DataOnDemandProvider#

class DataOnDemandProvider(token, tickers, start=datetime.datetime(2016, 1, 1, 0, 0), end=datetime.datetime(2016, 1, 30, 0, 0), verify=None)[source]#

Bases: BaseDataProvider

NASDAQ Data on Demand data provider.

Please see: https://qiskit-community.github.io/qiskit-finance/tutorials/11_time_series.html for instructions on use, which involve obtaining a NASDAQ DOD access token.

Parameters:

token (str) – data on demand access token
tickers (str | List[str]) – tickers
start (datetime) – first data point
end (datetime) – last data point precedes this date
verify (str | bool | None) – if verify is None, certify certificates will be used (default); if this is False, no certificates will be checked; if this is a string, it should be pointing to a certificate for the HTTPS connection to NASDAQ (dataondemand.nasdaq.com), either in the form of a CA_BUNDLE file or a directory wherein to look.

Methods

get_coordinates()#

Returns random coordinates for visualisation purposes.

Return type:: Tuple[ndarray, ndarray]

get_covariance_matrix()#

Returns the covariance matrix.

Returns:: an asset-to-asset covariance matrix.
Raises:: QiskitFinanceError – no data loaded
Return type:: ndarray

get_mean_vector()#

Returns a vector containing the mean value of each asset.

Returns:: a per-asset mean vector.
Raises:: QiskitFinanceError – no data loaded
Return type:: ndarray

get_period_return_covariance_matrix()#

Returns a vector containing the mean value of each asset.

Returns:: a per-asset mean vector.
Raises:: QiskitFinanceError – no data loaded
Return type:: ndarray

get_period_return_mean_vector()#

Returns a vector containing the mean value of each asset.

Returns:: a per-asset mean vector.
Raises:: QiskitFinanceError – no data loaded
Return type:: ndarray

get_similarity_matrix()#

Returns time-series similarity matrix computed using dynamic time warping.

Returns:: an asset-to-asset similarity matrix.
Raises:: QiskitFinanceError – no data loaded
Return type:: ndarray

run()[source]#

Loads data, thus enabling get_similarity_matrix and get_covariance_matrix methods in the base class.