def Initialize(self):
self.SetStartDate(2018, 1, 1)
self.SetCash(100000)
# Set zero transaction fees
self.SetSecurityInitializer(
lambda security: security.SetFeeModel(ConstantFeeModel(0)))
# select stocks using PennyStockUniverseSelectionModel
self.UniverseSettings.Resolution = Resolution.Daily
self.SetUniverseSelection(PennyStockUniverseSelectionModel())
# Use SykesShortMicroCapAlphaModel to establish insights
self.SetAlpha(SykesShortMicroCapAlphaModel())
# Equally weigh securities in portfolio, based on insights
self.SetPortfolioConstruction(
EqualWeightingPortfolioConstructionModel())
# Set Immediate Execution Model
self.SetExecution(ImmediateExecutionModel())
# Set Null Risk Management Model
self.SetRiskManagement(NullRiskManagementModel())
def Initialize(self):
self.SetStartDate(2018, 1, 1)
self.SetCash(100000)
# Set zero transaction fees
self.SetSecurityInitializer(
lambda security: security.SetFeeModel(ConstantFeeModel(0)))
# Use Hourly Data For Simplicity
self.UniverseSettings.Resolution = Resolution.Hour
self.SetUniverseSelection(
CoarseFundamentalUniverseSelectionModel(
self.CoarseSelectionFunction))
# Use MeanReversionLunchBreakAlphaModel to establish insights
self.SetAlpha(MeanReversionLunchBreakAlphaModel())
# Equally weigh securities in portfolio, based on insights
self.SetPortfolioConstruction(
EqualWeightingPortfolioConstructionModel())
# Set Immediate Execution Model
self.SetExecution(ImmediateExecutionModel())
# Set Null Risk Management Model
self.SetRiskManagement(NullRiskManagementModel())
def Initialize(self):
# -- STRATEGY INPUT PARAMETERS --
self.k1 = 0.63
self.k2 = 0.63
self.rangePeriod = 20
self.consolidatorBars = 30
# Settings
self.SetStartDate(2018, 10, 1)
self.SetSecurityInitializer(lambda security: security.SetFeeModel(ConstantFeeModel(0)))
self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Margin);
# Universe Selection
self.UniverseSettings.Resolution = Resolution.Minute # it's minute by default, but lets leave this param here
symbols = [Symbol.Create("SPY", SecurityType.Equity, Market.USA)]
self.SetUniverseSelection(ManualUniverseSelectionModel(symbols))
# Warming up
resolutionInTimeSpan = Extensions.ToTimeSpan(self.UniverseSettings.Resolution)
warmUpTimeSpan = Time.Multiply(resolutionInTimeSpan, self.consolidatorBars)
self.SetWarmUp(warmUpTimeSpan)
# Alpha Model
self.SetAlpha(DualThrustAlphaModel(self.k1, self.k2, self.rangePeriod, self.UniverseSettings.Resolution, self.consolidatorBars))
## Portfolio Construction
self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
## Execution
self.SetExecution(ImmediateExecutionModel())
## Risk Management
self.SetRiskManagement(MaximumDrawdownPercentPerSecurity(0.03))
def Initialize(self):
self.SetStartDate(2019, 2, 1) #Set Start Date
self.SetCash(100000) #Set Strategy Cash
# Set zero transaction fees
self.SetSecurityInitializer(
lambda security: security.SetFeeModel(ConstantFeeModel(0)))
## Select trio of currencies to trade where
## Currency A = USD
## Currency B = EUR
## Currency C = GBP
currencies = ['EURUSD', 'EURGBP', 'GBPUSD']
symbols = [
Symbol.Create(currency, SecurityType.Forex, Market.Oanda)
for currency in currencies
]
## Manual universe selection with tick-resolution data
self.UniverseSettings.Resolution = Resolution.Minute
self.SetUniverseSelection(ManualUniverseSelectionModel(symbols))
self.SetAlpha(
ForexTriangleArbitrageAlphaModel(Resolution.Minute, symbols))
