alteregoeth-ai
629 lines
25 KiB
Python
629 lines
25 KiB
Python
#!/usr/bin/env python3
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"""
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Weather Trading Bot v2 — Polymarket
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Kelly Criterion + Expected Value simulation.
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Usage:
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python weather_bot_v2.py # Paper mode with $1000 virtual balance
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python weather_bot_v2.py --live # Real trades
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python weather_bot_v2.py --positions
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python weather_bot_v2.py --reset # Reset simulation balance
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"""
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import re
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import json
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import argparse
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import requests
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from datetime import datetime, timezone, timedelta
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# =============================================================================
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# CONFIG
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# =============================================================================
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with open("config.json") as f:
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_cfg = json.load(f)
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ENTRY_THRESHOLD = _cfg.get("entry_threshold", 0.15)
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EXIT_THRESHOLD = _cfg.get("exit_threshold", 0.45)
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MAX_TRADES = _cfg.get("max_trades_per_run", 5)
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MIN_HOURS_LEFT = _cfg.get("min_hours_to_resolution", 2)
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PRICE_DROP_SIGNAL = _cfg.get("price_drop_threshold", 0.10)
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# Kelly + EV settings
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NOAA_ACCURACY = 0.78 # NOAA forecast accuracy for 1-3 day predictions
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KELLY_FRACTION = 0.25 # Use 1/4 Kelly for safety (full Kelly is too aggressive)
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MAX_POSITION_PCT = 0.10 # Never bet more than 10% of balance on one trade
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MIN_EV = 0.05 # Minimum EV to enter (5 cents per dollar risked)
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SIM_BALANCE = 1000.0 # Starting virtual balance
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LOCATIONS = {
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"NYC": {"lat": 40.77, "lon": -73.87, "name": "New York City"},
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"Chicago": {"lat": 41.97, "lon": -87.90, "name": "Chicago"},
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"Seattle": {"lat": 47.45, "lon": -122.30, "name": "Seattle"},
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"Atlanta": {"lat": 33.64, "lon": -84.43, "name": "Atlanta"},
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"Dallas": {"lat": 32.90, "lon": -97.04, "name": "Dallas"},
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"Miami": {"lat": 25.80, "lon": -80.29, "name": "Miami"},
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}
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ACTIVE_LOCATIONS = _cfg.get("locations", "NYC,Chicago,Seattle,Atlanta,Dallas,Miami").split(",")
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ACTIVE_LOCATIONS = [l.strip() for l in ACTIVE_LOCATIONS]
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MONTHS = ["january","february","march","april","may","june",
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"july","august","september","october","november","december"]
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# =============================================================================
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# COLORS
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# =============================================================================
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class C:
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GREEN = "\033[92m"
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YELLOW = "\033[93m"
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RED = "\033[91m"
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CYAN = "\033[96m"
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GRAY = "\033[90m"
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RESET = "\033[0m"
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BOLD = "\033[1m"
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def ok(msg): print(f"{C.GREEN} ✅ {msg}{C.RESET}")
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def warn(msg): print(f"{C.YELLOW} ⚠️ {msg}{C.RESET}")
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def info(msg): print(f"{C.CYAN} {msg}{C.RESET}")
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def skip(msg): print(f"{C.GRAY} ⏸️ {msg}{C.RESET}")
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# =============================================================================
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# KELLY CRITERION + EV
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# =============================================================================
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def calculate_ev(our_prob: float, market_price: float) -> float:
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"""
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Expected Value per $1 risked.
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EV = (our_prob * payout) - (1 - our_prob) * 1
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payout = (1 / market_price) - 1 (net profit per $1 if we win)
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Example: our_prob=0.75, price=0.08
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payout = 1/0.08 - 1 = 11.5x
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EV = 0.75 * 11.5 - 0.25 = 8.375 - 0.25 = +$8.12 per $1 risked
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"""
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if market_price <= 0 or market_price >= 1:
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return 0.0
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payout = (1.0 / market_price) - 1.0
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ev = (our_prob * payout) - (1.0 - our_prob)
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return round(ev, 4)
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def calculate_kelly(our_prob: float, market_price: float) -> float:
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"""
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Kelly Criterion: optimal fraction of bankroll to bet.
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f* = (p * b - q) / b
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where:
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p = our probability of winning
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q = 1 - p (probability of losing)
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b = net odds (payout per $1 bet)
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We apply KELLY_FRACTION (0.25) for safety — fractional Kelly.
