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SymbolData.py
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Charts
Statistics
Code
##################################
##################################
#
#
# SymbolData Class
# SymbolData Class
#
#
##################################
##################################
class SymbolData():
class SymbolData():
## Constructor
## Constructor
## -----------
## -----------
def __init__(self, theSymbol, algo):
def __init__(self, theSymbol, algo):
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## Algo / Symbol / Price reference
## Algo / Symbol / Price reference
self.algo = algo
self.algo = algo
self.symbol = theSymbol
self.symbol = theSymbol
self.lastDailyClose = None
self.lastDailyClose = None
self.lastClosePrice = None
self.lastClosePrice = None
## Initialize our Indicators and rolling windows
## Initialize our Indicators and rolling windows
self.ema = ExponentialMovingAverage(self.algo.dailyEMAPeriod)
self.ema = ExponentialMovingAverage(self.algo.dailyEMAPeriod)
self.momentum = MomentumPercent(self.algo.hourlyMomPeriod)
self.momentum = MomentumPercent(self.algo.hourlyMomPeriod)
self.lastDailyCloseWindow = RollingWindow[float](2)
self.lastDailyCloseWindow = RollingWindow[float](2)
self.emaWindow = RollingWindow[float](2)
self.emaWindow = RollingWindow[float](2)
## These will hold our 'messages' used in our order notes
## These will hold our 'messages' used in our order notes
self.ClosePositionMessage = ""
self.ClosePositionMessage = ""
self.OpenPositionMessage = ""
self.OpenPositionMessage = ""
## Seed Daily indicators with history.
## Seed Daily indicators with history.
## -----------------------------------
## -----------------------------------
def SeedDailyIndicators(self, dailyHistory):
def SeedDailyIndicators(self, dailyHistory):
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# Loop over the history data and update our indicators
# Loop over the history data and update our indicators
if dailyHistory.empty or 'close' not in dailyHistory.columns:
if dailyHistory.empty or 'close' not in dailyHistory.columns:
# self.algo.Log(f"No Daily history for {self.symbol}")
# self.algo.Log(f"No Daily history for {self.symbol}")
return
return
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else:
else:
for timeIndex, dailyBar in dailyHistory.loc[self.symbol].iterrows():
for timeIndex, dailyBar in dailyHistory.loc[self.symbol].iterrows():
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if(self.ema is not None):
self.ema.Update(timeIndex, dailyBar['close'])
self.ema.Update(timeIndex, dailyBar['close'])
self.lastDailyClose = dailyBar['close']
self.lastDailyClose = dailyBar['close']
self.timeOflastDailyClose = timeIndex
self.timeOflastDailyClose = timeIndex
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self.lastDailyCloseWindow.Add(
dailyBar['close']
)
self.lastDailyCloseWindow.Add(
dailyBar['close']
)
self.emaWindow.Add(
self.ema.Current.Value
)
self.emaWindow.Add(
self.ema.Current.Value
)
## Seed intraday indicators with history
## Seed intraday indicators with history
## These indicators might be have eitehr hourly or minute resolution
## These indicators might be have eitehr hourly or minute resolution
## -----------------------------------------------------------------
## -----------------------------------------------------------------
def SeedIntradayIndicators(self, hourlyHistory=None, minuteHistory=None):
def SeedIntradayIndicators(self, hourlyHistory=None, minuteHistory=None):
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# Loop over the history data and update our indicators
# Loop over the history data and update our indicators
if hourlyHistory is not None:
if hourlyHistory is not None:
if hourlyHistory.empty or 'close' not in hourlyHistory.columns:
if hourlyHistory.empty or 'close' not in hourlyHistory.columns:
self.algo.Log(f"Missing hourly history for {self.symbol}")
self.algo.Log(f"Missing hourly history for {self.symbol}")
else:
else:
for timeIndex, hourlyBar in hourlyHistory.loc[self.symbol].iterrows():
for timeIndex, hourlyBar in hourlyHistory.loc[self.symbol].iterrows():
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if(self.momentum is not None):
self.momentum.Update(timeIndex, hourlyBar['close'])
self.momentum.Update(timeIndex, hourlyBar['close'])
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# If you are using minuteHistory, you need to add "someIndicator" to manage it in this class (in __init__())
if minuteHistory is not None:
if minuteHistory is not None:
if minuteHistory.empty or 'close' not in minuteHistory.columns:
if minuteHistory.empty or 'close' not in minuteHistory.columns:
self.algo.Log(f"Missing minute history for {self.symbol}")
self.algo.Log(f"Missing minute history for {self.symbol}")
else:
else:
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for timeIndex,
hourlyBar
in
hourlyHistory
.loc[self.symbol].iterrows():
for timeIndex,
minuteBar
in
minuteHistory
.loc[self.symbol].iterrows():
if
(
self.someIndicator is not None
):
if
self.someIndicator is not None
:
self.someIndicator.Update(timeIndex,
hourlyBar
['close'])
self.someIndicator.Update(timeIndex,
minuteBar
['close'])
