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MacroEconomicFix

MacroEconomicFix#

class sigtech.framework.instruments.fixes.MacroEconomicFix

Baseclasses: HistoricalFrameworkObject

A class representing a macroeconomic fixing.

country: str
data_provider: str
property data_source_all

Data sources of the instrument.

description: str
property due_time

Required for parent class

Returns:

None

fixing_source: str
group_name: str
metric: str
schedule_start: Optional[date]
property timezone: str

Returns the timezone

Returns:

the timezone identifier as a string

unit: str
adjustments(frequency: str = 'ALL') → list[str]

Returns the available adjustments for the MacroEconomic fix, and optionally frequency

Parameters:

frequency – The frequency of results to query in

Returns:

List of the available adjustments

data_df(data_point: DataPoint = None, multi_index: bool = False, drop_nan_cols: bool = False, pretty_print=True) → DataFrame

Return a DataFrame containing all data available for this object.

Parameters:

  • data_point – Optional data point used to load the object history (if applicable).

  • multi_index – If set to True, rows are uniquely indexed by a multi index (if applicable). Default is False.

  • drop_nan_cols – If set to True, all-NaN columns are dropped. Default is False.

  • pretty_print – If set to True, formatting is added to columns names and data values. Rates will be represented as percentage number instead of decimal number (e.g. 3.5 instead of 0.035).

Returns:

pandas DataFrame.

frequencies(adjustment: str = 'ALL') → list[str]

Returns the available frequencies present for the MacroEconomic fix and optionally adjustment

Parameters:

adjustment – The results’ adjustment to query within

Returns:

List of the available frequencies

history(field: str = 'LastPrice', adjust_for_delay: bool = False, date_index: bool = False, data_point: Optional[DataPoint] = None, datetime_index: bool = False) → Union[Series, DataFrame]

Method to retrieve time series for objects If the given field does not exist, an empty series will be returned.

Parameters:

  • field – Optional - Which revision of a date’s reading to use. Must be one of

  • adjust_for_delay – Not supported

  • date_index – Optional - Convert the timestamp index to dates.

  • data_point – Optional data point, not fully supported

  • datetime_index – Optional - Add time and UTC timezone to the returned series index

Returns:

pd.Series.

history_df(fields: list[str] = None, data_point: DataPoint = None, multicolumn: bool = False, revision_version: str = 'last', adjustment: str = 'ALL', frequency: str = 'ALL', metric: str = 'ALL') deprecated

Method to retrieve a pd.DataFrame of the historical macroeconomic data.

Parameters:

  • fields – list of fields. If not supplied, self.history_fields will be used

  • data_point – optional data point used to load the object history.

  • multicolumn – If True (default) return a pd.DataFrame with columns as pd.MultiIndex, otherwise, if False return the same pd.DataFrame with the columns simply as fields.

  • revision_version – The revision version to return. Permissible values are ‘last’ (default), ‘first’ and ‘all’ (returns all revisions).

  • adjustment – The adjustment to return, ‘all’ by default. List available adjustments with .adjustments()

  • frequency – The frequency to return, ‘all’ by default. List available frequencies with .frequencies()

  • metric – The metric to return, ‘all’ by default. List available metrics with .metrics()

Returns:

pd.DataFrame.

holidays()

Returns the name of the holiday calendar associated with this Fix

Returns:

The name of the holiday calendar

macro(field: str = 'value', date_index: bool = False, revision_version: str = 'last', adjustment: str = 'ALL', frequency: str = 'ALL', return_df: bool = True, metric: str = 'ALL') deprecated

Method to retrieve a pd.DataFrame of the macro data.

Parameters:

  • field – Optional - Field to return, ‘lastPrice’ by default

  • date_index – Optional - Convert the timestamp index to dates.

  • revision_version – The revision version to return. Permissible values are ‘last’ (default), ‘first’ and ‘all’ (returns all revisions)

  • adjustment – The adjustment to return, ‘all’ by default. List available adjustments with .adjustments()

  • frequency – The frequency to return, ‘all’ by default. List available frequencies with .frequencies()

  • metric – The metric to return, ‘all’ by default. List available metrics with .metrics()

  • return_df – Whether to return a pd.DataFrame or pd.Series object. True (pd.DataFrame) by default.

Returns:

pd.DataFrame by default, pd.Series optionally

metrics(frequency: str = 'ALL', adjustment: str = 'ALL') → list[str]

Returns the available metrics present for the MacroEconomic fix

Parameters:

  • frequency – The frequency of results to query in

  • adjustment – The results’ adjustment to query in

Returns:

List of the available metrics

schedule_builder(start, end, frequency: str = 'ALL', adjustment: str = 'ALL')

Builds the schedule of days on which data was released, for all datapoints held, and returns it

Parameters:

  • start – Unused

  • end – Unused

  • frequency – Frequency of the fix

  • adjustment – Adjustment of the fix

Returns:

Schedule object