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Result is capped at MAX_POSITION_PCT (10% of balance).
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"""
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if market_price <= 0 or market_price >= 1:
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return 0.0
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b = (1.0 / market_price) - 1.0 # net odds
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p = our_prob
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q = 1.0 - p
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kelly = (p * b - q) / b
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kelly = max(0.0, kelly) # never negative
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kelly = kelly * KELLY_FRACTION # fractional Kelly
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kelly = min(kelly, MAX_POSITION_PCT) # cap at max position
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return round(kelly, 4)
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def calculate_position_size(kelly_fraction: float, balance: float) -> float:
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"""Convert Kelly fraction to dollar amount."""
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return round(kelly_fraction * balance, 2)
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# =============================================================================
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# SIMULATION STATE
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# =============================================================================
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SIM_FILE = "simulation.json"
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def load_sim() -> dict:
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try:
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with open(SIM_FILE) as f:
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return json.load(f)
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except FileNotFoundError:
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return {
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"balance": SIM_BALANCE,
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"starting_balance": SIM_BALANCE,
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"positions": {},
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"trades": [],
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"total_trades": 0,
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"wins": 0,
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"losses": 0,
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"peak_balance": SIM_BALANCE,
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}
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def save_sim(sim: dict):
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with open(SIM_FILE, "w") as f:
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json.dump(sim, f, indent=2)
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def reset_sim():
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import os
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if os.path.exists(SIM_FILE):
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os.remove(SIM_FILE)
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if os.path.exists("positions.json"):
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os.remove("positions.json")
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print(f"{C.GREEN} ✅ Simulation reset — balance back to ${SIM_BALANCE:.2f}{C.RESET}")
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# =============================================================================
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# OPEN-METEO FORECAST
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# =============================================================================
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def get_forecast(location: str) -> dict:
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loc = LOCATIONS[location]
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url = (
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f"https://api.open-meteo.com/v1/forecast"
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f"?latitude={loc['lat']}&longitude={loc['lon']}"
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f"&daily=temperature_2m_max&temperature_unit=fahrenheit&forecast_days=4"
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)
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try:
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r = requests.get(url, timeout=10)
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data = r.json()
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result = {}
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for date, temp in zip(data["daily"]["time"], data["daily"]["temperature_2m_max"]):
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result[date] = round(temp, 1)
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return result
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except Exception as e:
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warn(f"Forecast error for {location}: {e}")
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return {}
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# =============================================================================
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# POLYMARKET API
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# =============================================================================
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def get_polymarket_event(location_slug: str, month: str, day: int, year: int) -> dict:
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slug = f"highest-temperature-in-{location_slug}-on-{month}-{day}-{year}"
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url = f"https://gamma-api.polymarket.com/events?slug={slug}"
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try:
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r = requests.get(url, timeout=10)
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data = r.json()
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if data and isinstance(data, list) and len(data) > 0:
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return data[0]
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except Exception as e:
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warn(f"Polymarket API error: {e}")
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return None
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def get_price_history(market_id: str) -> list:
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url = f"https://clob.polymarket.com/prices-history?market={market_id}&interval=1d&fidelity=60"
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try:
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r = requests.get(url, timeout=10)
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return r.json().get("history", [])
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except Exception:
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return []
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# =============================================================================
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# PARSING
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# =============================================================================
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def parse_temp_range(question: str) -> tuple:
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if not question:
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return None
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if "or below" in question.lower():
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m = re.search(r'(\d+)°F or below', question, re.IGNORECASE)
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if m: return (-999, int(m.group(1)))
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if "or higher" in question.lower():
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m = re.search(r'(\d+)°F or higher', question, re.IGNORECASE)
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if m: return (int(m.group(1)), 999)
