Total Portfolio Market value

Here’s the guidance and an example code that could help 'Dharmesh':

Yes, in QuantConnect, the property self.Portfolio.TotalPortfolioValue (or, if accessing from a different class, self.algorithm.Portfolio.TotalPortfolioValue) is the correct and recommended way to get your current total portfolio market value both in live trading and backtesting.

• In live trading, this value is automatically kept in sync with your brokerage account and reflects the actual total value of all your holdings plus your available cash.
• In backtesting, it is updated based on the simulated trades and price changes.

You do not need to call any special broker sync function—QuantConnect’s platform ensures TotalPortfolioValue is current. Rounding, as shown, is perfectly fine for logging or display.

Here’s an example of its use and optional live mode check:

from AlgorithmImports import *

class TotalPortfolioValueExample(QCAlgorithm):
    def initialize(self) -> None:
        """
        - self.portfolio.total_portfolio_value is the correct property to check your total portfolio value.
        - In live trading, this property reflects the actual brokerage portfolio value.
        - In backtesting, it uses the simulated portfolio value.
        """
        # Set start and end dates for the backtest
        # (In live trading, these are ignored, but must still be set)
        self.set_start_date(2021, 1, 1)
        self.set_end_date(2022, 1, 1)

        # Set initial cash
        # In backtesting, this is the starting portfolio value; in live trading, your actual brokerage balance is used
        self.set_cash(100000)

        # Add a symbol for data (required by the scheduler below)
        self._spy = self.add_equity("SPY", Resolution.DAILY).symbol

        # Schedule a function to log the portfolio value every day at noon
        self.schedule.on(
            self.date_rules.every_day(self._spy),
            self.time_rules.noon,
            self.log_total_portfolio_value
        )

    def log_total_portfolio_value(self) -> None:
        """
        Logs your total portfolio market value each day at noon.
        """
        portfolio_value = self.portfolio.total_portfolio_value
        rounded_value = round(portfolio_value, 2)

        # Optionally check if we are in live mode
        if self.live_mode:
            self.debug(f"(Live Mode) Total Portfolio Value: ${rounded_value}")
        else:
            self.debug(f"(Backtest Mode) Total Portfolio Value: ${rounded_value}")

Key point:
self.Portfolio.TotalPortfolioValue will return the broker-synced value in live mode and the simulated value in backtests. Your line:

current_portfolio_value = round(self.algorithm.portfolio.total_portfolio_value)

is correct for obtaining the total portfolio market value in either case.

Sources: Ordering - QuantConnect.com