Analyst Cheat Sheet

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Analyst Cheat Sheet

Goal

This guide covers the basic workflow:

deal_spec() -> analyze_deal() -> summary() -> deal_cashflows()

The 5 functions to know

deal_spec(): define the deal
debt_terms(): define the debt
analyze_deal(): run the model
summary(): read key metrics
deal_cashflows(): extract tables

The 10 variables that matter most

Variable	Meaning
`price`	all-in acquisition price
`horizon_years`	holding period
`entry_yield`	entry cap rate
`noi_y1`	year-1 NOI if already known
`rent_sqm`	rent per sqm
`area_sqm`	lettable area
`vacancy_rate`	average vacancy
`discount_rate`	discount rate
`ltv`	initial leverage
`rate`	debt interest rate

Use exactly one income mode:

entry_yield
or noi_y1
or rent_sqm + area_sqm

Quick Start

library(cre.dcf)

deal <- deal_spec(
  price = 10e6,
  entry_yield = 0.055,
  horizon_years = 10,
  debt = debt_terms(
    ltv = 0.60,
    rate = 0.045,
    type = "bullet"
  )
)

res <- analyze_deal(deal)

summary(res)
#> # A tibble: 1 × 25
#>   income_mode purchase_year  price horizon_years area_sqm price_per_sqm rent_sqm
#>   <chr>               <dbl>  <dbl>         <int>    <dbl>         <dbl>    <dbl>
#> 1 entry_yield          2026    1e7            10       NA            NA       NA
#> # ℹ 18 more variables: vacancy_rate <dbl>, opex_sqm <dbl>,
#> #   gross_potential_rent_y1 <dbl>, gei_y1 <dbl>, noi_y1 <dbl>, pbtcf_y1 <dbl>,
#> #   entry_yield <dbl>, index_rate <dbl>, discount_rate <dbl>, debt_type <chr>,
#> #   debt_ltv <dbl>, debt_rate <dbl>, irr_project <dbl>, irr_equity <dbl>,
#> #   dscr_min <dbl>, ltv_max_forward <dbl>, ops_share <dbl>, tv_share <dbl>

Typical Workflow

1. Define the deal

deal <- deal_spec(
  price = 12e6,
  rent_sqm = 240,
  area_sqm = 4000,
  vacancy_rate = 0.08,
  opex_sqm = 15,
  horizon_years = 7,
  discount_rate = 0.08,
  debt = debt_terms(
    ltv = 0.55,
    rate = 0.043,
    type = "amort",
    maturity = 7
  )
)

deal
#> <cre_deal_spec>
#> price_di: 12000000.00
#> asset: 4,000.00 sqm | rent 240.00/sqm | vacancy 8.0% | opex 15.00/sqm | price 3,000.00/sqm
#> year-1: GEI 883,200.00 | NOI 823,200.00 | PBTCF 823,200.00 | entry yield 6.86%
#> horizon: 7 years
#> income mode: 4000.00 sqm x 240.00 rent/sqm
#> growth/discount: indexation 2.00% | discount rate 8.00%
#> debt: amort, LTV 55.0%, rate 4.30%

2. Run the deal

res <- analyze_deal(deal)
res
#> <cre_deal_result>
#> # A tibble: 1 × 25
#>   income_mode purchase_year  price horizon_years area_sqm price_per_sqm rent_sqm
#>   <chr>               <dbl>  <dbl>         <int>    <dbl>         <dbl>    <dbl>
#> 1 rent_roll            2026 1.20e7             7     4000          3000      240
#> # ℹ 18 more variables: vacancy_rate <dbl>, opex_sqm <dbl>,
#> #   gross_potential_rent_y1 <dbl>, gei_y1 <dbl>, noi_y1 <dbl>, pbtcf_y1 <dbl>,
#> #   entry_yield <dbl>, index_rate <dbl>, discount_rate <dbl>, debt_type <chr>,
#> #   debt_ltv <dbl>, debt_rate <dbl>, irr_project <dbl>, irr_equity <dbl>,
#> #   dscr_min <dbl>, ltv_max_forward <dbl>, ops_share <dbl>, tv_share <dbl>

3. Read the key metrics

summary(res)
#> # A tibble: 1 × 25
#>   income_mode purchase_year  price horizon_years area_sqm price_per_sqm rent_sqm
#>   <chr>               <dbl>  <dbl>         <int>    <dbl>         <dbl>    <dbl>
#> 1 rent_roll            2026 1.20e7             7     4000          3000      240
#> # ℹ 18 more variables: vacancy_rate <dbl>, opex_sqm <dbl>,
#> #   gross_potential_rent_y1 <dbl>, gei_y1 <dbl>, noi_y1 <dbl>, pbtcf_y1 <dbl>,
#> #   entry_yield <dbl>, index_rate <dbl>, discount_rate <dbl>, debt_type <chr>,
#> #   debt_ltv <dbl>, debt_rate <dbl>, irr_project <dbl>, irr_equity <dbl>,
#> #   dscr_min <dbl>, ltv_max_forward <dbl>, ops_share <dbl>, tv_share <dbl>

