Order rejected on Daily Resolution

In QuantConnect, when you place a market order while the market is closed, the LEAN engine automatically converts the order into a market-on-open order. This is most common when you use daily or hourly data, which your algorithm can receive when the market is closed. However, this behavior might not be supported by all brokerages. For example, in one of the forum discussions, a user mentioned that if they try to place a TimeInForce day order at any broker after 4pm, it would just be rejected and not be converted to a market-on-open order.

To avoid this issue, you can check if the market is open before placing an order. You can use the IsMarketOpen method in QuantConnect to check if the market is open. Here is an example in Python:

# Check market status before placing an order to avoid unintended market-on-open trades
if self.is_market_open(self._symbol):
    self.market_order(self._symbol, quantity)

If you are using a specific brokerage, you might want to check their specific rules and regulations regarding order placement when the market is closed.

Sources:

• QuantConnect Documentation
• QuantConnect Forum Discussion

let me explain my strategy,

Resolution → One Day (Daily) Resolution

Alpha Model → generate an Up/Down Signal

Portfolio Constructor → Place an order based on the Signal and Weight of the insights. I'm using inbuild EqualWeightPortfolioConstructor. 

So expecitily I'm not placing an order. It is using Portfolio Constructor for calculating Quantity and placing an order.

So basically I'm running a live code, I got data at 4:00pm when The market is just close, So based on data I generated a signal (Alpha Signal), and portfolio construction receive signal and place and order after market close, So How can I order after Market is open.

Hi Sukhvinder

An easy way to do so will be to schedule a function to place order at a certain time:

class YouBaseAlgorithm(QCAlgorithm):
    def initialize(self):
        spy = self.add_equity("SPY")
        self.add_alpha(CustomAlphaModel(self))
    
class CustomAlphaModel(AlphaModel):
    def __init__(self, algorithm):
        self.algorithm = algorithm
        self.insights = []
        # Emit insights at market open
        algorithm.schedule.on(
            algorithm.date_rules.every_day("SPY"),
            algorithm.time_rules.after_market_open("SPY", 0),
            self.order
        )
    
    def update(self):
        # you logics...
        
        # save the insights to emit afterwards
        self.insights = your_insight_list
        # emit nothing now
        return []
        
    def order(self):
        self.algorithm.emit_insights(self.insights)
        # clear the insight list after emitting
        self.insights = []

Best
Louis