"""Market data providers. MVP ships a deterministic mock provider (seeded per symbol per day, so results are stable within a trading day). The `MarketDataProvider` interface is the integration point for Alpaca / Tradier (see live_data.py). """ import math import random from datetime import date, datetime, timedelta UNIVERSE = [ ("TSLA", "Tesla Inc", 250.0), ("NVDA", "NVIDIA Corp", 130.0), ("AMD", "Advanced Micro Devices", 160.0), ("META", "Meta Platforms", 500.0), ("AAPL", "Apple Inc", 210.0), ("AMZN", "Amazon.com", 185.0), ("MSFT", "Microsoft Corp", 430.0), ("GOOGL", "Alphabet Inc", 175.0), ("NFLX", "Netflix Inc", 650.0), ("COIN", "Coinbase Global", 240.0), ("MARA", "Marathon Digital", 22.0), ("RIOT", "Riot Platforms", 12.0), ("PLTR", "Palantir Technologies", 26.0), ("SOFI", "SoFi Technologies", 8.0), ("SQ", "Block Inc", 70.0), ("SHOP", "Shopify Inc", 65.0), ("UBER", "Uber Technologies", 72.0), ("ABNB", "Airbnb Inc", 150.0), ("SNAP", "Snap Inc", 12.0), ("ROKU", "Roku Inc", 62.0), ("DKNG", "DraftKings Inc", 40.0), ("RIVN", "Rivian Automotive", 12.0), ("LCID", "Lucid Group", 3.5), ("NIO", "NIO Inc", 5.0), ("BABA", "Alibaba Group", 78.0), ("CRM", "Salesforce Inc", 260.0), ("ORCL", "Oracle Corp", 140.0), ("INTC", "Intel Corp", 32.0), ("MU", "Micron Technology", 120.0), ("AVGO", "Broadcom Inc", 1400.0), ("SMCI", "Super Micro Computer", 800.0), ("ARM", "Arm Holdings", 130.0), ("CRWD", "CrowdStrike Holdings", 350.0), ("NET", "Cloudflare Inc", 80.0), ("DDOG", "Datadog Inc", 120.0), ("MDB", "MongoDB Inc", 240.0), ("SPY", "SPDR S&P 500 ETF", 545.0), ("QQQ", "Invesco QQQ Trust", 470.0), ("IWM", "iShares Russell 2000", 205.0), ("XOM", "Exxon Mobil", 112.0), ] CRYPTO_UNIVERSE = [ ("BTC/USD", "Bitcoin", 68000.0), ("ETH/USD", "Ethereum", 3500.0), ("SOL/USD", "Solana", 150.0), ("LINK/USD", "Chainlink", 18.0), ("AVAX/USD", "Avalanche", 35.0), ("DOGE/USD", "Dogecoin", 0.2), ("XRP/USD", "XRP", 0.6), ] def is_crypto(symbol: str) -> bool: return "/" in symbol class MarketDataProvider: """Interface for market data providers (implement for Alpaca/Tradier).""" def get_universe(self) -> list[dict]: raise NotImplementedError def get_crypto_universe(self) -> list[dict]: return [{"symbol": s, "company": c, "base_price": p} for s, c, p in CRYPTO_UNIVERSE] def get_history(self, symbol: str, days: int = 60) -> list[dict]: raise NotImplementedError def get_quote(self, symbol: str) -> dict: raise NotImplementedError def get_options_chain(self, symbol: str) -> list[dict]: raise NotImplementedError class MockMarketDataProvider(MarketDataProvider): """Deterministic pseudo-random data; stable per symbol per calendar day.""" def __init__(self, seed_date: date | None = None): self.seed_date = seed_date or date.today() def _rng(self, symbol: str, tag: str = "") -> random.Random: return random.Random(f"{symbol}:{self.seed_date.isoformat()}:{tag}") def get_universe(self) -> list[dict]: return [{"symbol": s, "company": c, "base_price": p} for s, c, p in UNIVERSE] def get_history(self, symbol: str, days: int = 60) -> list[dict]: crypto = is_crypto(symbol) if crypto: base = next((p for s, _, p in CRYPTO_UNIVERSE if s == symbol), 100.0) else: base = next((p for s, _, p in UNIVERSE if s == symbol), 100.0) rng = self._rng(symbol, "hist") drift = rng.uniform(-0.002, 0.003) # Crypto trades 24/7 with roughly double equity volatility