                                            <chr> …
$ name                                                                              <chr> …
$ incept_date                                                                       <chr> …
$ gross_expense_ratio_percent                                                       <dbl> …
$ net_expense_ratio_percent                                                         <dbl> …
$ net_assets_usd_mn                                                                 <dbl> …
$ net_assets_as_of                                                                  <chr> …
$ asset_class                                                                       <chr> …
$ sub_asset_class                                                                   <chr> …
$ region                                                                            <chr> …
$ market                                                                            <chr> …
$ location                                                                          <chr> …
$ investment_style                                                                  <chr> …
$ sustainability_characteristics_msci_esg_fund_ratings_msci_esg_fund_rating_aaa_ccc <chr> …
$ msci_esg_quality_score_0_10                                                       <dbl> …
$ msci_weighted_average_carbon_intensity_tons_co2e_m_sales                          <dbl> …
$ msci_esg_percent_coverage                                                         <dbl> …
$ sustainable_classification                                                        <chr> …
$ name_wo_ishares_etf                                                               <chr> …
$ is_esg                                                                            <chr> …
$ years_from_inception                                                              <dbl> …
$ year_launched                                                                     <dbl> …

mini_blackrock_data <- blackrock_etf_data |> 
  # group by whether the fund is an ESG fund or not
  group_by(is_esg) |> 
  # take the top 5 from each group, by net assets
  slice_max(order_by = net_assets_usd_mn, n = 5) |> 
  # select the following columns 
  select(ticker, name, asset_class, sub_asset_class, region, incept_date, net_assets_usd_mn,
         msci_weighted_average_carbon_intensity_tons_co2e_m_sales) |> 
  # rename to `co2_intensity` because the full name is a mouthful, if descriptive.
  rename(co2_intensity = msci_weighted_average_carbon_intensity_tons_co2e_m_sales) |> 
  # always good to ungroup() if you've used a group_by().  We'll discuss later.
  ungroup()

Adding missing grouping variables: `is_esg`

mini_blackrock_data

# A tibble: 10 × 9
   is_esg       ticker name       asset…¹ sub_a…² region incep…³ net_a…⁴ co2_i…⁵
   <chr>        <chr>  <chr>      <chr>   <chr>   <chr>  <chr>     <dbl>   <dbl>
 1 ESG Fund     ESGU   iShares E… Equity  Large/… North… 12/1/16  22377.   104. 
 2 ESG Fund     ESGD   iShares E… Equity  Large/… Global 6/28/16   6426.   104. 
 3 ESG Fund     ICLN   iShares G… Equity  All Cap Global 6/24/08   5628.   266. 
 4 ESG Fund     ESGE   iShares E… Equity  Large/… Global 6/28/16   4234.   168. 
 5 ESG Fund     DSI    iShares M… Equity  Large/… North… 11/14/…   3689.    72.7
 6 Regular Fund IVV    iShares C… Equity  Large … North… 5/15/00 297663.   148. 
 7 Regular Fund IEFA   iShares C… Equity  All Cap Global 10/18/…  84222.   127. 
 8 Regular Fund AGG    iShares C… Fixed … Multi … North… 9/22/03  82344.   283. 
 9 Regular Fund IJR    iShares C… Equity  Small … North… 5/22/00  66533.   133. 
10 Regular Fund IEMG   iShares C… Equity  All Cap Global 10/18/…  64920.   369. 
# … with abbreviated variable names ¹​asset_class, ²​sub_asset_class,
#   ³​incept_date, ⁴​net_assets_usd_mn, ⁵​co2_intensity

mini_blackrock_data |> glimpse()

Rows: 10
Columns: 9
$ is_esg            <chr> "ESG Fund", "ESG Fund", "ESG Fund", "ESG Fund", "ESG…
$ ticker            <chr> "ESGU", "ESGD", "ICLN", "ESGE", "DSI", "IVV", "IEFA"…
$ name              <chr> "iShares ESG Aware MSCI USA ETF", "iShares ESG Aware…
$ asset_class       <chr> "Equity", "Equity", "Equity", "Equity", "Equity", "E…
$ sub_asset_class   <chr> "Large/Mid Cap", "Large/Mid Cap", "All Cap", "Large/…
$ region            <chr> "North America", "Global", "Global", "Global", "Nort…
$ incept_date       <chr> "12/1/16", "6/28/16", "6/24/08", "6/28/16", "11/14/0…
$ net_assets_usd_mn <dbl> 22376.688, 6425.673, 5628.011, 4233.544, 3688.930, 2…
$ co2_intensity     <dbl> 103.60, 103.83, 265.82, 167.71, 72.73, 148.34, 126.6…

mini_blackrock_data |> 
  select(is_esg, name, net_assets_usd_mn)

