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Qiskit Finance is no longer maintained and this documentation is no longer updated. It is kept online for reference only, and the code it describes may not work with current versions of Qiskit. See the project repository for more information.

ExchangeDataProvider#

class ExchangeDataProvider(token, tickers, stockmarket=StockMarket.LONDON, start=datetime.datetime(2016, 1, 1, 0, 0), end=datetime.datetime(2016, 1, 30, 0, 0))[source]#

Bases: BaseDataProvider

Exchange 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 Data Link access token.

Parameters:

token (str) – Nasdaq Data Link access token
tickers (str | List[str]) – tickers
stockmarket (StockMarket) – LONDON, EURONEXT, or SINGAPORE
start (datetime) – first data point
end (datetime) – last data point precedes this date

Raises:

QiskitFinanceError – provider doesn’t support given stock market

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.