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m = re.search(r'between (\d+)-(\d+)°F', question, re.IGNORECASE)
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if m: return (int(m.group(1)), int(m.group(2)))
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return None
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def temp_in_range(temp: float, rng: tuple) -> bool:
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return rng[0] <= temp <= rng[1]
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def hours_until_resolution(event: dict) -> float:
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try:
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end_date = event.get("endDate") or event.get("end_date_iso")
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if not end_date: return 999
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end_dt = datetime.fromisoformat(end_date.replace("Z", "+00:00"))
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delta = (end_dt - datetime.now(timezone.utc)).total_seconds() / 3600
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return max(0, delta)
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except Exception:
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return 999
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def detect_price_drop(history: list) -> dict:
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if not history or len(history) < 2:
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return {"dropped": False, "change": 0}
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recent = history[-1].get("p", 0.5)
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lookback = min(96, len(history) - 1)
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old = history[-lookback].get("p", recent)
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if old == 0: return {"dropped": False, "change": 0}
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change = (recent - old) / old
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return {"dropped": change < -PRICE_DROP_SIGNAL, "change": change}
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# =============================================================================
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# SHOW POSITIONS
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# =============================================================================
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def show_positions():
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sim = load_sim()
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positions = sim["positions"]
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print(f"\n{C.BOLD}📊 Open Positions:{C.RESET}")
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if not positions:
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print(" No open positions")
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return
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total_pnl = 0
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for mid, pos in positions.items():
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try:
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url = f"https://gamma-api.polymarket.com/markets/{mid}"
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r = requests.get(url, timeout=5)
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current_price = float(r.json().get("outcomePrices", ["0.5"])[0])
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except Exception:
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current_price = pos["entry_price"]
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pnl = (current_price - pos["entry_price"]) * pos["shares"]
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total_pnl += pnl
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pnl_str = f"{C.GREEN}+${pnl:.2f}{C.RESET}" if pnl >= 0 else f"{C.RED}-${abs(pnl):.2f}{C.RESET}"
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print(f"\n • {pos['question'][:65]}...")
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print(f" Entry: ${pos['entry_price']:.3f} | Now: ${current_price:.3f} | "
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f"Shares: {pos['shares']:.1f} | PnL: {pnl_str}")
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print(f" Kelly used: {pos['kelly_pct']:.1%} | EV: {pos['ev']:.2f} | Cost: ${pos['cost']:.2f}")
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balance_str = f"${sim['balance']:.2f}"
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pnl_color = C.GREEN if total_pnl >= 0 else C.RED
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print(f"\n Balance: {balance_str}")
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print(f" Open PnL: {pnl_color}{'+'if total_pnl>=0 else ''}{total_pnl:.2f}{C.RESET}")
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print(f" Total trades: {sim['total_trades']} | W/L: {sim['wins']}/{sim['losses']}")
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# =============================================================================
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# MAIN STRATEGY
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# =============================================================================
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def run(dry_run: bool = True):
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print(f"\n{C.BOLD}{C.CYAN}🌤 Weather Trading Bot v2 — Kelly + EV Edition{C.RESET}")
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print("=" * 55)
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sim = load_sim()
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balance = sim["balance"]
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positions = sim["positions"]
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mode = f"{C.YELLOW}PAPER MODE{C.RESET}" if dry_run else f"{C.RED}LIVE MODE{C.RESET}"
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starting = sim["starting_balance"]
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total_return = (balance - starting) / starting * 100
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return_str = f"{C.GREEN}+{total_return:.1f}%{C.RESET}" if total_return >= 0 else f"{C.RED}{total_return:.1f}%{C.RESET}"
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print(f"\n Mode: {mode}")
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print(f" Virtual balance: {C.BOLD}${balance:.2f}{C.RESET} (started ${starting:.2f}, {return_str})")
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print(f" Kelly fraction: {KELLY_FRACTION:.0%} of full Kelly")
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print(f" Max per trade: {MAX_POSITION_PCT:.0%} of balance")
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print(f" Min EV: {MIN_EV:.2f} per $1 risked")
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print(f" NOAA accuracy: {NOAA_ACCURACY:.0%}")
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print(f" Trades W/L: {sim['wins']}/{sim['losses']}")
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forecast_cache = {}
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trades_executed = 0
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opportunities = 0
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# Check exits
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print(f"\n{C.BOLD}📤 Checking exits...{C.RESET}")
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exits_found = 0
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for mid, pos in list(positions.items()):
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try:
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url = f"https://gamma-api.polymarket.com/markets/{mid}"
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r = requests.get(url, timeout=5)
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current_price = float(r.json().get("outcomePrices", ["0.5"])[0])
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except Exception:
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continue
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if current_price >= EXIT_THRESHOLD:
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exits_found += 1
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pnl = (current_price - pos["entry_price"]) * pos["shares"]
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ok(f"EXIT: {pos['question'][:50]}...")
