// The first AI agent to trade on real markets via Robinhood.

Warrenn.
Autonomous Alpha.

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An AI agent that analyzes markets, executes trades,
and grows wealth — all onchain, all transparent,
all through Robinhood.
Not a bot. A market participant.

Read the Docs →Follow on X

// Lifecycle

Awareness

Accumulation

Autonomous Trading

Wealth Expansion

Community grows.
Narrative builds.

$WARRENN accrues
treasury.

AI begins live
trading via Robinhood.

Compounds capital.
Expands into new markets.

// Manifesto

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Markets are for everyone.
Warrenn is a step toward a more open, autonomous financial future —
where AI works for the many, not the few.
This is just the beginning.

Trade smarter. Together.

Warrenn · core (Robinhood)

1# Warrenn core trading logic (Robinhood)
2from robin_stocks import robinhood as r
3import pandas as pd
4import time
5
6# Login (uses env variables)
7r.login(
8    username=os.getenv("ROBINHOOD_USERNAME"),
9    password=os.getenv("ROBINHOOD_PASSWORD")
10)
11
12def get_market_data(symbol: str):
13    """Fetch recent market data from Robinhood."""
14    data = r.stocks.get_stock_historicals(
15        symbol,
16        interval="5minute",
17        span="day"
18    )
19    return pd.DataFrame(data)
20
21def analyze(symbol: str):
22    """Simple momentum strategy (placeholder)."""
23    df = get_market_data(symbol)
24    if len(df) < 10:
25        return None
26    df["close"] = df["close"].astype(float)
27    ma_short = df["close"].rolling(5).mean().iloc[-1]
28    ma_long = df["close"].rolling(20).mean().iloc[-1]
29    if ma_short > ma_long:
30        return "buy"
31    elif ma_short < ma_long:
32        return "sell"
33    return "hold"
34
35def execute_trade(symbol: str, action: str, quantity: int = 1):
36    """Execute a trade through Robinhood."""
37    if action == "buy":
38        r.orders.order_buy_market(symbol, quantity)
39    elif action == "sell":
40        r.orders.order_sell_market(symbol, quantity)
41    print(f"Executed {action} for {quantity} shares of {symbol}")
42

Warrenn.Autonomous Alpha.

Warrenn.
Autonomous Alpha.