# A tibble: 10 × 3
   is_esg       name                                   net_assets_usd_mn
   <chr>        <chr>                                              <dbl>
 1 ESG Fund     iShares ESG Aware MSCI USA ETF                    22377.
 2 ESG Fund     iShares ESG Aware MSCI EAFE ETF                    6426.
 3 ESG Fund     iShares Global Clean Energy ETF                    5628.
 4 ESG Fund     iShares ESG Aware MSCI EM ETF                      4234.
 5 ESG Fund     iShares MSCI KLD 400 Social ETF                    3689.
 6 Regular Fund iShares Core S&P 500 ETF                         297663.
 7 Regular Fund iShares Core MSCI EAFE ETF                        84222.
 8 Regular Fund iShares Core U.S. Aggregate Bond ETF              82344.
 9 Regular Fund iShares Core S&P Small-Cap ETF                    66533.
10 Regular Fund iShares Core MSCI Emerging Markets ETF            64920.

mini_blackrock_data |> 
  select(contains("asset"))

# A tibble: 10 × 3
   asset_class  sub_asset_class net_assets_usd_mn
   <chr>        <chr>                       <dbl>
 1 Equity       Large/Mid Cap              22377.
 2 Equity       Large/Mid Cap               6426.
 3 Equity       All Cap                     5628.
 4 Equity       Large/Mid Cap               4234.
 5 Equity       Large/Mid Cap               3689.
 6 Equity       Large Cap                 297663.
 7 Equity       All Cap                    84222.
 8 Fixed Income Multi Sectors              82344.
 9 Equity       Small Cap                  66533.
10 Equity       All Cap                    64920.

mini_blackrock_data |>
  # note that it uses `==` not `=`
  filter(is_esg == "ESG Fund")

# A tibble: 5 × 9
  is_esg   ticker name            asset…¹ sub_a…² region incep…³ net_a…⁴ co2_i…⁵
  <chr>    <chr>  <chr>           <chr>   <chr>   <chr>  <chr>     <dbl>   <dbl>
1 ESG Fund ESGU   iShares ESG Aw… Equity  Large/… North… 12/1/16  22377.   104. 
2 ESG Fund ESGD   iShares ESG Aw… Equity  Large/… Global 6/28/16   6426.   104. 
3 ESG Fund ICLN   iShares Global… Equity  All Cap Global 6/24/08   5628.   266. 
4 ESG Fund ESGE   iShares ESG Aw… Equity  Large/… Global 6/28/16   4234.   168. 
5 ESG Fund DSI    iShares MSCI K… Equity  Large/… North… 11/14/…   3689.    72.7
# … with abbreviated variable names ¹​asset_class, ²​sub_asset_class,
#   ³​incept_date, ⁴​net_assets_usd_mn, ⁵​co2_intensity

mini_blackrock_data |>
  # column name goes on the left
  filter(net_assets_usd_mn > 10000)

# A tibble: 6 × 9
  is_esg       ticker name        asset…¹ sub_a…² region incep…³ net_a…⁴ co2_i…⁵
  <chr>        <chr>  <chr>       <chr>   <chr>   <chr>  <chr>     <dbl>   <dbl>
1 ESG Fund     ESGU   iShares ES… Equity  Large/… North… 12/1/16  22377.    104.
2 Regular Fund IVV    iShares Co… Equity  Large … North… 5/15/00 297663.    148.
3 Regular Fund IEFA   iShares Co… Equity  All Cap Global 10/18/…  84222.    127.
4 Regular Fund AGG    iShares Co… Fixed … Multi … North… 9/22/03  82344.    283.
5 Regular Fund IJR    iShares Co… Equity  Small … North… 5/22/00  66533.    133.
6 Regular Fund IEMG   iShares Co… Equity  All Cap Global 10/18/…  64920.    369.
# … with abbreviated variable names ¹​asset_class, ²​sub_asset_class,
#   ³​incept_date, ⁴​net_assets_usd_mn, ⁵​co2_intensity

mini_blackrock_data |>
  # column name goes on the left
  filter(net_assets_usd_mn < 10000)

