The following examples demonstrate some common practices for dataless scheduled universes.
-The following example directly download a dataframe file from dropbox, in which its only column contains a list of equity to be included in the universe on that day with the date as index. The dataless scheduled universe can then retrieve the required equities from that day.
+public class DatalessScheduledUniverseExampleAlgorithm : QCAlgorithm
+{
+ // A dictionary of date-stock list pairs for easy access.
+ private Dictionary<DateTime, string> _selections = new();
+ private List<Symbol> _universe = new();
+
+ public override void Initialize()
+ {
+ SetStartDate(2015, 1, 1);
+
+ // To download the list of stocks to be included in the universe of each day, make sure you set "dl=1" for dropbox links.
+ var file = Download("https://www.dropbox.com/scl/fi/fbrxitk4ec3w91nse1raa/df.csv?rlkey=7r042rukzkthp7y1srloyhkov&st=5r4sdfwd&dl=1");
+ // Map into a dictionary of date-stock list pairs for easy access. Remember to skip the header row
+ foreach (var line in file.Split('\n').Skip(1))
+ {
+ // Skip empty line
+ if (line.IsNullOrEmpty())
+ {
+ continue;
+ }
+
+ // CSV entry items are split by comma.
+ var items = line.Split(',');
+
+ var date = Parse.DateTimeExact(items[0], "yyyy-MM-dd").Date;
+ _selections[date] = String.Join(',', items.Skip(1));
+ }
+
+ // Daily weight signals from our custom universe data only requires daily resolution to trade with.
+ UniverseSettings.Resolution = Resolution.Daily;
+ // Filter using the custom dataset, our sample data is by daily basis.
+ AddUniverse(
+ new ScheduledUniverse(
+ DateRules.EveryDay(),
+ TimeRules.At(8, 0),
+ (dt) => {
+ // Check if the date is in the selection dictionary with stocks selection, return empty list if not.
+ if (!_selections.TryGetValue(dt.Date, out var stockListString))
+ {
+ return Enumerable.Empty<Symbol>();
+ }
+
+ // The stock list is in string format that each stock is split by ",".
+ _universe = stockListString.Split(',')
+ // All selections in list are US Equity.
+ .Select(x => QuantConnect.Symbol.Create(x, SecurityType.Equity, Market.USA))
+ .ToList();
+ return _universe;
+ }));
+ }
+
+ public override void OnData(Slice slice)
+ {
+ var universeCount = _universe.Count;
+
+ // Invest equally to evenly dissipate capital risk. Since the resolution is daily, there is no issue for over rebalancing.
+ SetHoldings(_universe.Select(symbol => new PortfolioTarget(symbol, 1m / universeCount)).ToList());
+ }
+
+ public override void OnSecuritiesChanged(SecurityChanges changes)
+ {
+ // Liquidate the remove securities to free margin.
+ foreach (var removed in changes.RemovedSecurities)
+ {
+ Liquidate(removed.Symbol);
+ }
+ }
+}
+ from AlgorithmImports import *
+from io import StringIO
+
+class DatalessScheduledUniverseExampleAlgorithm(QCAlgorithm):
+
+ def initialize(self) -> None:
+ self.set_start_date(2015, 1, 1)
+
+ # To download the list of stocks to be included in the universe of each day, make sure you set "dl=1" for dropbox links.
+ file = self.download("https://www.dropbox.com/scl/fi/fbrxitk4ec3w91nse1raa/df.csv?rlkey=7r042rukzkthp7y1srloyhkov&st=5r4sdfwd&dl=1")
+ # Map into a dictionary of date-stock list pairs for easy access.
+ df = pd.read_csv(StringIO(file), index_col=0).iloc[:, 0]
+ df.index = pd.to_datetime(df.index).date
+ self.selections = df.to_dict()
+
+ # Daily weight signals from our custom universe data only requires daily resolution to trade with.
+ self.universe_settings.resolution = Resolution.DAILY
+ # Filter using the custom dataset, our sample data is by daily basis.
+ self.add_universe(
+ ScheduledUniverse(
+ self.date_rules.every_day(),
+ self.time_rules.at(8, 0),
+ self._select_symbols
+ ))
+
+ def _select_symbols(self, dt: datetime) -> List[Symbol]:
+ # Check if the date is in the selection dictionary with stocks selection, return empty list if not.
+ date = dt.date()
+ if date not in self.selections:
+ return []
+
+ self._universe = [
+ # All selections in list are US Equity.
+ Symbol.create(x, SecurityType.EQUITY, Market.USA)
+ # The stock list is in string format that each stock is split by ","
+ for x in self.selections[date].split(",")
+ ]
+ return self._universe
+
+ def on_data(self, slice: Slice) -> None:
+ # Invest equally to evenly dissipate capital risk. Since the resolution is daily, there is no issue for over rebalancing.
+ self.set_holdings([
+ PortfolioTarget(symbol, 1./len(self._universe)) for symbol in self._universe
+ ])
+
+ def on_securities_changed(self, changes: SecurityChanges) -> None:
+ # Liquidate the remove securities to free margin.
+ for removed in changes.removed_securities:
+ self.liquidate(removed.symbol)
+The following example selects SPY on the last month of each quarter. For the remaining months, it selects no assets.
public class DatalessScheduledUniverseDemoAlgorithm : QCAlgorithm @@ -38,7 +160,7 @@Example 1: Quarter End Selection
return []
Standard Options expire at end of the third week of each month. The following algorithm selects VIX-related products on the third week to trade the foreseeable increasing volatility:
public class DatalessScheduledUniverseDemoAlgorithm : QCAlgorithm @@ -63,7 +185,7 @@Example 2: Third Week VIX
} _month = dt.Month; _week = 0; - return Enumerable.Empty(); + return Enumerable.Empty<Symbol>(); } )); }