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info(f"Price ${current_price:.3f} >= exit ${EXIT_THRESHOLD:.2f} | PnL: +${pnl:.2f}")
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if not dry_run:
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balance += pos["cost"] + pnl
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sim["wins"] += 1 if pnl > 0 else 0
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sim["losses"] += 1 if pnl <= 0 else 0
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sim["trades"].append({
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"type": "exit", "question": pos["question"],
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"entry_price": pos["entry_price"], "exit_price": current_price,
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"pnl": round(pnl, 2), "cost": pos["cost"],
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"closed_at": datetime.now().isoformat(),
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})
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del positions[mid]
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ok(f"Closed position — PnL: {'+'if pnl>=0 else ''}{pnl:.2f}")
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else:
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skip("Paper mode — not selling")
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if exits_found == 0:
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skip("No exit opportunities")
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# Scan entries
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print(f"\n{C.BOLD}🔍 Scanning for entry signals...{C.RESET}")
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for loc_key in ACTIVE_LOCATIONS:
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loc_key = loc_key.strip()
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if loc_key not in LOCATIONS:
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warn(f"Unknown location: {loc_key}")
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continue
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loc_data = LOCATIONS[loc_key]
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loc_slug = loc_key.lower().replace(" ", "-")
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if loc_key not in forecast_cache:
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forecast_cache[loc_key] = get_forecast(loc_key)
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forecast = forecast_cache[loc_key]
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if not forecast:
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continue
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for i in range(0, 3):
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date = datetime.now() + timedelta(days=i)
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date_str = date.strftime("%Y-%m-%d")
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month = MONTHS[date.month - 1]
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day = date.day
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year = date.year
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forecast_temp = forecast.get(date_str)
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if forecast_temp is None:
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continue
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event = get_polymarket_event(loc_slug, month, day, year)
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if not event:
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continue
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hours_left = hours_until_resolution(event)
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print(f"\n{C.BOLD}📍 {loc_data['name']} — {date_str}{C.RESET}")
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info(f"Forecast: {forecast_temp}°F | Resolves in: {hours_left:.0f}h")
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if hours_left < MIN_HOURS_LEFT:
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skip(f"Resolves in {hours_left:.0f}h — too soon")
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continue
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# Find matching bucket
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matched = None
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for market in event.get("markets", []):
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question = market.get("question", "")
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rng = parse_temp_range(question)
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if rng and temp_in_range(forecast_temp, rng):
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try:
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prices = json.loads(market.get("outcomePrices", "[0.5,0.5]"))
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yes_price = float(prices[0])
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except Exception:
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continue
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matched = {"market": market, "question": question,
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"price": yes_price, "range": rng}
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break
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if not matched:
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skip(f"No bucket found for {forecast_temp}°F")
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continue
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price = matched["price"]
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market_id = matched["market"].get("id", "")
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question = matched["question"]