return
return
## Daily screening criteria. Called by the main algorithm.
## Daily screening criteria. Called by the main algorithm.
## Returns true if daily screening conditions are met.
## Returns true if daily screening conditions are met.
## Replace with your own criteria.
## Replace with your own criteria.
## -------------------------------------------------------
## -------------------------------------------------------
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@property
def DailyScreeningCriteriaMet(self):
def DailyScreeningCriteriaMet(self):
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## Price is above ema.
## Price is above ema.
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if
(
self.lastDailyCloseWindow[0]
> self.emaWindow[0]
):
if
self.lastDailyCloseWindow[0]
> self.emaWindow[0]
:
return True
return True
return False
return False
## Intraday screening criteria. Called by the main
## Intraday screening criteria. Called by the main
## algorithm. Returns true if entry conditions are met.
## algorithm. Returns true if entry conditions are met.
## Replace with your own criteria.
## Replace with your own criteria.
## ----------------------------------------------------
## ----------------------------------------------------
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@property
def IntradayScreeningCriteriaMet(self):
def IntradayScreeningCriteriaMet(self):
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## If we have positive momentum
## If we have positive momentum
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if
(
self.momentum.Current.Value > 0
):
if
self.momentum.Current.Value > 0
:
## Informative message that will be submitted as order notes
## Informative message that will be submitted as order notes
self.OpenPositionMessage = f"OPEN (${round(self.lastDailyCloseWindow[0],3)} > EMA: {round(self.emaWindow[0],3)})"
self.OpenPositionMessage = f"OPEN (${round(self.lastDailyCloseWindow[0],3)} > EMA: {round(self.emaWindow[0],3)})"
return True
return True
return False
return False
## Trade Exit criteria. Called by the main algorithm.
## Trade Exit criteria. Called by the main algorithm.
## Returns true if exit conditions are met.
## Returns true if exit conditions are met.
## Replace with your own criteria.
## Replace with your own criteria.
## ---------------------------------------------------
## ---------------------------------------------------
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@property
def ExitCriteriaMet(self):
def ExitCriteriaMet(self):
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## Exit If price is below ema
## Exit If price is below ema
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if
(
self.lastClosePrice < self.ema.Current.Value
)
:
if
self.lastClosePrice < self.ema.Current.Value
:
self.ClosePositionMessage = f"CLOSE (${round(self.lastClosePrice,3)} < EMA: {round(self.ema.Current.Value,3)})"
self.ClosePositionMessage = f"CLOSE (${round(self.lastClosePrice,3)} < EMA: {round(self.ema.Current.Value,3)})"
return True
return True
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return False
return False
## Returns true if our daily indicators are ready.
## Returns true if our daily indicators are ready.
## Called from the main algo
## Called from the main algo
## -----------------------------------------------
## -----------------------------------------------
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@property
def DailyIndicatorsAreReady(self):
def DailyIndicatorsAreReady(self):
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return
(
self.ema.IsReady and self.lastDailyCloseWindow.IsReady
)
return
self.ema.IsReady and self.lastDailyCloseWindow.IsReady
## Returns true if our intraday indicators are ready.
## Returns true if our intraday indicators are ready.
## Called from the main algo
## Called from the main algo
## --------------------------------------------------
## --------------------------------------------------
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@property
def IntradayIndicatorsAreReady(self):
def IntradayIndicatorsAreReady(self):
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return
(
self.momentum.IsReady
)
return
self.momentum.IsReady
## Called by the main algorithm right after
## Called by the main algorithm right after
## a position is opened for this symbol.
## a position is opened for this symbol.
## ----------------------------------------
## ----------------------------------------
def OnPositionOpened(self):
def OnPositionOpened(self):
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## Register & warmup the indicators we need to track for exits
## Register & warmup the indicators we need to track for exits
self.algo.RegisterIndicator(self.symbol, self.ema, timedelta(1))
self.algo.RegisterIndicator(self.symbol, self.ema, timedelta(1))
self.algo.WarmUpIndicator(self.symbol, self.ema, Resolution.Daily)
self.algo.WarmUpIndicator(self.symbol, self.ema, Resolution.Daily)