Key fields:

irr_project: project return before leverage
irr_equity: return to equity
dscr_min: minimum debt-service coverage ratio
ltv_max_forward: maximum forward LTV
ops_share: share of present value coming from operating cash flows
tv_share: share of present value coming from terminal value

4. Extract the tables

deal_cashflows(res, "comparison")
#> # A tibble: 3 × 9
#>   scenario    irr_equity npv_equity irr_project npv_project min_dscr
#>   <chr>            <dbl>      <dbl>       <dbl>       <dbl>    <dbl>
#> 1 all_equity       0.100   1353712.       0.100    1353712.   NA    
#> 2 debt_bullet      0.161   2625108.       0.100    1353712.    3.11 
#> 3 debt_amort       0.130   2165030.       0.100    1353712.    0.794
#> # ℹ 3 more variables: max_ltv_forward <dbl>, ops_share <dbl>, tv_share <dbl>
deal_cashflows(res, "full")
#> # A tibble: 8 × 36
#>    year      gei     noi   pbtcf net_operating_income capex  opex free_cash_flow
#>   <int>    <dbl>   <dbl>   <dbl>                <dbl> <dbl> <dbl>          <dbl>
#> 1     0       0       0       0                    0      0    0      -12000000 
#> 2     1  888000  883200  883200               888000      0 4800         883200 
#> 3     2  905760  900864  900864               905760      0 4896         900864 
#> 4     3  923875. 918881. 918881.              923875.     0 4994.        918881.
#> 5     4  942353. 937259. 937259.              942353.     0 5094.        937259.
#> 6     5  961200. 956004. 956004.              961200.     0 5196.        956004.
#> 7     6  980424. 975124. 975124.              980424.     0 5300.        975124.
#> 8     7 1000032. 994627. 994627.             1000032.     0 5406.      15561702.
#> # ℹ 28 more variables: sale_proceeds <dbl>, discount_factor <dbl>,
#> #   discounted_cash_flow <dbl>, asset_value <dbl>, acquisition_price <dbl>,
#> #   discounted_cf <dbl>, debt_draw <dbl>, interest <dbl>, amortization <dbl>,
#> #   payment <dbl>, arrangement_fee <dbl>, outstanding_debt <dbl>,
#> #   loan_init <dbl>, df <dbl>, cf_pre_debt <dbl>, cf_post_debt <dbl>,
#> #   equity_flow <dbl>, equity_disc <dbl>, noi_fwd <dbl>, value_forward <dbl>,
#> #   dscr <dbl>, interest_cover_ratio <dbl>, debt_yield_init <dbl>, …

Use:

"full" for the merged operating and debt cash flows
"all_equity" for the unlevered table
"leveraged" for the equity cash-flow view
"comparison" for the summary by financing structure

Three Common Input Styles

Entry yield known

deal_spec(price = 10e6, entry_yield = 0.055)
#> <cre_deal_spec>
#> price_di: 10000000.00
#> asset: aggregated inputs (entry_yield)
#> year-1: GEI NA | NOI 550,000.00 | PBTCF 550,000.00 | entry yield 5.50%
#> horizon: 10 years
#> income mode: entry yield 5.50%
#> growth/discount: indexation 2.00% | discount rate 8.00%
#> debt: bullet, LTV 55.0%, rate 4.50%

NOI already known

deal_spec(price = 10e6, noi_y1 = 550000)
#> <cre_deal_spec>
#> price_di: 10000000.00
#> asset: aggregated inputs (noi_y1)
#> year-1: GEI 550,000.00 | NOI 550,000.00 | PBTCF 550,000.00 | entry yield 5.50%
#> horizon: 10 years
#> income mode: NOI_y1 550000.00
#> growth/discount: indexation 2.00% | discount rate 8.00%
#> debt: bullet, LTV 55.0%, rate 4.50%

Rent roll style input

deal_spec(
  price = 10e6,
  rent_sqm = 220,
  area_sqm = 3000,
  vacancy_rate = 0.05,
  opex_sqm = 12
)
#> <cre_deal_spec>
#> price_di: 10000000.00
#> asset: 3,000.00 sqm | rent 220.00/sqm | vacancy 5.0% | opex 12.00/sqm | price 3,333.33/sqm
#> year-1: GEI 627,000.00 | NOI 591,000.00 | PBTCF 591,000.00 | entry yield 5.91%
#> horizon: 10 years
#> income mode: 3000.00 sqm x 220.00 rent/sqm
#> growth/discount: indexation 2.00% | discount rate 8.00%
#> debt: bullet, LTV 55.0%, rate 4.50%

Common Mistakes

Do not provide more than one income mode.
price is always the all-in acquisition price in the simplified API.
If you use rent_sqm + area_sqm, the package derives year-1 NOI for you.
If you want a quick first pass, start with debt_terms() defaults and only change ltv, rate, and type.

When to move to the advanced API

Use the advanced API only if you need:

YAML-based workflows,
explicit lease-event structures,
direct access to normalization helpers,
custom scenario tooling built around run_case().

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They may not be fully stable and should be used with caution. We make no claims about them.
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