vol = rng.uniform(0.025, 0.07) if crypto else rng.uniform(0.012, 0.045) bars = [] price = base * rng.uniform(0.85, 1.1) d = datetime.now() - timedelta(days=days) for i in range(days): d += timedelta(days=1) if not crypto and d.weekday() >= 5: continue change = rng.gauss(drift, vol) o = price c = max(0.5, price * (1 + change)) hi = max(o, c) * (1 + abs(rng.gauss(0, vol / 2))) lo = min(o, c) * (1 - abs(rng.gauss(0, vol / 2))) v = int(rng.uniform(0.6, 3.0) * 10_000_000) bars.append({ "date": d.strftime("%Y-%m-%d"), "open": round(o, 2), "high": round(hi, 2), "low": round(lo, 2), "close": round(c, 2), "volume": v, }) price = c return bars def get_quote(self, symbol: str) -> dict: hist = self.get_history(symbol) last, prev = hist[-1], hist[-2] avg_vol = sum(b["volume"] for b in hist[-20:]) / 20 return { "symbol": symbol, "price": last["close"], "change_pct": round((last["close"] / prev["close"] - 1) * 100, 2), "volume": last["volume"], "relative_volume": round(last["volume"] / avg_vol, 2), } def get_options_chain(self, symbol: str) -> list[dict]: quote = self.get_quote(symbol) price = quote["price"] rng = self._rng(symbol, "opt") iv_base = rng.uniform(0.35, 0.95) expiry = (self.seed_date + timedelta(days=30)).isoformat() step = max(0.5, round(price * 0.025, 1)) chain = [] for i in range(-4, 5): strike = round(price + i * step, 1) for opt_type in ("call", "put"): moneyness = (price - strike) / price * (1 if opt_type == "call" else -1) delta = max(0.03, min(0.97, 0.5 + moneyness * 6)) mid = max(0.05, price * iv_base * 0.12 * math.exp(-abs(moneyness) * 8) + max(0.0, moneyness * price)) spread = mid * rng.uniform(0.02, 0.15) chain.append({ "symbol": symbol, "type": opt_type, "strike": strike, "expiry": expiry, "bid": round(mid - spread / 2, 2), "ask": round(mid + spread / 2, 2), "iv": round(iv_base * rng.uniform(0.9, 1.15), 3), "delta": round(delta if opt_type == "call" else delta - 1, 3), "gamma": round(rng.uniform(0.005, 0.05), 4), "theta": round(-mid * rng.uniform(0.01, 0.04), 3), "vega": round(price * rng.uniform(0.0008, 0.002), 3), "open_interest": int(rng.uniform(50, 20000) * math.exp(-abs(i) * 0.4)), "volume": int(rng.uniform(10, 8000) * math.exp(-abs(i) * 0.5)), }) return chain def bars_are_fresh(bars: list[dict], max_age_days: int | None = None) -> bool: """Stale-data circuit breaker (audit Phase 5): signals must never be generated from old bars. True when the latest bar is recent enough.""" import os if max_age_days is None: try: max_age_days = int(os.getenv("DATA_FRESHNESS_MAX_DAYS", "5")) except ValueError: max_age_days = 5 if not bars: return False try: last = date.fromisoformat(str(bars[-1]["date"])[:10]) except (KeyError, ValueError): return False return (date.today() - last).days <= max_age_days def get_provider() -> MarketDataProvider: """Provider factory. DATA_PROVIDER=live (+ ALPACA_API_KEY/SECRET and/or TRADIER_API_TOKEN) activates real market data; anything else - or missing keys - uses the deterministic mock so the platform always works. """ import os if os.getenv("DATA_PROVIDER", "mock").lower() == "live": has_alpaca = bool(os.getenv("ALPACA_API_KEY") and os.getenv("ALPACA_API_SECRET")) has_tradier = bool(os.getenv("TRADIER_API_TOKEN")) if has_alpaca or has_tradier: from .live_data import LiveMarketDataProvider return LiveMarketDataProvider() return MockMarketDataProvider()