2.3.2 infra_equity_comparable

Purpose
Performs a comparable computation for private infrastructure equities. This involves finding data points which have similar TICCS classifications and factor values, and averaging the metric values.

Parameters

• metric (string, required):
  The metric for which the comparable has to be evaluated.
  Supported metrics include: "EvToEbitda", "Irr", "PriceToBook", "PriceToSales", "Premia", "RevenueGrowth", "Wacc".

• currency (string, optional):
  The currency of monetary factor inputs such as size.
  Acceptable currencies include: "AUD", "CAD", "EUR", "GBP", "JPY", "LCU", "USD".

• age_in_months (int, optional):
  The age of the company in months, and the value should be between 24 and 240. Note that the computation extends 6-month before and after the specified age. For instance, 24 would indicate inclusion of companies of age between 18-month and 30-month.
  If this parameter is set, end_date and window_in_years will be ignored.

• end_date (date, optional):
  The maximum date of the comparable dataset.

• window_in_years (int, optional):
  The window in years of the comparable dataset. The minimum date of the dataset is calculated as end_date - window_in_years.

• industrial_activities (list of strings, optional):
  List of industrial activity TICCS codes. See https://docs.sipametrics.com/docs/industrial-activities for the complete definitions.
  Acceptable values include: "IC10", "IC2010", "IC302010".

• business_risk (string, optional):
  Business risk TICCS code. See https://docs.sipametrics.com/docs/business-risk for the complete definitions.
  Supported values include: "BR1", "BR2", "BR3".

• corporate_structure (string, optional):
  Corporate structure TICCS code. See https://docs.sipametrics.com/docs/corporate-structure for the complete definitions.
  Supported values include: "CS1", "CS2".

• countries (list of strings, optional):
  List of country ISO codes. Values can be obtained by referring to https://docs.sipametrics.com/docs/inframetrics-country-codes.

• size (float or string, optional):
  Total assets or size of the company. Represented either as an absolute value in millions of the specified currency (e.g., “USD”, “EUR”) or as a quintile value.
  Acceptable numerical values: 5.6 (represents 5.6 million).
  Supported quintile values include: "Q1", "Q2", "Q3", "Q4", "Q5".

• leverage (float or string, optional):
  Total senior liabilities over total assets. Represented either as a percentage (e.g., "50%") or as a quintile value.
  Acceptable numerical values: 1 to 100 (without the % symbol).
  Supported quintile values include: "Q1", "Q2", "Q3", "Q4", "Q5".

• profitability (float or string, optional):
  Return on assets or profitability metric. Represented either as a percentage (e.g., "15%") or as a quintile value.
  Acceptable numerical values: 1 to 100 (without the % symbol).
  Supported quintile values include: "Q1", "Q2", "Q3", "Q4", "Q5".

• investment (float or string, optional):
  Capital expenditures over total assets. Represented either as a percentage (e.g., "10%") or as a quintile value.
  Acceptable numerical values: 1 to 100 (without the % symbol).
  Supported quintile values include: "Q1", "Q2", "Q3", "Q4", "Q5".

• time_to_maturity: (float or string, optional)
  Years until maturity. Represented as either a numerical value (e.g., "10 years") or as a bucket.
  Acceptable numerical values: Any, e.g. 10 (represents 10 years).
  Supported bucket values include:

  • "T1": 0-5 (years)

  • "T2": 5-10 (years)

  • "T3": 10-15 (years)

  • "T4": 15-20 (years)

  • "T5": 20+ (years)

Example 1: Quintile

response = await service.infra_equity_comparable(
    metric="EvToEbitda",
    # currency="",
    # age_in_months=None,
    end_date=datetime.date(2023, 7, 31),
    window_in_years=2,
    industrial_activities=["IC10"],
    business_risk="BR1",
    corporate_structure="CS1",
    countries=["AUS", "NZL"],
    size="Q1",
    leverage="Q1",
    profitability="Q1",
    investment="Q1",
    time_to_maturity="T2",
)

#Sample Response
#{
#    "data": {
#        "results": {
#            "mean": 15.981798553660548,
#            "q1": 5.981449640866844,
#            "median": 10.80715995763961,
#            "q3": 18.432610791417122,
#            "datumCount": 3922,
#            "companyCount": 211,
#            "min": 2.2721601980289723,
#            "max": 90.05322208506935
#        }
#    }
#}

Example 2: Absolute value

response = await service.infra_equity_comparable(
    metric="EvToEbitda",
    # currency="",
    # age_in_months=None,
    end_date=datetime.date(2023, 7, 31),
    window_in_years=2,
    # industrial_activities=None,
    # business_risk=None,
    # corporate_structure=None,
    # countries=None,
    size=50,
    leverage=54,
    profitability=0.2,
    investment=23,
    time_to_maturity=7,
)

#Sample Response
#{
#    "data": {
#        "results": {
#            "mean": 24.67669348532026,
#            "q1": 10.058913742758115,
#            "median": 21.274396186798203,
#            "q3": 35.01179726152446,
#            "datumCount": 869,
#            "companyCount": 76,
#            "min": 2.2721601980289723,
#            "max": 90.05322208506935
#        }
#    }
#}