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I am learning to use the “Algorithm Framework” where I found an example of creating symbols to create a manual universe selection model from the documentation.
Now I am trying to create a custom data source using a pre-saved CSV file, and below is the main algorithm initialise method:
def Initialize(self):
self.SetStartDate(2018, 7, 1)
self.SetEndDate(2019, 3, 31)
self.SetCash(100000)
self.UniverseSettings.Resolution = Resolution.Daily
self.UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw
# -------------------- to use Custom Data class ----------------------
self.symbols: List[Symbol] = []
symbol_str: List[str] = ["GLD", "GDX"]
for sym in symbol_str:
# Manual universes doesn't work with custom data
# See https://github.com/QuantConnect/Lean/blob/master/Algorithm/Selection/ManualUniverseSelectionModel.py
self.symbols.append(self.AddData(MyCustomDataClass, ticker=sym, resolution=self.UniverseSettings.Resolution).Symbol)
# TODO Set Benchmark
# self.SetBenchmark(self.symbol)
self.AddUniverseSelection(ManualUniverseSelectionModel(self.symbols))It turns out that in the Alpha Model, in OnSecuritiesChanged, the changes.AddedSecurities is an empty list.
However, if I use the “classic style” algorithm using self.AddData method, I can see the added securities.
Here are my two questions:
- Does ManualUniverseSelectionModel support custom data symbols?
2. If not, how can I write a custom ManualUniverseSelectionModel to achieve the same result as using self.AddData(CustomDataClass, <name>, resolution). (And is it even worth it)?
Alexandre Catarino
Hi Bella Yousefi ,
The OnSecuritesChanged method does not receive events of addition or removal of custom data.
I don't think you should write a custom selection model for custom data. Generally, custom data is used to create insights, so we can add them directly to the Alpha Model:
However, if the custom data is market data as it seems in your case, it's not worth creating a Selection Model.
Best regards,
Alex
Bella Yousefi
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