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I have been practicing making alpha model with shared project in this community.
I would like to add alpha model but I keep having error message.
"Runtime Error: TypeError : iteration over non-sequence TypeError : iteration over non-sequence"
This is "main.py" file.
import pandas as pd
from SpyTrendAlphaModel import SpyTrendAlphaModel
class MultidimensionalTransdimensionalPrism(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2020, 2, 1) # Earliest start date for all ETFs in universe 2/1/10
self.SetEndDate(2020, 5, 6)
self.SetCash(10000)
symbols = [ Symbol.Create("UST", SecurityType.Equity, Market.USA), Symbol.Create("TQQQ", SecurityType.Equity, Market.USA), Symbol.Create("UBT", SecurityType.Equity, Market.USA)]
self.SetUniverseSelection(ManualUniverseSelectionModel(symbols))
self.SetAlpha(SpyTrendAlphaModel())
self.SetRiskManagement(CompositeRiskManagementModel(
MaximumUnrealizedProfitPercentPerSecurity(0.2),
MaximumDrawdownPercentPerSecurity(0.3)
))
self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
self.SetExecution(NullExecutionModel())
and this is "SpyTrendAlphaModel.py" file.
class SpyTrendAlphaModel(AlphaModel):
def __init__(self):
pass
def OnSecuritiesChanged(self, algorithm, changes):
self.symbols = [x.Symbol for x in changes.AddedSecurities]
def Update(self, algorithm, data):
for x in self.symbols:
history = algorithm.History(x, 7, Resolution.Daily)
price = history["close"]
TF_3 = price.pct_change(3)[-1]
if TF_3 > 0:
return Insight.Price(price.index[0][0], timedelta(1), InsightDirection.Up)
else :
return Insight.Price(price.index[0][0], timedelta(1), InsightDirection.Down)
because of the error I could not attach my backtest.
I would appreciate somebody help me to figure out why I keep getting error msg.
Thanks!
Rahul Chowdhury
Hi Juhwan,
The Update method in the AlphaModel must return a list of insights. The portfolio construction model iterates through this list of insights to create portfolio targets. Let's define an empty list and append the insights we create to that list.
def Update(self, algorithm, data): insights = [] for x in self.symbols: history = algorithm.History(x, 7, Resolution.Daily) price = history["close"] TF_3 = price.pct_change(3)[-1] if TF_3 > 0: insights.append(Insight.Price(price.index[0][0], timedelta(1), InsightDirection.Up)) else : insights.append(Insight.Price(price.index[0][0], timedelta(1), InsightDirection.Down)) return insightsLearn more in the documentation on Alpha Creation and make sure to also check out the boot camps on the framework!
Best
Rahul
Juhwan Kim
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