def __init__(self, resolution=Resolution.Daily):
'''Initialize a new instance of EqualWeightingPortfolioConstructionModel
Args:
resolution: Rebalancing frequency'''
self.insightCollection = InsightCollection()
self.removedSymbols = []
self.nextExpiryTime = UTCMIN
self.rebalancingTime = UTCMIN
self.rebalancingPeriod = Extensions.ToTimeSpan(resolution)
def __init__(self, resolution, slowPeriod, longPeriod, positive_abnormal,
negative_abnormal):
'''Initializes a new instance of the EmaCrossAlphaModel class
Args:
slowPeriod: The slow EMA period'''
self.resolution = resolution
self.slowPeriod = slowPeriod
self.longPeriod = longPeriod
#self.positive_abnormal = positive_abnormal
#self.negative_abnormal = negative_abnormal
self.predictionInterval = Time.Multiply(
Extensions.ToTimeSpan(self.resolution), self.slowPeriod)
self.symbolDataBySymbol = {}
resolutionString = Extensions.GetEnumString(self.resolution,
Resolution)
self.Name = '{}({},{})'.format(self.__class__.__name__,
self.slowPeriod, resolutionString)
def CreateUniverses(self, algorithm):
'''Creates the universes for this algorithm. Called once after IAlgorithm.Initialize
Args:
algorithm: The algorithm instance to create universes for</param>
Returns:
The universes to be used by the algorithm'''
universeSettings = self.universeSettings \
if self.universeSettings is not None else algorithm.UniverseSettings
resolution = universeSettings.Resolution
type = typeof(Tick) if resolution == Resolution.Tick else typeof(
TradeBar)
universes = list()
# universe per security type/market
self.symbols = sorted(self.symbols,
key=lambda s: (s.ID.Market, s.SecurityType))
for key, grp in groupby(self.symbols, lambda s:
(s.ID.Market, s.SecurityType)):
market = key[0]
securityType = key[1]
securityTypeString = Extensions.GetEnumString(
securityType, SecurityType)
universeSymbol = Symbol.Create(
f"manual-universe-selection-model-{securityTypeString}-{market}",
securityType, market)
if securityType == SecurityType.Base:
# add an entry for this custom universe symbol -- we don't really know the time zone for sure,
# but we set it to TimeZones.NewYork in AddData, also, since this is a manual universe, the time
# zone doesn't actually matter since this universe specifically doesn't do anything with data.
symbolString = MarketHoursDatabase.GetDatabaseSymbolKey(
universeSymbol)
alwaysOpen = SecurityExchangeHours.AlwaysOpen(
TimeZones.NewYork)
entry = self.MarketHours.SetEntry(market, symbolString,
securityType, alwaysOpen,
TimeZones.NewYork)
else:
entry = self.MarketHours.GetEntry(market, None, securityType)
config = SubscriptionDataConfig(type, universeSymbol, resolution,
entry.DataTimeZone,
entry.ExchangeHours.TimeZone,
False, False, True)
universes.append(
ManualUniverse(config, universeSettings, list(grp)))
return universes
def __init__(self, rebalancingParam=Resolution.Daily):
'''Initialize a new instance of EqualWeightingPortfolioConstructionModel
Args:
rebalancingParam: Rebalancing parameter. If it is a timedelta or Resolution, it will be converted into a function.
The function returns the next expected rebalance time for a given algorithm UTC DateTime'''
self.removedSymbols = []
# If the argument is an instance of Resolution or Timedelta
# Redefine rebalancingFunc
rebalancingFunc = rebalancingParam
if isinstance(rebalancingParam, int):
rebalancingParam = Extensions.ToTimeSpan(rebalancingParam)
if isinstance(rebalancingParam, timedelta):
rebalancingFunc = lambda dt: dt + rebalancingParam
if rebalancingFunc:
self.SetRebalancingFunc(rebalancingFunc)
def __init__(self, rebalancingParam=Resolution.Daily):
'''Initialize a new instance of EqualWeightingPortfolioConstructionModel
Args:
rebalancingParam: Rebalancing parameter. If it is a timedelta, date rules or Resolution, it will be converted into a function.
If None will be ignored.
The function returns the next expected rebalance time for a given algorithm UTC DateTime.
The function returns null if unknown, in which case the function will be called again in the
next loop. Returning current time will trigger rebalance.'''
self.removedSymbols = []
# If the argument is an instance of Resolution or Timedelta
# Redefine rebalancingFunc
rebalancingFunc = rebalancingParam
if isinstance(rebalancingParam, int):
rebalancingParam = Extensions.ToTimeSpan(rebalancingParam)
if isinstance(rebalancingParam, timedelta):
rebalancingFunc = lambda dt: dt + rebalancingParam
if rebalancingFunc:
self.SetRebalancingFunc(rebalancingFunc)
def __init__(self,
rebalance=Resolution.Daily,
portfolioBias=PortfolioBias.LongShort):
'''Initialize a new instance of EqualWeightingPortfolioConstructionModel
Args:
rebalance: Rebalancing parameter. If it is a timedelta, date rules or Resolution, it will be converted into a function.
If None will be ignored.
The function returns the next expected rebalance time for a given algorithm UTC DateTime.
The function returns null if unknown, in which case the function will be called again in the
next loop. Returning current time will trigger rebalance.
portfolioBias: Specifies the bias of the portfolio (Short, Long/Short, Long)'''
self.portfolioBias = portfolioBias
# If the argument is an instance of Resolution or Timedelta
# Redefine rebalancingFunc
rebalancingFunc = rebalance
if isinstance(rebalance, int):
rebalance = Extensions.ToTimeSpan(rebalance)
if isinstance(rebalance, timedelta):
rebalancingFunc = lambda dt: dt + rebalance
if rebalancingFunc:
self.SetRebalancingFunc(rebalancingFunc)