def make_pipeline():
russell_universe = StaticAssets(
symbols(
['AAPL', 'AA', 'KKD', 'MON', 'SPY', 'XOM', 'JNJ', 'HD', 'MSFT']))
filt = AverageDollarVolume(window_length=30, mask=russell_universe) > 10e6
pipeline = Pipeline(columns={
"1y_returns": Returns(window_length=252),
},
screen=filt)
return pipeline
def make_pipeline():
base_universe = StaticAssets(symbols(['AAPL', 'SPY']))
pipe = Pipeline(columns={
'close':
USEquityPricing.close.latest,
'prev':
Previous([USEquityPricing.close], window_length=2, mask=base_universe),
'ret':
Returns(window_length=2, mask=base_universe),
'excess_return':
ExcessReturn(window_length=2, mask=base_universe),
},
screen=base_universe)
return pipe
import pandas as pd
from sharadar.pipeline.universes import UniverseWriter, UniverseReader, NamedUniverse
from zipline.pipeline.filters import StaticAssets
from sharadar.pipeline.engine import symbols, make_pipeline_engine
from sharadar.util.output_dir import get_output_dir
import os
from zipline.pipeline import Pipeline
from zipline.pipeline.data import USEquityPricing
pipe_start = pd.to_datetime('2009-02-03', utc=True)
pipe_end = pd.to_datetime('2020-02-07', utc=True)
screen = StaticAssets(symbols(['IBM', 'F', 'AAPL']))
universes_db_path = os.path.join(get_output_dir(), "universes.sqlite")
universe_name = 'my_universe1'
UniverseWriter(universes_db_path).write(universe_name, screen, pipe_start,
pipe_end)
sids = UniverseReader(universes_db_path).get_sid(universe_name, '2020-02-07')
print(sids)
sids = UniverseReader(universes_db_path).get_sid(universe_name, '2002-02-07')
print(sids)
spe = make_pipeline_engine()
pipe = Pipeline(columns={
'Close': USEquityPricing.close.latest,
},
screen=NamedUniverse('my_universe1'))
import pandas as pd
from zipline.pipeline import Pipeline
from zipline.pipeline.data import USEquityPricing
from sharadar.pipeline.engine import load_sharadar_bundle, symbols, make_pipeline_engine
from zipline.pipeline.filters import StaticAssets
import time
import datetime
bundle = load_sharadar_bundle()
bundle.asset_finder.retrieve_equities([199059, 199623])
print(symbols(['SPY']))
spe = make_pipeline_engine()
pipe_start = pd.to_datetime('2020-02-03', utc=True)
pipe_end = pd.to_datetime('2020-02-07', utc=True)
pipe = Pipeline(columns={
'Close': USEquityPricing.close.latest,
},
screen = StaticAssets(symbols(['IBM', 'F', 'AAPL']))
)
stocks = spe.run_pipeline(pipe, pipe_start, pipe_end)
print("stocks.shape [close]", stocks)
from sharadar.pipeline.factors import MarketCap, EV, Fundamentals
pipe_mkt_cap = Pipeline(columns={
from sharadar.pipeline.engine import prices, symbols, load_sharadar_bundle
import pandas as pd
pd.set_option('display.float_format', lambda x: '%.2f' % x)
