How can I pull most active stocks from my alpaca paper trading account

To add stocks and options to your universe based on criteria such as the most active stocks, you can use the add_universe and add_universe_options methods in QuantConnect. Here's a step-by-step guide to help you implement this in your algorithm:

Step 1: Initialize Your Algorithm

Set up your algorithm with the necessary start and end dates, initial cash, and universe settings.

class MyAlgorithm(QCAlgorithm):
    def initialize(self):
        self.set_start_date(2020, 1, 1)
        self.set_end_date(2020, 12, 31)
        self.set_cash(100000)
        self.universe_settings.resolution = Resolution.DAILY
        self.add_universe(self.select_stocks)

Step 2: Define Stock Selection Criteria

Create a selection function that filters stocks based on your criteria, such as daily dollar volume or P/E ratio.

    def select_stocks(self, coarse):
        # Sort by daily dollar volume and select top 10
        sorted_by_volume = sorted(coarse, key=lambda x: x.dollar_volume, reverse=True)
        return [x.symbol for x in sorted_by_volume[:10]]

Step 3: Add Options to Your Universe

Use the add_universe_options method to include options for the selected stocks.

        self.add_universe_options(self.select_stocks, self.option_filter)

    def option_filter(self, universe):
        return universe.include_weeklys().strikes(-1, 1).expiration(timedelta(0), timedelta(30))

Step 4: Implement Data Handling

Use the on_data method to handle incoming data and manage your portfolio.

    def on_data(self, data):
        if not self.portfolio.invested:
            for symbol in data.keys():
                self.set_holdings(symbol, 0.1)

Step 5: Respond to Universe Changes

Implement the on_securities_changed method to adjust your holdings based on changes in the universe.

    def on_securities_changed(self, changes):
        for removed in changes.removed_securities:
            if removed.invested:
                self.liquidate(removed.symbol)
        for added in changes.added_securities:
            self.set_holdings(added.symbol, 1 / len(changes.added_securities))

This setup will allow you to dynamically select stocks and options based on your specified criteria and manage your portfolio accordingly. Adjust the selection criteria and option filters as needed to align with your trading strategy.

Sources: Dropbox Base Data Universe Selection Algorithm, User Defined Universe Algorithm, Add Universe Selection Model Algorithm, Basic Template Options Filter Universe Algorithm, Fundamental Universe Selection Algorithm

Hi Manoj Kandlikar ,

If Alpaca has a REST API that provides the list of stocks, you can use:

content = self.download(<url-to-alpaca-endpoint>) 

Parse current, which is a string, to the tickers, and call add_equity. You will have to remove the securities at some point too. Say that content is “SPY\nAAPL\nMSFT”, then

def add_active_stocks(self):
    content = self.download(<url-to-alpaca-endpoint>)
    self._symbols = [] 
    for ticker in content.split('\n'):
        self._symbol.append(self.add_equity(ticker).symbol)
        
def remove_active_stocks(self):
    for symbol in self._symbols:
        self.remove_security(symbol)

Best regards,
Alex