2.3.5 SIPAMETRICS - PRIVATE_EQUITY_COMPARABLE
Description: Perform a comparable computation for private equity. This involves finding datapoints which have similar PECCS classifications and factor values (the comparables dataset) and averaging the metric values.
Parameters:
metric (string, required):
The metric for which the comparable has to be evaluated. Options include:"priceToSales", "priceToEbitda", "priceToBook", "priceToEarnings", "evToSales", "evToEbitda", "totalReturns", "ebitdaToSales", "ebitToSales", "netIncomeToSales", "netDebtToAssets", "revenueGrowth", "dividendOverRevenue", "returnOnAssets", "returnOnEquity", "returnOnCapitalEmployed", "netOperatingIncome", "netDebtToEquity"
.currency (string, optional):
The currency of monetary factor inputs, such as size. Possible values include'USD', 'EUR', 'GBP'
.age_in_months (int, optional):
The age of the company in months. The comparable computation will keep companies within 6 months of this value. If age is set, endDate and windowInYears will be ignored.end_date (string, date format, required):
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 endDate - windowInYears.industrial_activites (array of strings, optional):
Comma-separated list of industrial activity PECCS codes. Possible values include"AC01", "AC02"
, etc.revenue_models (array of strings, optional):
Comma-separated list of revenue model PECCS codes. Possible values include"RM01", "RM02"
, etc.customer_models (array of strings, optional):
Comma-separated list of customer model PECCS codes. Possible values include"CM01", "CM02"
, etc.lifecycle_phases (array of strings, optional):
Comma-separated list of lifecycle phase PECCS codes. Possible values include"LP01", "LP02"
, etc.value_chain_types (array of strings, optional):
Comma-separated list of value chain type PECCS codes. Possible values include"VC01", "VC02"
, etc.countries (array of strings, optional):
Range of countries as three-letter ISO codes. Possible values can be obtained by calling countries.size: (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 value in millions: Enter any numerical value. eg. 5 represents 5 million
Acceptable quintile values include: "Q1", "Q2", "Q3", "Q4", "Q5".leverage: (string, optional)
Total senior liabilities over total assets. Represented either as a percentage (e.g., "50%") or as a quintile value.
Acceptable percentage values: range 1 to 100 only.
Acceptable quintile values include: "Q1", "Q2", "Q3", "Q4", "Q5".profits: (string, optional)
Return on assets or profitability metric. Represented either as a percentage (e.g., "15%") or as a quintile value.
Acceptable percentage values: range 1 to 100 only.
Acceptable quintile values include: "Q1", "Q2", "Q3", "Q4", "Q5".country_risk: (array of strings, optional):
Term spread. Specify 3-letter country ISOs or quintile (“Q1”, “Q2”, “Q3”, “Q4”, “Q5”)universe (string, optional):
Specifies the market universe. Possible values are"PEU"
for private equity universe and"MIU"
for market index universe.factor_weight (float, optional):
A decimal value between 0 and 1. At the extremes, 1 indicates that comparables are purely based on factors, while 0 indicates that comparables are purely based on PECCS. Values between 0 and 1 create a weighted average between the two.type (string, optional):
Determines how to aggregate the comparables dataset. Default is"mean"
. Other options include"mean", "median", "datumCount", "companyCount", "p25", "p75", "min", "max", "vol", "var97_5", "var99". Note: "vol", "var97_5", and "var99"
are only applicable for the "totalReturns" metric.intersect_peccs (boolean, optional):
Intersect or union the PECCS filters when doing the calculation. Default is
TRUE
.
Example 1: Quintile
response = await session.private_equity_comparable(
metric="PriceToSales",
currency="USD",
age_in_months=None,
end_date=date(2023, 10, 31),
window_in_years=2,
industrial_activities=None,
revenue_models=None,
customer_models=None,
lifecycle_phases=None,
value_chain_types=None,
countries=None,
size=None,
growth=None,
leverage="Q1",
profits=None,
country_risk=None,
universe="MIU",
factor_weight="1",
type="mean",
intersect_peccs=True,
)
Example 2: Absolute value
response = await session.private_equity_comparable(
metric="PriceToSales",
currency="USD",
age_in_months=None,
end_date=date(2022, 11, 30),
window_in_years=2,
industrial_activities=None,
revenue_models=None,
customer_models=None,
lifecycle_phases=None,
value_chain_types=None,
countries=None,
size=None,
growth="0.1",
leverage=None,
profits="0.2",
country_risk=None,
universe="MIU",
factor_weight="1",
type="mean",
intersect_peccs=True,
)