Sample cash flows for interest theory examples

A small pedagogical dataset containing cash-flow scenarios for present value, future value, net present value, internal rate of return, equations of value, and cash-flow diagrams.

A small pedagogical dataset containing cash-flow scenarios for present value, future value, net present value, internal rate of return, equations of value, and cash-flow diagrams.

Usage

cash_flows_sample

cash_flows_sample

Format

A tibble with 19 rows and 5 variables:

scenario_id

Scenario identifier.

t

Payment time.

C

Cash-flow amount. Negative values represent outflows and positive values represent inflows.

cashflow_type

Type of cash flow.

description

Short description of the cash flow.

A tibble with 19 rows and 5 variables:

scenario_id

Scenario identifier.

t

Payment time.

C

Cash-flow amount. Negative values represent outflows and positive values represent inflows.

cashflow_type

Type of cash flow.

description

Short description of the cash flow.

Source

Synthetic pedagogical data created for tidyactuarial examples.

Synthetic pedagogical data created for tidyactuarial examples.

Details

This dataset uses the compact financial-actuarial notation used throughout tidyactuarial: t denotes time and C denotes the cash-flow amount at that time.

This dataset uses the compact financial-actuarial notation used throughout tidyactuarial: t denotes time and C denotes the cash-flow amount at that time.

Examples

data(cash_flows_sample)

cash_flows_sample |>
  dplyr::filter(scenario_id == "investment_project") |>
  dplyr::select(scenario_id, t, C, cashflow_type)
#> # A tibble: 6 × 4
#>   scenario_id            t      C cashflow_type     
#>   <chr>              <dbl>  <dbl> <chr>             
#> 1 investment_project     0 -10000 initial_investment
#> 2 investment_project     1   2500 inflow            
#> 3 investment_project     2   2800 inflow            
#> 4 investment_project     3   3200 inflow            
#> 5 investment_project     4   3500 inflow            
#> 6 investment_project     5   4000 inflow            

data(cash_flows_sample)

cash_flows_sample |>
  dplyr::filter(scenario_id == "investment_project") |>
  dplyr::select(scenario_id, t, C, cashflow_type)
#> # A tibble: 6 × 4
#>   scenario_id            t      C cashflow_type     
#>   <chr>              <dbl>  <dbl> <chr>             
#> 1 investment_project     0 -10000 initial_investment
#> 2 investment_project     1   2500 inflow            
#> 3 investment_project     2   2800 inflow            
#> 4 investment_project     3   3200 inflow            
#> 5 investment_project     4   3500 inflow            
#> 6 investment_project     5   4000 inflow