Covariance

qcs.get_covariance(context, xtickers, ytickers=None, currency=None, unit='TKR')

Get the covariance matrix and levels of the allocation snapshot.

Parameters:

Name	Type	Description	Default
context	Context	The context in which the covariance matrix is calculated.	required
xtickers	List[str]	The tickers for the rows of the covariance matrix.	required
ytickers	List[str] | None = None	The tickers for the columns of the covariance matrix. If not provided, defaults to xtickers.	None
currency	CurrencyType | None	The currency in which tickers are computed. If None, then tickers are not converted to a common currency	None
unit	Literal["TKR", "LVL", "MKT", "MAV"] = "TKR"	The unit of the computation	'TKR'

Returns:

Type	Description
CovarianceOutput	An instance of CovarianceOutput class with the following properties: - "covariance": A DataFrame representing the covariance matrix. - "meta_info": A DataFrame representing the meta information of the covariance matrix. - "context": A dict representing the context of the covariance risk computation.

Examples:

>>> context = Context(date=date.today(), horizon="1d", local_db=my_local_db)
>>> covariance_output = qcs.get_covariance(
...     context, unit="TKR", currency="USD", xtickers=["EUR", "GBP"]
... )
>>> print(covariance_output.covariance)
     EUR       GBP
EUR  0.000553  0.000672
GBP  0.000672  0.001071
>>> print(covariance_output.meta_info)
     label               level  currency  variance
EUR  EUR to USD FX rate  1.0    USD       0.000553
GBP  GBP to USD FX rate  1.0    USD       0.001071
>>> print(covariance_output.context)
{'date': '2023-10-19', 'horizon': '1d', 'annualization_factor': 15.8745079}