Envoke AlphaModel on self.schedule.on method

To schedule your Alpha model to fetch daily data at market open (9:30 AM), you can use the self.schedule.on method in your QuantConnect algorithm. Here's how you can set it up:

1. Add the Security: Ensure you have added the necessary security to your algorithm. For example, if you're working with SPY, you can add it using:

   self.add_equity("SPY")
   

2. Schedule the Event: Use the self.schedule.on method to create a scheduled event. You'll need to specify both date and time rules.

3. Date Rule: Use self.date_rules.every_day("SPY") to ensure the event is triggered every trading day.

4. Time Rule: Use self.time_rules.after_market_open("SPY", 0) to trigger the event exactly at market open.

5. Define the Method: Create a method, such as self.fetch_daily_data, which will contain the logic to fetch daily data and generate your Alpha signal.

6. Schedule the Method: Pass the defined method as the third argument in the self.schedule.on method to execute it at the scheduled time.

Here's an example implementation:

class MyAlgorithm(QCAlgorithm):
    def initialize(self):
        self.set_start_date(2021, 1, 1)
        self.set_end_date(2021, 12, 31)
        self.set_cash(100000)

        # Add the security
        self.add_equity("SPY", Resolution.Daily)

        # Schedule the event to fetch data at market open
        self.schedule.on(
            self.date_rules.every_day("SPY"),
            self.time_rules.after_market_open("SPY", 0),
            self.fetch_daily_data
        )

    def fetch_daily_data(self):
        # Logic to fetch daily data and generate Alpha signal
        self.log(f"Fetching daily data at market open: {self.time}")
        # Example: Check conditions and place orders
        if some_condition:
            self.set_holdings("SPY", 1)

Make sureTo schedule your Alpha model to fetch daily data at market open (9:30 AM), you can use the self.schedule.on method in your QuantConnect algorithm. Here's how you can set it up:

1. Add the Security: Ensure you have added the necessary security to your algorithm. For example, if you're working with SPY, you can add it using:

   self.add_equity("SPY")
   

2. Schedule the Event: Use the self.schedule.on method to create a scheduled event. You'll need to specify both date and time rules.

3. Date Rule: Use self.date_rules.every_day("SPY") to ensure the event is triggered every trading day.

4. Time Rule: Use self.time_rules.after_market_open("SPY", 0) to trigger the event exactly at market open.

5. Define the Method: Create a method, such as self.fetch_daily_data, which will contain the logic to fetch daily data and generate your Alpha signal.

6. Schedule the Method: Pass the defined method as the third argument in the self.schedule.on method to execute it at the scheduled time.

Here's an example implementation:

class MyAlgorithm(QCAlgorithm):
    def initialize(self):
        self.set_start_date(2021, 1, 1)
        self.set_end_date(2021, 12, 31)
        self.set_cash(100000)

        # Add the security
        self.add_equity("SPY", Resolution.Daily)

        # Schedule the event to fetch data at market open
        self.schedule.on(
            self.date_rules.every_day("SPY"),
            self.time_rules.after_market_open("SPY", 0),
            self.fetch_daily_data
        )

    def fetch_daily_data(self):
        # Logic to fetch daily data and generate Alpha signal
        self.log(f"Fetching daily data at market open: {self.time}")
        # Example: Check conditions and place orders
        if some_condition:
            self.set_holdings("SPY", 1)

Make sure to replace some_condition with the actual condition you want to check before placing orders. This setup will ensure that your algorithm fetches daily data and processes it at market open, allowing you to generate signals and place orders during market hours.

Sources: Scheduled Events - QuantConnect.com, Dual Thrust Trading Algorithm, Scheduled Events Algorithm, Extended Market Trading Regression Algorithm, Market On Open On Close Algorithm

# region imports
from AlgorithmImports import *
from AlphaModel.invokeAlphaModel import invokeAlphaModel
# endregion

class DemoRlStrategy(QCAlgorithm):

    def initialize(self):
        # Locally Lean installs free sample data, to download more data please visit https://www.quantconnect.com/docs/v2/lean-cli/datasets/downloading-data
        self.set_start_date(2013, 10, 7)  # Set Start Date
        self.set_end_date(2013, 10, 11)  # Set End Date
        self.set_cash(100000)  # Set Strategy Cash
        security = self.add_equity("SPY", Resolution.Daily)
        self.symbol = security.Symbol
        # self.add_alpha(invokeAlphaModel())
        self.alpha_model_obj = invokeAlphaModel()
        self.schedule.on(
            self.date_rules.every_day(self.symbol),
            self.time_rules.after_market_open(self.symbol, 0),
            self.fetchdata
        )
    def on_data(self, data: Slice):
        
        pass
    
    def fetchdata(self):
        trade_bars = self.history[TradeBar](self.symbol, timedelta(days=1)) 
        self.alpha_model_obj.Update(self, trade_bars)

can you suggest me the code How can I update my alpha Model after market open ?
 

Hi Sukhvinder

My suggestion will be storing the 4am insight and emit at next loop of update.

class DemoRlStrategy(QCAlgorithm):
    def initialize(self):
        symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self.add_alpha(CustomAlphaModel(self, symbol))

class CustomAlphaModel(AlphaModel):
    def __init__(self, algorithm, symbol):
        algorithm.schedule.on(
            algorithm.date_rules.every_day(symbol),
            algorithm.time_rules.after_market_open(symbol, 0),
            self.fetchdata
        )
        
        self.symbol = symbol
        self.insights = []
        
    def fetchdata(self):
        trade_bars = self.history[TradeBar](self.symbol, timedelta(days=1))
        # your logic...
        self.insights.append(insight)
        
    def update(self, algorithm, slice):
        # Make sure the market is open
        if algorithm.is_market_open(self.symbol):
            # copy the insight list for insight emission
            insights = self.insights.copy()
            # clear the stored insights
            self.insights = []
            # emit the insights
            return insights

Best
Louis