## Set Equal Weighting Portfolio Construction Model
self.SetPortfolioConstruction(
EqualWeightingPortfolioConstructionModel())
## Set Immediate Execution Model
self.SetExecution(ImmediateExecutionModel())
## Set Null Risk Management Model
self.SetRiskManagement(NullRiskManagementModel())
def Initialize(self):
self.SetStartDate(2018, 1, 1) #Set Start Date
self.SetCash(100000) #Set Strategy Cash
## Initialize variables to be used in controlling frequency of universe selection
self.week = None
self.symbols = None
self.SetWarmUp(100)
## Manual Universe Selection
self.SetUniverseSelection(
CoarseFundamentalUniverseSelectionModel(
self.CoarseSelectionFunction))
## Set trading fees to $0
self.SetSecurityInitializer(
lambda security: security.SetFeeModel(ConstantFeeModel(0)))
## Set custom Alpha Model
self.SetAlpha(PriceGapMeanReversionAlphaModel())
## Set equal-weighting Portfolio Construction Model
self.SetPortfolioConstruction(
EqualWeightingPortfolioConstructionModel())
## Set Execution Model
self.SetExecution(ImmediateExecutionModel())
## Set Risk Management Model
self.SetRiskManagement(NullRiskManagementModel())
def Initialize(self):
self.SetStartDate(2015, 1, 1)
self.SetCash(100000)
# Set zero transaction fees
self.SetSecurityInitializer(
lambda security: security.SetFeeModel(ConstantFeeModel(0)))
# Select resolution
resolution = Resolution.Hour
# Reversion on the USD.
symbols = [Symbol.Create("EURUSD", SecurityType.Forex, Market.Oanda)]
# Set requested data resolution
self.UniverseSettings.Resolution = resolution
self.SetUniverseSelection(ManualUniverseSelectionModel(symbols))
self.SetAlpha(IntradayReversalAlphaModel(5, resolution))
# Equally weigh securities in portfolio, based on insights
self.SetPortfolioConstruction(
EqualWeightingPortfolioConstructionModel())
# Set Immediate Execution Model
self.SetExecution(ImmediateExecutionModel())
# Set Null Risk Management Model
self.SetRiskManagement(NullRiskManagementModel())
#Set WarmUp for Indicators
self.SetWarmUp(20)
def Initialize(self):
self.SetStartDate(2018, 1, 1)
self.SetCash(100000)
# Set zero transaction fees
self.SetSecurityInitializer(lambda security: security.SetFeeModel(ConstantFeeModel(0)))
# 3X ETF pair tickers
ultraLong = Symbol.Create("UGLD", SecurityType.Equity, Market.USA)
ultraShort = Symbol.Create("DGLD", SecurityType.Equity, Market.USA)
# Manually curated universe
self.UniverseSettings.Resolution = Resolution.Daily
self.SetUniverseSelection(ManualUniverseSelectionModel([ultraLong, ultraShort]))
# Select the demonstration alpha model
self.SetAlpha(RebalancingTripleLeveragedETFAlphaModel(ultraLong, ultraShort))
## Set Equal Weighting Portfolio Construction Model
self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
## Set Immediate Execution Model
self.SetExecution(ImmediateExecutionModel())
## Set Null Risk Management Model
self.SetRiskManagement(NullRiskManagementModel())
def Initialize(self):
self.UniverseSettings.Resolution = Resolution.Daily
self.SetStartDate(2018, 1, 1) # Set Start Date
self.SetCash(1000000) # Set Strategy Cash
benchmark = Symbol.Create("SPY", SecurityType.Equity, Market.USA)
self.SetUniverseSelection(
UncorrelatedUniverseSelectionModel(benchmark))
self.SetAlpha(UncorrelatedUniverseSelectionAlphaModel())
self.SetPortfolioConstruction(
EqualWeightingPortfolioConstructionModel())
self.SetExecution(ImmediateExecutionModel())
def Initialize(self):
self.SetStartDate(2018, 1, 1)
self.SetCash(100000)
# Set zero transaction fees
self.SetSecurityInitializer(