## Called by the main algorithm right after
## Called by the main algorithm right after
## a position is closed for this symbol.
## a position is closed for this symbol.
## ----------------------------------------
## ----------------------------------------
def OnPositionClosed(self):
def OnPositionClosed(self):
# cleanup
# cleanup
pass
pass
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Texte d'origine
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Charts Statistics Code ################################## # # SymbolData Class # ################################## class SymbolData(): ## Constructor ## ----------- def __init__(self, theSymbol, algo): ## Algo / Symbol / Price reference self.algo = algo self.symbol = theSymbol self.lastDailyClose = None self.lastClosePrice = None ## Initialize our Indicators and rolling windows self.ema = ExponentialMovingAverage(self.algo.dailyEMAPeriod) self.momentum = MomentumPercent(self.algo.hourlyMomPeriod) self.lastDailyCloseWindow = RollingWindow[float](2) self.emaWindow = RollingWindow[float](2) ## These will hold our 'messages' used in our order notes self.ClosePositionMessage = "" self.OpenPositionMessage = "" ## Seed Daily indicators with history. ## ----------------------------------- def SeedDailyIndicators(self, dailyHistory): # Loop over the history data and update our indicators if dailyHistory.empty or 'close' not in dailyHistory.columns: # self.algo.Log(f"No Daily history for {self.symbol}") return else: for timeIndex, dailyBar in dailyHistory.loc[self.symbol].iterrows(): if(self.ema is not None): self.ema.Update(timeIndex, dailyBar['close']) self.lastDailyClose = dailyBar['close'] self.timeOflastDailyClose = timeIndex self.lastDailyCloseWindow.Add( dailyBar['close'] ) self.emaWindow.Add( self.ema.Current.Value ) ## Seed intraday indicators with history ## These indicators might be have eitehr hourly or minute resolution ## ----------------------------------------------------------------- def SeedIntradayIndicators(self, hourlyHistory=None, minuteHistory=None): # Loop over the history data and update our indicators if hourlyHistory is not None: if hourlyHistory.empty or 'close' not in hourlyHistory.columns: self.algo.Log(f"Missing hourly history for {self.symbol}") else: for timeIndex, hourlyBar in hourlyHistory.loc[self.symbol].iterrows(): if(self.momentum is not None): self.momentum.Update(timeIndex, hourlyBar['close']) if minuteHistory is not None: if minuteHistory.empty or 'close' not in minuteHistory.columns: self.algo.Log(f"Missing minute history for {self.symbol}") else: for timeIndex, hourlyBar in hourlyHistory.loc[self.symbol].iterrows(): if(self.someIndicator is not None): self.someIndicator.Update(timeIndex, hourlyBar['close']) return ## Daily screening criteria. Called by the main algorithm. ## Returns true if daily screening conditions are met. ## Replace with your own criteria. ## ------------------------------------------------------- def DailyScreeningCriteriaMet(self): ## Price is above ema. if(self.lastDailyCloseWindow[0] > self.emaWindow[0]): return True return False ## Intraday screening criteria. Called by the main ## algorithm. Returns true if entry conditions are met. ## Replace with your own criteria. ## ---------------------------------------------------- def IntradayScreeningCriteriaMet(self): ## If we have positive momentum if (self.momentum.Current.Value > 0): ## Informative message that will be submitted as order notes self.OpenPositionMessage = f"OPEN (${round(self.lastDailyCloseWindow[0],3)} > EMA: {round(self.emaWindow[0],3)})" return True return False ## Trade Exit criteria. Called by the main algorithm. ## Returns true if exit conditions are met. ## Replace with your own criteria. ## --------------------------------------------------- def ExitCriteriaMet(self): ## Exit If price is below ema if( self.lastClosePrice < self.ema.Current.Value ): self.ClosePositionMessage = f"CLOSE (${round(self.lastClosePrice,3)} < EMA: {round(self.ema.Current.Value,3)})" return True return False ## Returns true if our daily indicators are ready. ## Called from the main algo ## ----------------------------------------------- def DailyIndicatorsAreReady(self): return (self.ema.IsReady and self.lastDailyCloseWindow.IsReady) ## Returns true if our intraday indicators are ready. ## Called from the main algo ## -------------------------------------------------- def IntradayIndicatorsAreReady(self): return (self.momentum.IsReady) ## Called by the main algorithm right after ## a position is opened for this symbol. ## ---------------------------------------- def OnPositionOpened(self): ## Register & warmup the indicators we need to track for exits self.algo.RegisterIndicator(self.symbol, self.ema, timedelta(1)) self.algo.WarmUpIndicator(self.symbol, self.ema, Resolution.Daily) ## Called by the main algorithm right after ## a position is closed for this symbol. ## ---------------------------------------- def OnPositionClosed(self): # cleanup pass
