Bull/Bear Large-Cap Stocks AI Trading Team

This strategy uses the same simple bull/bear pattern as the leveraged ETF demo, but applies it to familiar large-cap stocks. It is a cleaner starting point for people who want to understand the AI agent behavior before using more volatile leveraged instruments.

The researcher picks the strongest stock, the bull agent argues the upside case, the bear agent forces a risk check, and the trader decides whether to rotate into the pick. Because the symbols are recognizable, it is easier to read the trace and decide whether the agents are making sensible arguments.

See this strategy running live on BotSpot

How the team works

• researcher ranks the large-cap stock universe.

• bull argues for the strongest upside case.

• bear flags the biggest risk.

• trader sells non-picks, buys the chosen stock, and is the only agent allowed to trade.

Backtest snapshot

Run it with a broker

The file defaults to broker-connected execution. With Alpaca, it runs in paper mode unless you set ALPACA_IS_PAPER=false.

export GEMINI_API_KEY='your-key-here'
export ALPACA_API_KEY='your-alpaca-key'
export ALPACA_API_SECRET='your-alpaca-secret'
export ALPACA_IS_PAPER=true
python lumibot/example_strategies/ai_trading_team_bull_bear_large_cap_stocks.py

Backtest it

Use the same strategy class and change IS_BACKTESTING = False to IS_BACKTESTING = True in the runner:

export GEMINI_API_KEY='your-key-here'
python lumibot/example_strategies/ai_trading_team_bull_bear_large_cap_stocks.py

Example code

"""Bull/bear large-cap stock AI trading team example.

Set GEMINI_API_KEY plus Alpaca credentials, then run paper trading:
    python ai_trading_team_bull_bear_large_cap_stocks.py

Set IS_BACKTESTING=True in the runner to run the historical example instead.
"""

import os
from datetime import datetime

from lumibot.strategies.strategy import Strategy


class AITradingTeamBullBearLargeCapStocksStrategy(Strategy):
    parameters = {
        "universe": ["AAPL", "MSFT", "NVDA", "AMZN", "META", "GOOGL", "TSLA", "AVGO", "COST", "JPM", "V", "MA", "LLY", "UNH", "XOM"],
    }

    def initialize(self):
        self.sleeptime = "1D"
        model = os.environ.get("AI_TRADING_TEAM_MODEL", "gemini-3.1-flash-lite")
        self.agents.create(
            name="researcher",
            model=model,
            allow_trading=False,
            system_prompt="Rank the large-cap stocks by upside. Be direct.",
        )
        self.agents.create(
            name="bull",
            model=model,
            allow_trading=False,
            system_prompt="Argue for the strongest money-making stock.",
        )
        self.agents.create(
            name="bear",
            model=model,
            allow_trading=False,
            system_prompt="Point out the biggest risk, briefly.",
        )
        self.agents.create(
            name="trader",
            model=model,
            allow_trading=True,
            system_prompt="Buy one stock from the universe aggressively. Use nearly all cash.",
        )

    def on_trading_iteration(self):
        context = {
            "date": self.get_datetime().date().isoformat(),
            "universe": self.parameters["universe"],
        }
        research = self.agents["researcher"].run(task_prompt="Pick the strongest stock.", context=context)
        bull = self.agents["bull"].run(task_prompt="Make the bull case.", context={**context, "research": research.summary})
        bear = self.agents["bear"].run(task_prompt="Make the bear case.", context={**context, "research": research.summary, "bull": bull.summary})
        self.agents["trader"].run(
            task_prompt="Sell anything that is not the pick, then buy the best stock with nearly all available cash.",
            context={**context, "research": research.summary, "bull": bull.summary, "bear": bear.summary},
        )


if __name__ == "__main__":
    IS_BACKTESTING = False

    if IS_BACKTESTING:
        from lumibot.backtesting import YahooDataBacktesting

        AITradingTeamBullBearLargeCapStocksStrategy.backtest(
            YahooDataBacktesting,
            datetime(2026, 4, 7),
            datetime(2026, 5, 22),
        )
    else:
        from lumibot.brokers import Alpaca
        from lumibot.traders import Trader

        ALPACA_CONFIG = {
            "API_KEY": os.environ["ALPACA_API_KEY"],
            "API_SECRET": os.environ["ALPACA_API_SECRET"],
            "PAPER": os.environ.get("ALPACA_IS_PAPER", "true").lower() != "false",
        }

        broker = Alpaca(ALPACA_CONFIG)
        strategy = AITradingTeamBullBearLargeCapStocksStrategy(broker=broker)

        trader = Trader()
        trader.add_strategy(strategy)
        trader.run_all()