# A tibble: 4 × 9
  is_esg   ticker name            asset…¹ sub_a…² region incep…³ net_a…⁴ co2_i…⁵
  <chr>    <chr>  <chr>           <chr>   <chr>   <chr>  <chr>     <dbl>   <dbl>
1 ESG Fund ESGD   iShares ESG Aw… Equity  Large/… Global 6/28/16   6426.   104. 
2 ESG Fund ICLN   iShares Global… Equity  All Cap Global 6/24/08   5628.   266. 
3 ESG Fund ESGE   iShares ESG Aw… Equity  Large/… Global 6/28/16   4234.   168. 
4 ESG Fund DSI    iShares MSCI K… Equity  Large/… North… 11/14/…   3689.    72.7
# … with abbreviated variable names ¹​asset_class, ²​sub_asset_class,
#   ³​incept_date, ⁴​net_assets_usd_mn, ⁵​co2_intensity

mini_blackrock_data |> 
  filter(ticker %in% c("ESGU", "IVV", "DSI"))

# A tibble: 3 × 9
  is_esg       ticker name        asset…¹ sub_a…² region incep…³ net_a…⁴ co2_i…⁵
  <chr>        <chr>  <chr>       <chr>   <chr>   <chr>  <chr>     <dbl>   <dbl>
1 ESG Fund     ESGU   iShares ES… Equity  Large/… North… 12/1/16  22377.   104. 
2 ESG Fund     DSI    iShares MS… Equity  Large/… North… 11/14/…   3689.    72.7
3 Regular Fund IVV    iShares Co… Equity  Large … North… 5/15/00 297663.   148. 
# … with abbreviated variable names ¹​asset_class, ²​sub_asset_class,
#   ³​incept_date, ⁴​net_assets_usd_mn, ⁵​co2_intensity

tickers_i_want <- c("ESGU", "IVV", "DSI")

mini_blackrock_data |> 
  filter(ticker %in% tickers_i_want)

# A tibble: 3 × 9
  is_esg       ticker name        asset…¹ sub_a…² region incep…³ net_a…⁴ co2_i…⁵
  <chr>        <chr>  <chr>       <chr>   <chr>   <chr>  <chr>     <dbl>   <dbl>
1 ESG Fund     ESGU   iShares ES… Equity  Large/… North… 12/1/16  22377.   104. 
2 ESG Fund     DSI    iShares MS… Equity  Large/… North… 11/14/…   3689.    72.7
3 Regular Fund IVV    iShares Co… Equity  Large … North… 5/15/00 297663.   148. 
# … with abbreviated variable names ¹​asset_class, ²​sub_asset_class,
#   ³​incept_date, ⁴​net_assets_usd_mn, ⁵​co2_intensity

mini_blackrock_data |> 
  #select the columns we want
  select(name, is_esg, incept_date) 

# A tibble: 10 × 3
   name                                   is_esg       incept_date
   <chr>                                  <chr>        <chr>      
 1 iShares ESG Aware MSCI USA ETF         ESG Fund     12/1/16    
 2 iShares ESG Aware MSCI EAFE ETF        ESG Fund     6/28/16    
 3 iShares Global Clean Energy ETF        ESG Fund     6/24/08    
 4 iShares ESG Aware MSCI EM ETF          ESG Fund     6/28/16    
 5 iShares MSCI KLD 400 Social ETF        ESG Fund     11/14/06   
 6 iShares Core S&P 500 ETF               Regular Fund 5/15/00    
 7 iShares Core MSCI EAFE ETF             Regular Fund 10/18/12   
 8 iShares Core U.S. Aggregate Bond ETF   Regular Fund 9/22/03    
 9 iShares Core S&P Small-Cap ETF         Regular Fund 5/22/00    
10 iShares Core MSCI Emerging Markets ETF Regular Fund 10/18/12   

mini_blackrock_data |> 
  #select the columns we want
  select(name, is_esg, incept_date) |> 
  # use mdy() from the lubridate package to turn the character string into a date object
  mutate(incept_date = lubridate::mdy(incept_date))

