Hi, how can we add other stocks to the algorithm taught on bootcamp, i tried to reproduce the algorithme using 2 stocks but it doesn't return me anything.Can someone help me to fix the problem?

Thank you

class FadingTheGap(QCAlgorithm): def Initialize(self): self.SetStartDate(2017, 11, 1) self.SetEndDate(2018, 7, 1) self.SetCash(100000) self.tickers=["FB","TSLA"] for ticker in self.tickers: self.AddEquity(ticker, Resolution.Minute) self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.BeforeMarketClose(ticker, 0), self.ClosingBar) self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.AfterMarketOpen(ticker, 1), self.OpeningBar) self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.AfterMarketOpen(ticker, 45), self.ClosePositions) self.volatility = StandardDeviation(ticker, 60) self.window = RollingWindow[TradeBar](2) def OnData(self, data): for ticker in self.tickers: if data[ticker] is not None: #2. Update our standard deviation indicator manually with algorithm time and TSLA's close price self.volatility.Update(self.Time, data[ticker].Close) def OpeningBar(self): for ticker in self.tickers: if self.CurrentSlice[ticker] is not None: self.window.Add(self.CurrentSlice[ticker]) #3. Use IsReady to check if both volatility and the window are ready, if not ready 'return' for ticker in self.tickers: if not self.window.IsReady or not self.volatility.IsReady: return for ticker in self.tickers: delta = self.window[0].Open - self.window[1].Close #4. Save an approximation of standard deviations to our deviations variable by dividing delta by the current volatility value: for ticker in self.tickers: deviations = delta / self.volatility.Current.Value for ticker in self.tickers: if deviations < -3: self.SetHoldings(ticker, 1) def ClosePositions(self): for ticker in self.tickers: self.Liquidate(ticker) def ClosingBar(self): for ticker in self.tickers: self.window.Add(self.CurrentSlice[ticker])