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################################## # # SymbolData Class # ################################## class SymbolData(): ## Constructor ## ----------- def __init__(self, theSymbol, algo): ## Algo / Symbol / Price reference self.algo = algo self.symbol = theSymbol self.lastDailyClose = None self.lastClosePrice = None ## Initialize our Indicators and rolling windows self.ema = ExponentialMovingAverage(self.algo.dailyEMAPeriod) self.momentum = MomentumPercent(self.algo.hourlyMomPeriod) self.lastDailyCloseWindow = RollingWindow[float](2) self.emaWindow = RollingWindow[float](2) ## These will hold our 'messages' used in our order notes self.ClosePositionMessage = "" self.OpenPositionMessage = "" ## Seed Daily indicators with history. ## ----------------------------------- def SeedDailyIndicators(self, dailyHistory): # Loop over the history data and update our indicators if dailyHistory.empty or 'close' not in dailyHistory.columns: # self.algo.Log(f"No Daily history for {self.symbol}") return else: for timeIndex, dailyBar in dailyHistory.loc[self.symbol].iterrows(): self.ema.Update(timeIndex, dailyBar['close']) self.lastDailyClose = dailyBar['close'] self.timeOflastDailyClose = timeIndex self.lastDailyCloseWindow.Add(dailyBar['close']) self.emaWindow.Add(self.ema.Current.Value) ## Seed intraday indicators with history ## These indicators might be have eitehr hourly or minute resolution ## ----------------------------------------------------------------- def SeedIntradayIndicators(self, hourlyHistory=None, minuteHistory=None): # Loop over the history data and update our indicators if hourlyHistory is not None: if hourlyHistory.empty or 'close' not in hourlyHistory.columns: self.algo.Log(f"Missing hourly history for {self.symbol}") else: for timeIndex, hourlyBar in hourlyHistory.loc[self.symbol].iterrows(): self.momentum.Update(timeIndex, hourlyBar['close']) # If you are using minuteHistory, you need to add "someIndicator" to manage it in this class (in __init__()) if minuteHistory is not None: if minuteHistory.empty or 'close' not in minuteHistory.columns: self.algo.Log(f"Missing minute history for {self.symbol}") else: for timeIndex, minuteBar in minuteHistory.loc[self.symbol].iterrows(): if self.someIndicator is not None: self.someIndicator.Update(timeIndex, minuteBar['close']) return ## Daily screening criteria. Called by the main algorithm. ## Returns true if daily screening conditions are met. ## Replace with your own criteria. ## ------------------------------------------------------- @property def DailyScreeningCriteriaMet(self): ## Price is above ema. if self.lastDailyCloseWindow[0] > self.emaWindow[0]: return True return False ## Intraday screening criteria. Called by the main ## algorithm. Returns true if entry conditions are met. ## Replace with your own criteria. ## ---------------------------------------------------- @property def IntradayScreeningCriteriaMet(self): ## If we have positive momentum if self.momentum.Current.Value > 0: ## Informative message that will be submitted as order notes self.OpenPositionMessage = f"OPEN (${round(self.lastDailyCloseWindow[0],3)} > EMA: {round(self.emaWindow[0],3)})" return True return False ## Trade Exit criteria. Called by the main algorithm. ## Returns true if exit conditions are met. ## Replace with your own criteria. ## --------------------------------------------------- @property def ExitCriteriaMet(self): ## Exit If price is below ema if self.lastClosePrice < self.ema.Current.Value: self.ClosePositionMessage = f"CLOSE (${round(self.lastClosePrice,3)} < EMA: {round(self.ema.Current.Value,3)})" return True return False ## Returns true if our daily indicators are ready. ## Called from the main algo ## ----------------------------------------------- @property def DailyIndicatorsAreReady(self): return self.ema.IsReady and self.lastDailyCloseWindow.IsReady ## Returns true if our intraday indicators are ready. ## Called from the main algo ## -------------------------------------------------- @property def IntradayIndicatorsAreReady(self): return self.momentum.IsReady ## Called by the main algorithm right after ## a position is opened for this symbol. ## ---------------------------------------- def OnPositionOpened(self): ## Register & warmup the indicators we need to track for exits self.algo.RegisterIndicator(self.symbol, self.ema, timedelta(1)) self.algo.WarmUpIndicator(self.symbol, self.ema, Resolution.Daily) ## Called by the main algorithm right after ## a position is closed for this symbol. ## ---------------------------------------- def OnPositionClosed(self): # cleanup pass
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