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://www.transitionmonitor.com/).
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_lo…¹ name_…² id_in…³ name_…⁴ id_ul…⁵ name_…⁶ loan_…⁷ loan_…⁸
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <chr>
#> 1 L1 C294 Yuamen… NA NA UP15 Alpine… 225625 EUR
#> 2 L2 C293 Yuamen… NA NA UP84 Eco Wa… 301721 EUR
#> 3 L3 C292 Yuama … IP5 Yuama … UP288 Univer… 410297 EUR
#> 4 L4 C299 Yudaks… NA NA UP54 China … 233049 EUR
#> 5 L5 C305 Yukon … NA NA UP104 Garlan… 406585 EUR
#> 6 L6 C304 Yukon … NA NA UP83 Earthp… 185721 EUR
#> # … with 10 more variables: 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>,
#> # lei_direct_loantaker <lgl>, isin_direct_loantaker <lgl>, and abbreviated
#> # variable names ¹id_direct_loantaker, ²name_direct_loantaker, …