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info(f"Bucket: {question[:60]}")
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info(f"Market price: ${price:.3f}")
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# Trend check
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history = get_price_history(market_id)
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trend = detect_price_drop(history)
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if trend["dropped"]:
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info(f"📉 Price dropped {abs(trend['change']):.0%} in 24h — stronger signal")
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# ── KELLY + EV CALCULATION ──
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our_prob = NOAA_ACCURACY # base accuracy
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# Boost if strong trend signal
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if trend["dropped"] and abs(trend["change"]) > 0.20:
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our_prob = min(0.90, our_prob + 0.05)
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ev = calculate_ev(our_prob, price)
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kelly_pct = calculate_kelly(our_prob, price)
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position_size = calculate_position_size(kelly_pct, balance)
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print(f"\n {C.BOLD}📐 Kelly + EV Analysis:{C.RESET}")
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info(f" Our probability: {our_prob:.0%}")
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info(f" Market implies: {price:.1%}")
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info(f" Edge: {our_prob - price:.1%}")
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ev_color = C.GREEN if ev > 0 else C.RED
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print(f" {C.CYAN} EV per $1: {ev_color}{ev:+.2f}{C.RESET}")
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print(f" {C.CYAN} Kelly fraction: {kelly_pct:.1%} of balance{C.RESET}")
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print(f" {C.CYAN} Position size: ${position_size:.2f}{C.RESET}")
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# Entry checks
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if price >= ENTRY_THRESHOLD:
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skip(f"Price ${price:.3f} above threshold ${ENTRY_THRESHOLD:.2f}")
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continue
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if ev < MIN_EV:
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skip(f"EV {ev:.2f} below minimum {MIN_EV:.2f} — skip")
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continue
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if kelly_pct <= 0:
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skip("Kelly says no edge — skip")
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continue
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opportunities += 1
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ok(f"ENTRY signal! EV={ev:+.2f} | Kelly={kelly_pct:.1%} | Size=${position_size:.2f}")
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if market_id in positions:
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skip("Already in this market")
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continue
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if trades_executed >= MAX_TRADES:
|
|
skip(f"Max trades ({MAX_TRADES}) reached")
|
|
continue
|
|
|
|
if position_size < 0.50:
|
|
skip(f"Position size ${position_size:.2f} too small — skip")
|
|
continue
|
|
|
|
shares = position_size / price
|
|
info(f"Buying {shares:.1f} shares @ ${price:.3f} = ${position_size:.2f}")
|
|
|
|
if not dry_run:
|
|
balance -= position_size
|
|
positions[market_id] = {
|
|
"question": question,
|
|
"entry_price": price,
|
|
"shares": shares,
|
|
"cost": position_size,
|
|
"kelly_pct": kelly_pct,
|
|
"ev": ev,
|
|
"our_prob": our_prob,
|
|
"date": date_str,
|
|
"location": loc_key,
|
|
"forecast_temp": forecast_temp,
|
|
"opened_at": datetime.now().isoformat(),
|
|
}
|
|
sim["total_trades"] += 1
|
|
sim["trades"].append({
|
|
"type": "entry", "question": question,
|
|
"entry_price": price, "shares": shares,
|
|
"cost": position_size, "kelly_pct": kelly_pct,
|
|
"ev": ev, "our_prob": our_prob,
|
|
"opened_at": datetime.now().isoformat(),
|
|
})
|
|
trades_executed += 1
|
|
ok(f"Bought {shares:.1f} shares — ${position_size:.2f} deducted from balance")
|
|
else:
|
|
skip("Paper mode — not buying")
|
|
trades_executed += 1
|
|
|
|
# Save simulation state
|
|
if not dry_run:
|
|
sim["balance"] = round(balance, 2)
|
|
sim["positions"] = positions
|
|
sim["peak_balance"] = max(sim["peak_balance"], balance)
|
|
save_sim(sim)
|
|
|
|
# Summary
|
|
print(f"\n{'=' * 55}")
|
|
print(f"{C.BOLD}📊 Summary:{C.RESET}")
|
|
info(f"Opportunities found: {opportunities}")
|
|
info(f"Trades executed: {trades_executed}")
|
|
info(f"Exits found: {exits_found}")
|
|
info(f"Balance: ${balance:.2f}")
|
|
|
|
if dry_run:
|
|
print(f"\n {C.YELLOW}[PAPER MODE — use --live to simulate trades against real prices]{C.RESET}")
|
|
|
|
# =============================================================================
|
|
# LIVE MONITOR — updates prices every N seconds, auto-exits on threshold
|
|
# =============================================================================
|
|
|
|
import time as _time
|
|
|
|
def monitor(interval: int = 10):
|
|
"""
|
|
Background monitor — fetches live prices from Polymarket every N seconds,
|
|
updates PnL in simulation.json so the dashboard stays current.
|
|
Auto-exits positions when price hits EXIT_THRESHOLD.