# A tibble: 10 × 3
   name                                   is_esg       incept_date
   <chr>                                  <chr>        <date>     
 1 iShares ESG Aware MSCI USA ETF         ESG Fund     2016-12-01 
 2 iShares ESG Aware MSCI EAFE ETF        ESG Fund     2016-06-28 
 3 iShares Global Clean Energy ETF        ESG Fund     2008-06-24 
 4 iShares ESG Aware MSCI EM ETF          ESG Fund     2016-06-28 
 5 iShares MSCI KLD 400 Social ETF        ESG Fund     2006-11-14 
 6 iShares Core S&P 500 ETF               Regular Fund 2000-05-15 
 7 iShares Core MSCI EAFE ETF             Regular Fund 2012-10-18 
 8 iShares Core U.S. Aggregate Bond ETF   Regular Fund 2003-09-22 
 9 iShares Core S&P Small-Cap ETF         Regular Fund 2000-05-22 
10 iShares Core MSCI Emerging Markets ETF Regular Fund 2012-10-18 

mini_blackrock_data |> 
  #select the columns we want
  select(name, is_esg, incept_date) |> 
  # use mdy() from the lubridate package to turn the character string into a date object
  mutate(incept_date = lubridate::mdy(incept_date),
         # extract the year from the date
         incept_year = lubridate::year(incept_date),
         # calculate how many years since the fund was launched.
         years_since_incept = lubridate::interval(incept_date, Sys.Date())/lubridate::years(1))

# A tibble: 10 × 5
   name                                   is_esg      incept_d…¹ incep…² years…³
   <chr>                                  <chr>       <date>       <dbl>   <dbl>
 1 iShares ESG Aware MSCI USA ETF         ESG Fund    2016-12-01    2016    6.18
 2 iShares ESG Aware MSCI EAFE ETF        ESG Fund    2016-06-28    2016    6.61
 3 iShares Global Clean Energy ETF        ESG Fund    2008-06-24    2008   14.6 
 4 iShares ESG Aware MSCI EM ETF          ESG Fund    2016-06-28    2016    6.61
 5 iShares MSCI KLD 400 Social ETF        ESG Fund    2006-11-14    2006   16.2 
 6 iShares Core S&P 500 ETF               Regular Fu… 2000-05-15    2000   22.7 
 7 iShares Core MSCI EAFE ETF             Regular Fu… 2012-10-18    2012   10.3 
 8 iShares Core U.S. Aggregate Bond ETF   Regular Fu… 2003-09-22    2003   19.4 
 9 iShares Core S&P Small-Cap ETF         Regular Fu… 2000-05-22    2000   22.7 
10 iShares Core MSCI Emerging Markets ETF Regular Fu… 2012-10-18    2012   10.3 
# … with abbreviated variable names ¹​incept_date, ²​incept_year,
#   ³​years_since_incept

mini_blackrock_data |> 
  arrange(co2_intensity)

# A tibble: 10 × 9
   is_esg       ticker name       asset…¹ sub_a…² region incep…³ net_a…⁴ co2_i…⁵
   <chr>        <chr>  <chr>      <chr>   <chr>   <chr>  <chr>     <dbl>   <dbl>
 1 ESG Fund     DSI    iShares M… Equity  Large/… North… 11/14/…   3689.    72.7
 2 ESG Fund     ESGU   iShares E… Equity  Large/… North… 12/1/16  22377.   104. 
 3 ESG Fund     ESGD   iShares E… Equity  Large/… Global 6/28/16   6426.   104. 
 4 Regular Fund IEFA   iShares C… Equity  All Cap Global 10/18/…  84222.   127. 
 5 Regular Fund IJR    iShares C… Equity  Small … North… 5/22/00  66533.   133. 
 6 Regular Fund IVV    iShares C… Equity  Large … North… 5/15/00 297663.   148. 
 7 ESG Fund     ESGE   iShares E… Equity  Large/… Global 6/28/16   4234.   168. 
 8 ESG Fund     ICLN   iShares G… Equity  All Cap Global 6/24/08   5628.   266. 
 9 Regular Fund AGG    iShares C… Fixed … Multi … North… 9/22/03  82344.   283. 
10 Regular Fund IEMG   iShares C… Equity  All Cap Global 10/18/…  64920.   369. 
# … with abbreviated variable names ¹​asset_class, ²​sub_asset_class,
#   ³​incept_date, ⁴​net_assets_usd_mn, ⁵​co2_intensity

mini_blackrock_data |> 
  arrange(co2_intensity |> desc())