# Apple's stock has split five times since the company went public.
# The stock split on a 4-for-1 basis on August 28, 2020, a 7-for-1 basis on June 9, 2014,
# and split on a 2-for-1 basis on February 28, 2005, June 21, 2000, and June 16, 1987.
start = pd.to_datetime('2020-08-26', utc=True)
end = pd.to_datetime('2020-09-02', utc=True)
# AAPL sid 199059
sids = symbols(['AAPL', 'F'])
print(prices(sids, start, end))
print("---")
bundle = load_sharadar_bundle()
pricing_reader = bundle.equity_daily_bar_reader
close, = pricing_reader.load_raw_arrays(
['close'],
start,
end,
sids,
)
print(close)
print("---")
import pandas as pd
from zipline.pipeline import Pipeline
from zipline.pipeline.data import USEquityPricing
from sharadar.pipeline.factors import MarketCap
from sharadar.pipeline.factors import EV
from sharadar.pipeline.factors import Fundamentals
from sharadar.pipeline.engine import load_sharadar_bundle, symbol, symbols, make_pipeline_engine
from zipline.pipeline.filters import StaticAssets
import time
import datetime
from zipline.pipeline.factors import CustomFactor, DailyReturns, Returns
from sharadar.pipeline.engine import BundleLoader
from sharadar.pipeline.factors import ForwardsReturns
universe = StaticAssets(symbols(['IBM', 'F', 'AAPL']))
pipe = Pipeline(columns={
'Close': USEquityPricing.close.latest,
'monthly_ret': Returns(window_length=2),
'monthly_fret': ForwardsReturns(window_length=3, mask=universe)
},
screen=universe)
engine = make_pipeline_engine()
pipe_start = pd.to_datetime('2020-04-06', utc=True)
stocks = engine.run_pipeline(pipe, pipe_start)
print(stocks)
from sharadar.pipeline.engine import (load_sharadar_bundle, symbol, symbols,
prices, prices_old, returns,
trading_date)
import pandas as pd
start = pd.to_datetime('2021-03-08', utc=True)
end = pd.to_datetime('2021-03-12', utc=True)
assets = symbols(['IBM', 'F', 'AAPL'])
p = prices(assets, start, end)
print(p)
assert p.shape == (5, 3)
assert type(p) == pd.DataFrame
assets = symbols(['SPY'])
p = prices(assets, start, end)
assert p.shape == (5, )
assert type(p) == pd.Series
assets = [symbol('SPY')]
p = prices(assets, start, end)
print(p)
assert p.shape == (5, )
assert type(p) == pd.Series
assets = symbols(['IBM', 'F', 'AAPL'])
p = returns(assets, start, end)
print(p)
assert p.shape == (5, 3)
assert type(p) == pd.DataFrame
from zipline.pipeline import Pipeline
from zipline.pipeline.data import EquityPricing
from zipline.pipeline.factors import Latest, Returns
from zipline.pipeline.filters import StaticAssets
pd.set_option('display.float_format', lambda x: '%.2f' % x)
# Apple's stock has split five times since the company went public.
# The stock split on a 4-for-1 basis on August 28, 2020, a 7-for-1 basis on June 9, 2014,
# and split on a 2-for-1 basis on February 28, 2005, June 21, 2000, and June 16, 1987.
start = pd.to_datetime('2020-08-26', utc=True)
end = pd.to_datetime('2020-09-02', utc=True)
# AAPL sid 199059
print(prices(symbols(['AAPL']), start, end))
engine = make_pipeline_engine()
universe = StaticAssets(symbols(['AAPL']))
pipe = Pipeline(
columns={
'close': Latest([EquityPricing.close], mask=universe),
'mkt_cap': MarketCap(mask=universe),
'prev': Previous([USEquityPricing.close],
window_length=2,
mask=universe),
'ret': Returns(window_length=2, mask=universe),
},
screen=universe,
)
import pandas as pd
from zipline.pipeline import Pipeline
from zipline.pipeline.data import USEquityPricing
from sharadar.pipeline.engine import symbol, symbols, make_pipeline_engine
from zipline.pipeline.filters import StaticAssets
