Live deploy cannot display information such as Net Profit, PSR, Return properly

Hi Trader! It’s common for some statistics—like Net Profit, PSR, and Return—to be missing or not displayed correctly during live deployments in QuantConnect. Here’s why this happens and what you can do about it:

Why Are Live Statistics Missing or Incomplete?

• Live Data Limitations: Advanced statistics such as PSR and some return calculations require complete, clean, and historical point-in-time equity and trade data. In live deployment, data can have lags, can be partial, or there may be interruptions from brokerage feeds, all of which affect calculations.
• API and Brokerage Differences: The live trading environment gets order fills, price updates, and other key data via integrated broker APIs. If there are data delays, dropped messages, or interruptions, QuantConnect’s live server can’t reliably calculate stats that are simple in backtesting where everything is simulated and perfectly “known.”
• Platform Limitations: Some statistics, particularly those requiring full trade history (like PSR or certain drawdown analytics), aren’t currently supported in live view due to these data reliability issues.

What You Can (and Can’t) Do:

1. Default Statistics: You can only expect a subset of basic statistics (like current equity, cash, and holdings) in live mode. Advanced stats will usually show as N/A or be missing.
2. Custom Runtime Statistics: If you want to track specific metrics or stats in live trading, you can use self.set_runtime_statistic('Your Metric', 'Value') in your algorithm’s OnData. This lets you display live-calculated custom values in the Results pane.
   • For example:

     def on_data(self, data):
         self.set_runtime_statistic('PnL', str(self.portfolio.total_profit))
     

Example Live Algorithm Snippet

def on_data(self, data):
    self.set_runtime_statistic('Net Profit', str(self.portfolio.total_profit))
    self.set_runtime_statistic('Return', f"{self.portfolio.total_return:.2%}")
    # (Calculate PSR or similar custom metrics here if needed)

Tips:

• Don’t rely on live Net Profit/PSR/Return for final evaluations—run a backtest for proper statistics.
• For critical stats, build your own calculations and update them via set_runtime_statistic.
• If you experience widespread missing data or errors, check your brokerage connection and ensure there are no feed or connectivity issues.

If you need a code example for custom stat tracking or have a specific metric you’d like to display, let me know!

Sources: Charting and Logging - QuantConnect.com, Runtime Statistics - QuantConnect.com, Live Analysis - QuantConnect.com, Algorithm Statistics - QuantConnect.com, Results - QuantConnect.com