def daily_trade(universe=None, date=None, days_back=90):
"""Returns a list of all the current traded spread (which are set to Trade in the universe)
:param universe: list: Not necessary, if not specified will use Excel.
:param date: If specified, returns the list for a specific date (today is set to default)
:param days_back: int - Number of business days to expiration
:return: DataFrame
"""
log = logging.getLogger(__name__)
log.debug('Daily Trade list')
universe = list(
get_universe()['CTicker']) if universe is None else universe
day = dt.datetime.now().strftime('%Y-%m-%d') if date is None else date
dfs = []
for ct in universe:
fc = cc.FutureChain(ct, i.FutureType.Spread)
fc.initialize_contracts(cc.Status.Active,
nac=4) # Trade the first 2 spreads
dfs.append(fc.chain)
rdf = pd.concat(dfs)
rdf['DaysTo'] = rdf.apply(
lambda x: len(pd.date_range(day, x['LastDate'], freq=o.BDay())),
axis=1)
rdf = rdf[rdf['DaysTo'] <= days_back + 3] # Added 3
return rdf.reset_index(drop=True)
def initialize_cerebro_for_single_bt(stem, cash, mode):
"""Initialize Cerebro for a backtest. Needs cash, commissions, data and analyser.
:param stem: str - Customized ticker
:param cash: float - Portfolio start value
:param mode: Enum Mode - Which mode to run: Backtest or Live?
:return: object Cerebro, object FutureChain - These are both needed to run a backtest
"""
log = logging.getLogger(__name__)
# Setup Cerebro
cerebro = ob.Backtest.setup_cerebro(cash)
# Future Chain
status = occ.Status.Expired if mode == Mode.Backtest else occ.Status.ActiveLive
fc = occ.FutureChain(stem, oci.FutureType.Spread)
fc.initialize_contracts(status, initialize_data=True)
start, end = fc.get_start_end(extra_days=True)
# Commissions - Note: When throwing margin rejects => due to missing data
cerebro.broker.setcommission(commission=fc.commission * 2,
margin=fc.margin,
mult=fc.point)
# Data
end = dt.datetime.today().strftime(
'%Y-%m-%d'
) if mode == Mode.Live else end # Needed to stop at today's bar
cerebro = oru.add_reference_data(cerebro, start, end)
cerebro = oru.add_chain_data(cerebro, [fc])
return cerebro, fc
def test_initialize_data():
fc = occ.FutureChain('LH', oci.FutureType.Outright)
fc.initialize_contracts(occ.Status.Expired,
filter='H',
initialize_data=True)
test = []
for ct in fc.contracts:
test.extend(fc.data[ct]['OI'])
def test_get_start_end():
fc = occ.FutureChain('LH', oci.FutureType.Outright)
fc.initialize_contracts(occ.Status.Active, initialize_data=True)
start, end = fc.get_start_end(extra_days=True)
print('Start: {} - End: {}'.format(start, end))
assert isinstance(start, str)
assert isinstance(end, str)
assert isinstance(dt.datetime.strptime(start, '%Y-%m-%d'), dt.datetime)
assert isinstance(dt.datetime.strptime(end, '%Y-%m-%d'), dt.datetime)
def test_get_dates():
stem = 'W_'
fc = occ.FutureChain(stem, oci.FutureType.Spread)
fc.initialize_contracts(occ.Status.Expired, we_trade=False)
fc.initialize_data()
start, end = fc.get_start_end(extra_days=True)
print('Start: {} - End: {}'.format(start, end))
calendar = pmc.get_calendar('CME').valid_days(start, end)
dates = ore.get_dates(ore.Events.SpotLimit, calendar, fc.chain, 2)
assert isinstance(dates, list)
assert isinstance(dates[0], dt.date)
print(dates)
def test_chain_last__ticker_filter():
fc = occ.FutureChain('LB', oci.FutureType.Spread)
fc.initialize_contracts(occ.Status.Active, initialize_data=True)
print(fc.last_date(0))
print(fc.ticker(1))
assert isinstance(fc.last_date(0), dt.datetime)
import pandas_market_calendars as pmc
calendar = pmc.get_calendar('CME').valid_days('2018-01-01', '2018-12-31')
print(calendar.get_loc(fc.last_date(0)))
assert isinstance(fc.ticker(1), str)
contracts = fc.contracts[0:2]
fc.filter_chain(contracts)
assert len(fc.contracts) == len(contracts)
def generate_tickers_df(stem, status=occ.Status.Active):
"""Generate a DataFrame of symbols for a given stem for data download
:param stem: str - Customized Stem
:param status: Enum Status - Status needed for download
:return: DataFrame with Ticker Column
"""
log = logging.getLogger(__name__)
dfs = []