tickers = symbols(['TR1M', 'TR1Y', 'RATEINF'])
print(tickers)
pipe = Pipeline(columns={
'Close': USEquityPricing.close.latest,
},
screen=StaticAssets(tickers))
engine = make_pipeline_engine()
pipe_start = pd.to_datetime('2020-02-03', utc=True)
pipe_end = pd.to_datetime('2020-02-07', utc=True)
stocks = engine.run_pipeline(pipe, pipe_start, pipe_end)
print("stocks.shape [close]", stocks)
print(symbol('TR1M').to_dict())
pipe = Pipeline(columns={
'close': USEquityPricing.close.latest,
'adv': AverageDollarVolume(window_length=3),
'sharesbas_arq': Fundamentals(field='sharesbas_arq'),
'sharefactor_arq': Fundamentals(field='sharefactor_arq'),
'mkt_cap': MarketCap(),
'ev': EV(),
'debt': Fundamentals(field='debtusd_arq'),
'cash': Fundamentals(field='cashnequsd_arq'),
'EvEbit': EvEbit(),
'EvEbitda': EvEbitda(),
'PriceBook': PriceBook(),
'PriceEarnings': PriceEarnings(),
'PriceSales': PriceSales()
},
screen=StaticAssets(symbols(['AAPL'])))
pipe_start = pd.to_datetime('2021-03-15', utc=True)
stocks = spe.run_pipeline(pipe, pipe_start)
print(stocks.iloc[0])
assert stocks.iloc[0]['EvEbit'] == 28.90
assert stocks.iloc[0]['EvEbitda'] == 25.20
assert stocks.iloc[0]['PriceBook'] == 31.40
assert stocks.iloc[0]['PriceEarnings'] == 32.60
assert stocks.iloc[0]['PriceSales'] == 7.10
assert stocks.iloc[0]['cash'] == 36010000000.00
assert stocks.iloc[0]['close'] == 121.03
assert stocks.iloc[0]['debt'] == 112043000000.00
assert stocks.iloc[0]['ev'] == 2157589000000.00
assert stocks.iloc[0]['mkt_cap'] == 2081556000000.00
assert stocks.iloc[0]['sharefactor_arq'] == 1.00
import pandas as pd
from zipline.pipeline import Pipeline
from zipline.pipeline.data import USEquityPricing
from sharadar.pipeline.factors import (MarketCap, EV, Fundamentals,
LogFundamentalsTrend, LogTimeTrend,
InvestmentToAssets,
InvestmentToAssetsTrend)
from sharadar.pipeline.engine import load_sharadar_bundle, symbol, symbols, make_pipeline_engine
from zipline.pipeline.filters import StaticAssets
from zipline.pipeline.factors import CustomFactor
import numpy as np
#universe = StaticAssets(symbols(['IBM', 'F', 'AAPL']))
universe = StaticAssets(symbols(['IBM']))
pipe = Pipeline(columns={
'ia': InvestmentToAssets(),
'ia_trend': InvestmentToAssetsTrend(mask=universe).trend
},
screen=universe)
engine = make_pipeline_engine()
pipe_date = pd.to_datetime('2020-06-01', utc=True)
stocks = engine.run_pipeline(pipe, pipe_date)
print(stocks)
#NO PERIODIC
# ey ey_trend \
#2017-09-07 00:00:00+00:00 Equity(199059 [AAPL]) 0.055782 0.000066
# Equity(199623 [IBM]) 0.085316 -0.000013
# Equity(199713 [F]) 0.083262 0.000290
from sharadar.pipeline.factors import Exchange, Sector, IsDomesticCommonStock, MarketCap, Fundamentals, EV
from zipline.pipeline.factors import AverageDollarVolume
from sharadar.pipeline.universes import TradableStocksUS
from sharadar.loaders.ingest_macro import ingest
bundle = load_sharadar_bundle()
def ingest_macro():
start = bundle.equity_daily_bar_reader.first_trading_day
print("Adding macro data from %s ..." % (start))
print(ingest(start))
#ingest_macro()
spe = make_pipeline_engine()
pipe_start = pd.to_datetime('2021-01-04', utc=True)
pipe_end = bundle.equity_daily_bar_reader.last_available_dt
macro = symbols([
'TR3M', 'TR6M', 'TR1Y', 'TR2Y', 'TR3Y', 'TR5Y', 'TR7Y', 'TR10Y', 'TR20Y',
'CBOND', 'INDPRO', 'INDPROPCT', 'PMICMP', 'UNRATE', 'RATEINF'
])
pipe = Pipeline(columns={
'Close': USEquityPricing.close.latest,
},
screen=StaticAssets(macro))
stocks = spe.run_pipeline(pipe, pipe_start, pipe_end)
print(stocks.tail(30))