# A tibble: 10 × 9
   is_esg       ticker name       asset…¹ sub_a…² region incep…³ net_a…⁴ co2_i…⁵
   <chr>        <chr>  <chr>      <chr>   <chr>   <chr>  <chr>     <dbl>   <dbl>
 1 Regular Fund IEMG   iShares C… Equity  All Cap Global 10/18/…  64920.   369. 
 2 Regular Fund AGG    iShares C… Fixed … Multi … North… 9/22/03  82344.   283. 
 3 ESG Fund     ICLN   iShares G… Equity  All Cap Global 6/24/08   5628.   266. 
 4 ESG Fund     ESGE   iShares E… Equity  Large/… Global 6/28/16   4234.   168. 
 5 Regular Fund IVV    iShares C… Equity  Large … North… 5/15/00 297663.   148. 
 6 Regular Fund IJR    iShares C… Equity  Small … North… 5/22/00  66533.   133. 
 7 Regular Fund IEFA   iShares C… Equity  All Cap Global 10/18/…  84222.   127. 
 8 ESG Fund     ESGD   iShares E… Equity  Large/… Global 6/28/16   6426.   104. 
 9 ESG Fund     ESGU   iShares E… Equity  Large/… North… 12/1/16  22377.   104. 
10 ESG Fund     DSI    iShares M… Equity  Large/… North… 11/14/…   3689.    72.7
# … with abbreviated variable names ¹​asset_class, ²​sub_asset_class,
#   ³​incept_date, ⁴​net_assets_usd_mn, ⁵​co2_intensity

mini_blackrock_data |> 
  summarize(sum_assets_mn = sum(net_assets_usd_mn),
            avg_assets_mn = mean(net_assets_usd_mn),
            median_assets_mn=median(net_assets_usd_mn))

# A tibble: 1 × 3
  sum_assets_mn avg_assets_mn median_assets_mn
          <dbl>         <dbl>            <dbl>
1       638036.        63804.           43648.

mini_blackrock_data |> 
  group_by(is_esg) |> 
  summarize(sum_assets_mn = sum(net_assets_usd_mn),
            avg_assets_mn = mean(net_assets_usd_mn))

# A tibble: 2 × 3
  is_esg       sum_assets_mn avg_assets_mn
  <chr>                <dbl>         <dbl>
1 ESG Fund            42353.         8471.
2 Regular Fund       595683.       119137.

mini_blackrock_data |>
  group_by(asset_class) |>
  summarize(avg_co2_intensity = mean (co2_intensity))

# A tibble: 2 × 2
  asset_class  avg_co2_intensity
  <chr>                    <dbl>
1 Equity                    166.
2 Fixed Income              283.

install.packages("ggplot2")

Warning: package 'ggplot2' is in use and will not be installed

library(ggplot2)

# compare ETF in different market by their net assets values, and to see whether these market has ESG fund of regular fund
ggplot(data = blackrock_etf_data) + 
  geom_col(mapping = aes(x = market, y = net_assets_usd_mn, color = is_esg,fill="pink"))

# showing the fund's Co2 level in different regions
ggplot(data = blackrock_etf_data) + 
  geom_point(mapping = aes(x = region, y = msci_weighted_average_carbon_intensity_tons_co2e_m_sales, color = is_esg), size =3,shape=1)

Warning: Removed 62 rows containing missing values (`geom_point()`).

#categorize ESG fund and regular Fund according to the region and their sub_asset_class, ranked by CO2_intensity
ggplot(data = mini_blackrock_data) + 
  geom_point(mapping = aes(x = region, y = co2_intensity, color=is_esg, size = 5))+
  facet_grid(sub_asset_class ~ region)