# Get number of active contracts and number of contracts in between
# TODO: Populate database.json with values for all contracts!
try:
dl = oci.get(stem, 'Download')
nac, ncb = dl['nac'], dl['ncb']
except oci.InstrumentError:
log.warning('{} - Set Download Parameters!'.format(stem))
nac, ncb = 4, 1 # Default behaviour when no parameters
params = {'as_dataframe': True, 'data_download': True}
ot = occ.FutureChain(stem, oci.FutureType.Outright).initialize_contracts(
status, we_trade=False, nac=nac, **params)
st = occ.FutureChain(stem, oci.FutureType.Spread).initialize_contracts(
status,
we_trade=(False if stem != 'ED' else True),
nac=nac - 1,
ncb=ncb,
**params)
bt = occ.FutureChain(stem, oci.FutureType.Butterfly).initialize_contracts(
status, we_trade=True, nac=nac -
2, ncb=ncb, **params) if stem == 'ED' else None
dfs.append(ot)
dfs.append(st)
if bt is not None:
dfs.append(bt)
sdf = pd.concat(dfs)
return sdf.reset_index(drop=True)
def test_filter_chain_contracts():
fc = occ.FutureChain('LB', oci.FutureType.Spread)
odf = fc.initialize_contracts(occ.Status.Expired)
# All the contracts with a specific letter!
df = fc.initialize_contracts(occ.Status.Expired,
filter='X',
as_dataframe=True)
print(df.head())
# Check filtering with an incorrect letter works
df = fc.initialize_contracts(occ.Status.Expired, filter='Z')
assert len(odf) == len(df)
# Last number of contracts
nfilt = 5
df = fc.initialize_contracts(occ.Status.Expired,
filter=nfilt,
as_dataframe=True)
print(df.tail())
assert len(df) == nfilt
# Check too high number of contracts ignored
df = fc.initialize_contracts(occ.Status.Expired, filter=1000)
assert len(odf) == len(df)
def initialize_cerebro(stems, cash, mode, future_type=oci.FutureType.Spread):
"""Initialize Cerebro for a backtest. This is the multi-market version.
:param stems: str - Customized ticker
:param cash: float - Portfolio start value
:param mode: Enum Mode - Which mode to run: Backtest or Live?
:param future_type: obj FutureType - Which type of Future do we run the backtest on
:return: object Cerebro, object FutureChain - These are both needed to run a backtest
"""
log = logging.getLogger(__name__)
# Setup Cerebro
cerebro = ob.Backtest.setup_cerebro(cash)
# Future Chains
status = occ.Status.Expired if mode == Mode.Backtest else occ.Status.ActiveLive
chains = []
min_start = str(dt.date.today())
max_end = '1900-01-01'
for stem in stems:
fc = occ.FutureChain(stem, oci.FutureType.Spread)
fc.initialize_contracts(status, days_back=90, initialize_data=True)
try:
# Get Start/End
start, end = fc.get_start_end(extra_days=True)
min_start = min(start, min_start)
max_end = max(end, max_end)
# Add chain to the list if start/end ok
chains.append(fc)
except occ.ChainError:
log.error(
'{} discarded as there is a problem with the chain/data!'.
format(stem))
# Data
end = dt.datetime.today().strftime(
'%Y-%m-%d'
) if mode == Mode.Live else max_end # Needed to stop at today's bar
cerebro = oru.add_reference_data(cerebro, min_start, end)
cerebro = oru.add_chain_data(cerebro, chains, with_comms=True)
return cerebro, chains
def test_future_chain_contracts(stem, future_type):
status = occ.Status.Expired
fc = occ.FutureChain(stem, future_type)
# Check Contracts
df = fc.initialize_contracts(status, as_dataframe=True)
print(df)
assert isinstance(df, pd.DataFrame)
assert len(df.columns) == 2
assert set(df.columns) == {'Ticker', 'LastDate'}
# Temporary - Check len against old table.py module
# if future_type == ci.FutureType.Outright:
# ot = ct.outright_table(stem, status)
# print('Comparison: new: {} - old: {}'.format(len(df), len(ot)))
# elif future_type == ci.FutureType.Spread:
# st = ct.spread_table(stem, status)
# print('Comparison: new: {} - old: {}'.format(len(df), len(st)))
# Check Data
data = fc.initialize_data()
first_key = list(data.keys())[0]
print('First Key: {}'.format(first_key))
print('Data check:\n{}'.format(data[first_key].head()))
assert isinstance(data[first_key], pd.DataFrame)