|
|
|
|
Run: python polymarket_weather_bot.py --monitor
|
|
Stop: Ctrl+C
|
|
"""
|
|
print(f"\n{C.BOLD}{C.CYAN}📡 Live Monitor — refreshing every {interval}s{C.RESET}")
|
|
print(f" Dashboard will update automatically")
|
|
print(f" Auto-exit threshold: ${EXIT_THRESHOLD:.2f}")
|
|
print(f" Press Ctrl+C to stop\n")
|
|
|
|
while True:
|
|
try:
|
|
sim = load_sim()
|
|
positions = sim.get("positions", {})
|
|
|
|
if not positions:
|
|
print(f"{C.GRAY} {_time.strftime('%H:%M:%S')} — No open positions{C.RESET}")
|
|
_time.sleep(interval)
|
|
continue
|
|
|
|
total_pnl = 0
|
|
|
|
for mid, pos in list(positions.items()):
|
|
# Fetch current price from Polymarket
|
|
try:
|
|
url = f"https://gamma-api.polymarket.com/markets/{mid}"
|
|
r = requests.get(url, timeout=5)
|
|
data = r.json()
|
|
prices = json.loads(data.get("outcomePrices", "[0.5,0.5]"))
|
|
current_price = float(prices[0])
|
|
except Exception:
|
|
current_price = pos.get("current_price", pos["entry_price"])
|
|
|
|
pnl = (current_price - pos["entry_price"]) * pos["shares"]
|
|
pos["current_price"] = round(current_price, 4)
|
|
pos["pnl"] = round(pnl, 2)
|
|
total_pnl += pnl
|
|
|
|
pnl_str = f"{C.GREEN}+${pnl:.2f}{C.RESET}" if pnl >= 0 else f"{C.RED}-${abs(pnl):.2f}{C.RESET}"
|
|
print(f" {C.GRAY}{_time.strftime('%H:%M:%S')}{C.RESET} "
|
|
f"{pos['question'][:45]}... "
|
|
f"${current_price:.3f} {pnl_str}")
|
|
|
|
# Auto-exit if price hit threshold
|
|
if current_price >= EXIT_THRESHOLD:
|
|
ok(f"AUTO EXIT: {pos['question'][:50]}... PnL: +${pnl:.2f}")
|
|
sim["balance"] = round(sim["balance"] + pos["cost"] + pnl, 2)
|
|
sim["wins"] += 1 if pnl > 0 else 0
|
|
sim["losses"] += 1 if pnl <= 0 else 0
|
|
sim["trades"].append({
|
|
"type": "exit",
|
|
"question": pos["question"],
|
|
"entry_price": pos["entry_price"],
|
|
"exit_price": current_price,
|
|
"pnl": round(pnl, 2),
|
|
"cost": pos["cost"],
|
|
"kelly_pct": pos.get("kelly_pct", 0),
|
|
"ev": pos.get("ev", 0),
|
|
"location": pos.get("location", ""),
|
|
"date": pos.get("date", ""),
|
|
"our_prob": pos.get("our_prob", 0),
|
|
"closed_at": datetime.now().isoformat(),
|
|
})
|
|
del sim["positions"][mid]
|
|
|
|
sim["positions"] = {k: v for k, v in sim["positions"].items()}
|
|
sim["peak_balance"] = max(sim.get("peak_balance", sim["balance"]), sim["balance"])
|
|
|
|
total_str = f"{C.GREEN}+${total_pnl:.2f}{C.RESET}" if total_pnl >= 0 else f"{C.RED}-${abs(total_pnl):.2f}{C.RESET}"
|
|
print(f" {'─'*60}")
|
|
print(f" Open PnL: {total_str} | Balance: ${sim['balance']:.2f} | "
|
|
f"Positions: {len(sim['positions'])}\n")
|
|
|
|
save_sim(sim)
|
|
|
|
except KeyboardInterrupt:
|
|
print(f"\n{C.YELLOW} Monitor stopped{C.RESET}")
|
|
break
|
|
except Exception as e:
|
|
warn(f"Monitor error: {e}")
|
|
|
|
_time.sleep(interval)
|
|
|
|
|
|
# =============================================================================
|
|
# CLI
|
|
# =============================================================================
|
|
|
|
if __name__ == "__main__":
|
|
parser = argparse.ArgumentParser(description="Weather Trading Bot v2 — Kelly + EV")
|
|
parser.add_argument("--live", action="store_true", help="Execute trades (updates simulation balance)")
|
|
parser.add_argument("--positions", action="store_true", help="Show open positions")
|
|
parser.add_argument("--reset", action="store_true", help="Reset simulation to $1000")
|
|
parser.add_argument("--monitor", action="store_true", help="Live price monitor — updates dashboard every 10s")
|
|
parser.add_argument("--interval", type=int, default=10, help="Monitor refresh interval in seconds (default: 10)")
|
|
args = parser.parse_args()
|
|
|
|
if args.reset:
|
|
reset_sim()
|
|
elif args.positions:
|
|
show_positions()
|
|
elif args.monitor:
|
|
monitor(interval=args.interval)
|
|
else:
|
|
|
|
run(dry_run=not args.live)
|