2019 to Present | Large Cap | Long | Smart Beta | CAGR 68% | Leveraged

Why doesn't the Algo gragh work? Refer to to Overall Stats tab. Here's a screenshot.

The provided code has several issues that need to be addressed:

1. Attribute Errors:

   • Time should be accessed using self.Time.
   • INVESTED, IS_SHORT, and IS_LONG should be accessed using lowercase invested, is_short, and is_long.

2. History Method Overload:

   • The history method call is incorrect. Ensure that the parameters match one of the overload variants provided in the error message.

3. Type Mismatch:

   • The assignment of a list to self.trades_by_price_date_shares_symbol, which is expected to be a dictionary, needs correction.

These errors need to be fixed to ensure the code runs correctly.

Sources: Stock Selection Strategy Based On Fundamental Factors, Momentum Short Term Reversal Strategy, Bybit Crypto Futures Regression Algorithm, Asset Growth Effect, Upcoming Holiday Momentum for Amazon

To troubleshoot why the algorithm graph isn't working, let's go through the key steps required for proper charting in QuantConnect:

1. Chart Initialization: Ensure that you have initialized your charts correctly using the Chart object and added them to the algorithm with self.add_chart(chart). For example:

   stock_plot = Chart("Trade Plot")
   self.add_chart(stock_plot)
   

2. Series Addition: Confirm that each chart has the necessary series added using the Series object and chart.add_series(series). For example:

   stock_plot.add_series(Series("Buy", SeriesType.SCATTER, 0))
   stock_plot.add_series(Series("Sell", SeriesType.SCATTER, 0))
   stock_plot.add_series(Series("Price", SeriesType.LINE, 0))
   

3. Plot Calls: Check your self.plot(chart_name, series_name, value) calls to ensure they are correctly referencing existing chart and series names. For example:

   self.plot("Trade Plot", "Buy", self.last_price)
   

4. Reserved Names: Make sure that the chart and series names do not conflict with any reserved names. Avoid using names like "Equity", "Return", "Benchmark", etc., for custom charts.

5. Data Availability: Ensure that the data being plotted is available and correctly processed before calling the plot method. If the data is not available, the plot will not update.

6. Review Logs for Errors: Check the algorithm logs for any errors or warnings related to charting or data processing. This can provide insights into what might be going wrong.

By following these steps, you should be able to identify and fix the issue with the algorithm graph not displaying as expected. If you need further assistance, please provide more details about the specific charting code or any error messages you are encountering.

Sources: Charting - QuantConnect.com, Custom Charting Algorithm, Logging and Plotting - QuantConnect.com, Object Store - QuantConnect.com

you answer without understanding context. I wasn't saying the algo didn't chart. It did. However, providing the backtest did not pull the chart into the discussion.

This AI troll steals my thunder with meaningless suggestions. The point of my post is - the model performs different  over the same sample period. Two weeks ago it performed with astronomical returns, now it is average. makes no sense. Only bots care these days….