EquityIndex

class sigtech.framework.instruments.indices.EquityIndex

Baseclasses: Index

A class representing equity indices.

property discount_curve_obj

Return an object representing the discount curve for the index.

property dividend_curve_name

Return the index name with a Dividend Curve identifier.

property dividend_curve_obj

Return an object representing the dividend curve of the index.

property dividend_curves

Return the timeseries of the dividend curve for the index.

property fundamental_fields: list[str]

Fundamental fields available for this equity index.

Returns:

List of fundamental fields.

total_return: Optional[bool]

underlying_fixing_delay: Optional[int]

constituents(start_datetime: datetime = None) → DataFrame

Index constituents.

Parameters:

start_datetime – Starting point in time of the index constituents (optional).

Returns:

pandas DataFrame containing the index constituents.

constituents_dict(dates: list = None, start_date: datetime = None, end_date: datetime = None) → dict[datetime.datetime, list[str]]

Return a dict containing the index constituents given a range or list of dates. If no parameters are provided, the dict will contain the most recent list of constituents.

Example of usage:

import datetime as dtm
import pandas as pd

sig.obj.get('SPX INDEX').constituents_dict()
sig.obj.get('SPX INDEX').constituents_dict([dtm.datetime(2021, 4, 4)])

start_date = dtm.datetime(2021, 1, 1)
end_date = dtm.datetime(2021, 1, 3)
sig.obj.get('SPX INDEX').constituents_dict(start_date=start_date, end_date=end_date)

few_dates = pd.date_range(dtm.date(2019, 3, 4), dtm.date(2019, 4, 1), freq='7d')
sig.obj.get('SPX INDEX').constituents_dict(few_dates)

Parameters:

• dates – DatetimeIndex or datetime list (optional).

• start_date – Start datetime (optional).

• end_date – End datetime (optional).

Returns:

dict.

discount_curves(data_point=None, data_dates=None)

Return the timeseries of the discount curve for the index.

Parameters:

• data_dates – List of dates.

• data_point – Data point (optional).

Returns:

Timeseries.

fundamental_series(field, data_as_of=None)

Return a fundamental series available for the equity index.

Parameters:

• field – Field name, e.g. 'price_to_earnings_ratio'.

• data_as_of – As of date/datetime of the data to be used. Defaults to environment as of date.

Returns:

pandas Series.

fundamentals() → DataFrame

Raw DataFrame of fundamental data.

Returns:

pandas DataFrame.

underlying_forward_price(quote_date, maturity_date, spot_date=None, discrete_dividend=False, spot_override=None, curve_shift=0, data_point=None)

Forward price of the underlying.

Parameters:

• quote_date – Quote date of the underlying.

• maturity_date – Maturity date of the underlying.

• spot_date – Spot date of the underlying (optional).

• discrete_dividend – Flag to replace dividend yield with discrete dividends if forwards are implied from discount factors and dividend (optional).

• spot_override – Spot price to override (optional).

• curve_shift – Curve shift (optional).

• data_point – Data point (optional).

Returns:

Forward price of the underlying.

underlying_forward_prices(quote_dates, maturity_dates, spot_dates=None, discrete_dividend=False, spot_overrides=None, curve_shift=0, data_point=None)

Forward prices of the underlying.

Parameters:

• quote_dates – Quote dates of the underlying.

• maturity_dates – Maturity dates of the underlying.

• spot_dates – Spot dates of the underlying (optional).

• discrete_dividend – Flag to replace dividend yield with discrete dividends if forwards are implied from discount factors and dividend (optional).

• spot_overrides – Spot prices to override (optional).

• curve_shift – Curve shift (optional).

• data_point – Data point (optional).

Returns:

Forward prices of the underlying.