ETFs#
Retrieve data for exchange-traded fund (ETF) instruments.
Initialize SigTech
Import Python libraries:
import datetime as dtm
import numpy as np
import pandas as pd
import sigtech.framework as sig
Initialize the SigTech framework environment:
env = sig.init()
Learn more
List available ETF instruments#
ETF instruments are instances of the sig.ExchangeTradedFund class.
To list ETF object names, call the sig.ExchangeTradedFund.get_names class method:
Input:
etf_names = sig.ExchangeTradedFund.get_names()
etf_names[:5]
Output:
['AGG UP EQUITY',
'BIL UP EQUITY',
'BND UP EQUITY',
'BNDX UP EQUITY',
'DBC UP EQUITY']
Retrieve an ETF instrument#
To retrieve an ETF instrument, pass its object name to sig.obj.get:
Input:
agg = sig.obj.get('AGG UP EQUITY')
agg
Output:
AGG UP EQUITY <class 'sigtech.framework.instruments.equities.ExchangeTradedFund'>[139953121183952]
Retrieve a dictionary of static data describing an ETF instrument:
Input:
agg.data_dict()
Output:
{'_product_type': 'Exchange Traded Fund',
'instrument_id': None,
'_data_source_all': [],
'_available_data_points': ['EOD'],
'_default_data_point': 'EOD',
'price_factor': 1.0,
...}
Retrieve the instrument group for an ETF:
Input:
group = agg.group()
group
Output:
NYSEARC(T) EQUITY INSTRUMENT GROUP <class 'sigtech.framework.instruments.equities.EquityGroup'>[140328852910736]
List the names of instruments in NYSEARC(T) EQUITY INSTRUMENT GROUP:
Input:
group.query_instrument_names()[:5]
Output:
['AGG UP EQUITY',
'BIL UP EQUITY',
'BND UP EQUITY',
'BNDX UP EQUITY',
'DBC UP EQUITY']
Retrieve the exchange on which an ETF is traded:
Input:
exchange = sig.obj.get(agg.exchange().name)
exchange
Output:
NYSEARC(T) EXCHANGE GROUP <class 'sigtech.framework.instruments.base.Exchange'>[139953149826448]
Retrieve an ETF instrument’s exchange holiday calendar#
Retrieve the object name of the exchange’s market holiday calendar:
Input:
exchange.holidays
Output:
'NYSEARC(T) CALENDAR'
Retrieve the corresponding holiday calendar object, an instance of sig.HolidayCalendar:
Input:
calendar = sig.obj.get(exchange.holidays)
calendar
Output:
NYSEARC(T) CALENDAR <class 'sigtech.framework.infra.calendar.calendar.HolidayCalendar'>[139915073725392]
View the dates in the calendar:
Input:
calendar.holidays[:5]
Output:
[datetime.date(1973, 1, 1),
datetime.date(1973, 1, 25),
datetime.date(1973, 1, 25),
datetime.date(1973, 2, 19),
datetime.date(1973, 4, 20)]
Retrieve an ETF instrument’s time series data#
Retrieve an ETF instrument’s time series data:
Python:
agg.history().tail()
Output:
2024-07-15 98.05
2024-07-16 98.45
2024-07-17 98.52
2024-07-18 98.25
2024-07-19 98.05
Name: (LastPrice, EOD, AGG UP EQUITY), dtype: float64
List available time series data fields for an ETF instrument:
Input:
agg.history_fields
Output:
['OPEN', 'HIGH', 'LOW', 'LastPrice', 'Volume']
Retrieve time series data for a specified field:
Input:
field_name = "HIGH"
agg.history(field_name).tail()
Output:
2024-07-15 98.28
2024-07-16 98.45
2024-07-17 98.57
2024-07-18 98.56
2024-07-19 98.10
Name: (HIGH, EOD, AGG UP EQUITY), dtype: float64
Create a pandas DataFrame from specified time series data fields, and plot the data:
df_agg = pd.concat({
'High': agg.history('HIGH').loc['2023':],
'Low': agg.history('LOW').loc['2023':]
}, axis=1)
df_agg.plot(title='AGG UP Equity High / Low');
Create a bar chart showing an ETF’s volume data over time:
volume_agg = agg.history('Volume').loc['2024-05':]
volume_agg.index = [x.date() for x in volume_agg.index]
volume_agg.plot(title='AGG UP EQUITY Volume', kind='bar');
Compare multiple ETFs using pandas#
SigTech time series data is compatible with NumPy and pandas data structures and methods.
Use pandas to compare multiple ETFs:
Input:
ptf_etfs = ['AGG UP EQUITY', 'SPY UP EQUITY', 'VEA UP EQUITY']
etf_histories = pd.concat({
x: sig.obj.get(x).history() for x in ptf_etfs
}, axis=1).dropna()
etf_histories.columns = [x.split('_')[0] for x in etf_histories.columns]
print(etf_histories.tail())
Output:
AGG UP EQUITY SPY UP EQUITY VEA UP EQUITY
2024-07-15 98.05 561.53 51.11
2024-07-16 98.45 564.86 51.41
2024-07-17 98.52 556.94 51.12
2024-07-18 98.25 552.66 50.62
2024-07-19 98.05 548.99 50.32
Display a plot of ETF performance over time:
(etf_histories / etf_histories.iloc[0]).plot(title='ETF Performance');