Issue with Running Copy Congress Trades in Live Mode

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Issue with Running Copy Congress Trades in Live Mode

Last comment by - September 2024

Issue with Running Copy Congress Trades in Live Mode

Live trading issue: RabbitMQ error "RESOURCE_LOCKED" prevents symbol list retrieval.

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Issue with Running Copy Congress Trades in Live Mode

Laurentiu Raducu | September 2024

I am trying to run the following algorithm live:

However, I am getting a weird error about rabbitMQ, which seems to be related to an internal implementation of LEAN:

Topology recovery exception: RabbitMQ.Client.TopologyRecoveryException: Caught an exception while recovering queue Command-306354.L-7c5e1b171b5c59af23cac3145463569b_master-e893e67-019b57f: The AMQP operation was interrupted: AMQP close-reason, initiated by Peer, code=405, text="RESOURCE_LOCKED - cannot obtain exclusive access to locked queue 'Command-306354.L-7c5e1b171b5c59af23cac3145463569b_master-e893e67-019b57f' in vhost '/'", classId=50, methodId=10, cause=

This seems to make the algorithm fail when trying to fetch the list of symbols, which is always of None type.
Did anyone experience anything like this?

Author

Laurentiu Raducu

September 2024

Upvote

Mia Alissi INVESTOR

September 2024

from datetime import timedelta
from AlgorithmImports import *
class LeveragedCopyCongressAlgorithm(QCAlgorithm):
    def initialize(self):
        self.set_start_date(2020, 1, 1)
        self.set_cash(100000)
        self._universe = self.add_universe(
            self.coarse_selection_function,
            self.fine_selection_function
        )
        spy = Symbol.create('SPY', SecurityType.EQUITY, Market.USA)
        self.schedule.on(self.date_rules.week_start(spy), self.time_rules.after_market_open(spy, 30), self._trade)
    def coarse_selection_function(self, coarse):
        return [c.symbol for c in coarse if c.has_fundamental_data]
    def fine_selection_function(self, fine):
        return [f.symbol for f in fine if f.some_criteria]  # Adjust criteria as needed
    def _trade(self):
        symbols = list(self._universe.selected)
        if len(symbols) == 0:
            return
        inv_volatility_by_symbol = 1 / self.history(symbols, timedelta(days=180), Resolution.DAILY)['close'].unstack(0).pct_change().iloc[1:].std()
        targets = [
            PortfolioTarget(symbol, min(0.1, 1.5 * (inv_volatility_by_symbol[symbol] / inv_volatility_by_symbol.sum())))
            for symbol in symbols
            if symbol in inv_volatility_by_symbol
        ]
        self.set_holdings(targets)
+ Expand
- Collapse

Sources: Copying Congress Trades, Debugging - QuantConnect.com, Scheduled Queuing Algorithm

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Author:

September 2024

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