lambda security: security.SetFeeModel(ConstantFeeModel(0)))
# Global Equity ETF tickers
tickers = [
"ECH", "EEM", "EFA", "EPHE", "EPP", "EWA", "EWC", "EWG", "EWH",
"EWI", "EWJ", "EWL", "EWM", "EWM", "EWO", "EWP", "EWQ", "EWS",
"EWT", "EWU", "EWY", "EWZ", "EZA", "FXI", "GXG", "IDX", "ILF",
"EWM", "QQQ", "RSX", "SPY", "THD"
]
symbols = [
Symbol.Create(ticker, SecurityType.Equity, Market.USA)
for ticker in tickers
]
# Manually curated universe
self.UniverseSettings.Resolution = Resolution.Daily
self.SetUniverseSelection(ManualUniverseSelectionModel(symbols))
# Use GlobalEquityMeanReversionAlphaModel to establish insights
self.SetAlpha(MeanReversionIBSAlphaModel())
# Equally weigh securities in portfolio, based on insights
self.SetPortfolioConstruction(
EqualWeightingPortfolioConstructionModel())
# Set Immediate Execution Model
self.SetExecution(ImmediateExecutionModel())
# Set Null Risk Management Model
self.SetRiskManagement(NullRiskManagementModel())
def Initialize(self):
self.SetStartDate(2019, 4, 30) # Set Start Date
self.SetEndDate(2019, 5, 1) # Set End Date
self.SetCash(100000) # Set Strategy Cash
#self.AddEquity("SPY")
self.symbol = "BTCUSD"
#self.AddEquity(self.symbol, Resolution.Minute).Symbol
self.AddCrypto(self.symbol, Resolution.Minute, Market.Bitfinex).Symbol
span = 500
longPeriod = 43200
ema = self.EMA(self.symbol, span)
ptvsd.break_into_debugger()
price = Identity(self.symbol)
ptvsd.break_into_debugger()
self.diff_pct_close_ema = IndicatorExtensions.Over(
IndicatorExtensions.Minus(price, ema), ema)
ptvsd.break_into_debugger()
self.diff_pct_close_ema_mean = IndicatorExtensions.SMA(
self.diff_pct_close_ema, longPeriod)
ptvsd.break_into_debugger()
std = self.STD(self.symbol, longPeriod)
diff_pct_close_ema_std = IndicatorExtensions.Of(
self.diff_pct_close_ema, std)
self.negative_abnormal = IndicatorExtensions.Minus(
self.diff_pct_close_ema_mean,
IndicatorExtensions.Times(diff_pct_close_ema_std, 1.96))
self.positive_abnormal = IndicatorExtensions.Plus(
self.diff_pct_close_ema_mean,
IndicatorExtensions.Times(diff_pct_close_ema_std, 1.96))
self.RegisterIndicator(self.symbol, self.diff_pct_close_ema,
Resolution.Minute)
self.RegisterIndicator(self.symbol, diff_pct_close_ema_std,
Resolution.Minute)
self.RegisterIndicator(self.symbol, self.diff_pct_close_ema_mean,
Resolution.Minute)
self.RegisterIndicator(self.symbol, self.negative_abnormal,
Resolution.Minute)
self.RegisterIndicator(self.symbol, self.positive_abnormal,
Resolution.Minute)
self.SetWarmUp(longPeriod)
#stockPlot = Chart("Trade Plot")
# On the Trade Plotter Chart we want 2 series: trades :
#stockPlot.AddSeries(Series("Buy", SeriesType.Scatter, 0))
#stockPlot.AddSeries(Series("Sell", SeriesType.Scatter, 0))
#stockPlot.AddSeries(Series("Close", SeriesType.Scatter, 0))
#self.AddChart(stockPlot)
# On the Deviation Chart we want serie, diff_pct_close_vs_ema
#deviation = Chart("Deviation Degree")
#deviation.AddSeries(Series("Deviation Degree", SeriesType.Line, 0))
#self.AddChart(deviation)
self.resamplePeriod = (self.EndDate - self.StartDate) / 4000
self.AddAlpha(
EmaReversionAlphaModel(self.symbol, self.diff_pct_close_ema,
self.negative_abnormal,
self.positive_abnormal,
self.diff_pct_close_ema_mean,
self.resamplePeriod))
self.SetPortfolioConstruction(
EqualWeightingPortfolioConstructionModel())
self.SetRiskManagement(MaximumDrawdownPercentPortfolio(0.1))
self.SetExecution(VolumeWeightedAveragePriceExecutionModel())
