qiskit.finance.data_providers.DataOnDemandProvider
class DataOnDemandProvider(token, tickers, start=datetime.datetime(2016, 1, 1, 0, 0), end=datetime.datetime(2016, 1, 30, 0, 0), verify=None)
NASDAQ Data on Demand data provider.
Please see: https://github.com/Qiskit/qiskit-tutorials/blob/master/legacy_tutorials/aqua/finance/data_providers/time_series.ipynb for instructions on use, which involve obtaining a NASDAQ DOD access token.
Parameters
- token (
str) – data on demand access token - tickers (
Union[str,List[str]]) – tickers - start (
datetime) – first data point - end (
datetime) – last data point precedes this date - verify (
Union[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.
__init__
__init__(token, tickers, start=datetime.datetime(2016, 1, 1, 0, 0), end=datetime.datetime(2016, 1, 30, 0, 0), verify=None)
Parameters
- token (
str) – data on demand access token - tickers (
Union[str,List[str]]) – tickers - start (
datetime) – first data point - end (
datetime) – last data point precedes this date - verify (
Union[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
__init__(token, tickers[, start, end, verify]) | type tokenstr |
get_coordinates() | Returns random coordinates for visualisation purposes. |
get_covariance_matrix() | Returns the covariance matrix. |
get_mean_vector() | Returns a vector containing the mean value of each asset. |
get_period_return_covariance_matrix() | Returns a vector containing the mean value of each asset. |
get_period_return_mean_vector() | Returns a vector containing the mean value of each asset. |
get_similarity_matrix() | Returns time-series similarity matrix computed using dynamic time warping. |
run() | Loads data, thus enabling get_similarity_matrix and get_covariance_matrix methods in the base class. |
get_coordinates
get_coordinates()
Returns random coordinates for visualisation purposes.
Return type
Tuple[float, float]
get_covariance_matrix
get_covariance_matrix()
Returns the covariance matrix.
Return type
ndarray
Returns
an asset-to-asset covariance matrix.
Raises
QiskitFinanceError – no data loaded
get_mean_vector
get_mean_vector()
Returns a vector containing the mean value of each asset.
Return type
ndarray
Returns
a per-asset mean vector.
Raises
QiskitFinanceError – no data loaded
get_period_return_covariance_matrix
get_period_return_covariance_matrix()
Returns a vector containing the mean value of each asset.
Return type
ndarray
Returns
a per-asset mean vector.
Raises
QiskitFinanceError – no data loaded
get_period_return_mean_vector
get_period_return_mean_vector()
Returns a vector containing the mean value of each asset.
Return type
ndarray
Returns
a per-asset mean vector.
Raises
QiskitFinanceError – no data loaded
get_similarity_matrix
get_similarity_matrix()
Returns time-series similarity matrix computed using dynamic time warping.
Return type
ndarray
Returns
an asset-to-asset similarity matrix.
Raises
QiskitFinanceError – no data loaded
run
run()
Loads data, thus enabling get_similarity_matrix and get_covariance_matrix methods in the base class.
Return type
None