How to Check if a Security is Invested in QuantConnect Using portfolio.invested

To check if your portfolio currently holds a position in a specific stock within the QuantConnect Lean engine, you should access the self.portfolio object. This object is a dictionary keyed by the security's Symbol.

Here are the primary methods to check your positions using the modern PEP8 Python API.

Method 1: The .invested Property (Recommended)

The cleanest way to check if you have any position (Long or Short) is to use the boolean property .invested.

# Check if we have any position in the symbol
if self.portfolio[self.symbol].invested:
    self.log(f"We are already invested in {self.symbol}")
else:
    self.buy(self.symbol, 10)

Method 2: Checking Quantity

If you need to know the specific size of the position or distinguish between Long and Short manually, check .quantity.

# Check if we have a specific quantity
current_qty = self.portfolio[self.symbol].quantity

if current_qty == 0:
    self.log("No position")
elif current_qty > 0:
    self.log(f"Long position of {current_qty} shares")
else:
    self.log(f"Short position of {current_qty} shares")

Method 3: Directional Helpers

QuantConnect provides helper properties to specifically check the direction of the trade.

position = self.portfolio[self.symbol]

if position.is_long:
    self.log("Currently Long")

if position.is_short:
    self.log("Currently Short")

Complete Algorithm Example

Below is a fully functional example demonstrating how to implement these checks inside the on_data method to prevent opening duplicate positions.

from AlgorithmImports import *

class PortfolioCheckAlgorithm(QCAlgorithm):

    def initialize(self):
        self.set_start_date(2023, 1, 1)
        self.set_end_date(2023, 6, 1)
        self.set_cash(100000)
        
        # Add Equity and save the Symbol object
        self.spy = self.add_equity("SPY", Resolution.DAILY).symbol

    def on_data(self, data: Slice):
        # Ensure data exists for the symbol before accessing
        if not data.contains_key(self.spy):
            return

        # 1. Check if we are NOT invested before buying
        if not self.portfolio[self.spy].invested:
            self.set_holdings(self.spy, 0.5)
            self.debug("Purchased SPY - Position Opened")
        
        # 2. Check if we are invested to manage exit logic
        else:
            # Example: Liquidate if profit is > 5%
            # unrealized_profit_percent returns a decimal (e.g., 0.05 for 5%)
            pnl_pct = self.portfolio[self.spy].unrealized_profit_percent
            
            if pnl_pct > 0.05:
                self.liquidate(self.spy)
                self.debug("Profit target hit - Position Closed")

Q&A: Portfolio Management in QuantConnect

Q: What is the difference between self.Portfolio and self.portfolio?
A: self.Portfolio is the older C#-style PascalCase naming convention. self.portfolio is the newer PEP8 snake_case convention. Both work in Python, but self.portfolio is recommended for new algorithms to ensure consistency with standard Python practices.

Q: Does self.portfolio[symbol].invested return true for pending orders?
A: No. The .invested property only returns True if the order has been filled and the asset is currently held in your holdings. To check for pending orders, you must check self.transactions.get_open_orders(symbol).

Q: How do I check if my entire portfolio is empty (100% Cash)?
A: You can check self.portfolio.invested. If this returns False, it means you hold no positions in any security and are entirely in cash.

Q: Can I check the average entry price of my position?
A: Yes. You can access self.portfolio[symbol].average_price to get the average cost basis of your current holdings.