Fake financial portfolio.
Demo datasets are synthetic because most financial data is strictly private; they help to demonstrate and test the implementation in R of 'PACTA' (https://2degrees-investing.org/resource/pacta/).
Definitions
fi_type(character): Financial instrument name or asset class.flag_project_finance_loan(character): Project finance flag denoting whether a loan is given out to a particular asset or not.id_direct_loantaker(character): Borrower identifier unique to each borrower/sector combination in loanbook.id_intermediate_parent_n(character): Optional input: id of the n-th intermediate parent company within the company structure that can be used for more granular mapping than the ultimate parent. Smaller values of n are closer to the direct_loantaker.id_loan(character): Unique loan identifier.id_ultimate_parent(character): Ultimate parent identifier unique to each ultimate parent/sector combination.isin_direct_loantaker(logical): Optional input: providing the isin identifier of the direct loan taker to improve the matching coverage.lei_direct_loantaker(logical): Optional input: providing the lei (legal entity identifier) of the direct loan taker to improve the matching coverage.loan_size_credit_limit(double): Total credit limit or exposure at default.loan_size_credit_limit_currency(character): Currency corresponding to credit limit.loan_size_outstanding(double): Amount drawn by borrower from total credit limit.loan_size_outstanding_currency(character): Currency corresponding to outstandings.name_direct_loantaker(character): Name of the company directly taking the loan.name_intermediate_parent_n(character): Optional input: name of intermediate parent company within the company structure that can be used for more granular mapping than the ultimate parent. Smaller values of n are closer to the direct_loantaker.name_project(logical): Required input for loans with the flag_project_finance_loan = TRUE: Name of the project being financed.name_ultimate_parent(character): Name of the ultimate parent company to which the borrower belongs. Can be the same as borrower.sector_classification_direct_loantaker(double): Sector classification code of the direct loantaker.sector_classification_input_type(character): Flag identifying if the sector classification code or character description is used.sector_classification_system(character): Name of the sector classification standard being used.
See also
Other demo datasets:
abcd_demo,
co2_intensity_scenario_demo,
overwrite_demo,
region_isos_demo,
scenario_demo_2020
Examples
head(loanbook_demo)
#> # A tibble: 6 × 19
#> id_loan id_direct_loantaker name_direct_loa… id_intermediate… name_intermedia…
#> <chr> <chr> <chr> <chr> <chr>
#> 1 L1 C294 Yuamen Xinneng … NA NA
#> 2 L2 C293 Yuamen Changyua… NA NA
#> 3 L3 C292 Yuama Ethanol L… IP5 Yuama Inc.
#> 4 L4 C299 Yudaksel Holdin… NA NA
#> 5 L5 C305 Yukon Energy Co… NA NA
#> 6 L6 C304 Yukon Developme… NA NA
#> # … with 14 more variables: id_ultimate_parent <chr>,
#> # name_ultimate_parent <chr>, loan_size_outstanding <dbl>,
#> # loan_size_outstanding_currency <chr>, loan_size_credit_limit <dbl>,
#> # loan_size_credit_limit_currency <chr>, sector_classification_system <chr>,
#> # sector_classification_input_type <chr>,
#> # sector_classification_direct_loantaker <dbl>, fi_type <chr>,
#> # flag_project_finance_loan <chr>, name_project <lgl>, …