Production Django trading dashboard with scalp trade signals, multi-timeframe confluence, price action patterns, market regime detection, 20+ technical indicators, LSTM forecasting, news sentiment, backtesting, and Firebase authentication.
| Link | |
|---|---|
| Live Demo | https://graves-clarify-freeness.ngrok-free.dev |
| GitHub | https://github.com/DMZ22/Stock-Trader-Pro |
- 50+ assets added — Now supports 230+ symbols across 12 categories: US stocks, Indian NSE (35 tickers), 60+ cryptocurrencies, Gold/Silver/Platinum futures + ETFs + miners, energy & agricultural commodities, forex, global ETFs & indices.
- CoinGecko provider (no API key) — Reliable crypto data for all major and alt coins.
- Multi-timeframe confluence — Scalp signals check higher-timeframe trend (5m → 1h, 1h → 1d) for alignment; +12 score boost when aligned, -15 when counter-trend.
- Price action patterns — Detects Hammer, Shooting Star, Doji, Bullish/Bearish Engulfing, Inside Bar, Morning/Evening Star, Three White Soldiers / Black Crows.
- Market regime classification — STRONG_TREND / WEAK_TREND / RANGING / TIGHT_RANGE / VOLATILE_CHOP with strategy adaptation.
- Support/resistance auto-detection — Fractal swing highs/lows. SL/TP snap to nearby levels when within 0.5 × ATR.
- Backtest endpoint — Replay signals on historical bars, report hit rate vs 2:1 R/R breakeven.
- 31 indicator values exposed per signal with tooltips explaining each.
- Firebase Authentication — Email/password + Google OAuth sign-in with Django session integration.
- Production hardening — HSTS, secure cookies, CSRF trusted origins, detailed health endpoint.
git clone <repo-url>
cd Stock-Trader-Pro
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env
python manage.py migrate
python manage.py runserver
# visit http://localhost:8000# Market Data API keys (yfinance + CoinGecko work without keys)
FINNHUB_API_KEY= # https://finnhub.io (60/min)
TWELVE_DATA_API_KEY= # https://twelvedata.com (8/min)
ALPHA_VANTAGE_API_KEY= # https://www.alphavantage.co (5/min)
# News APIs
NEWSAPI_KEY= # https://newsapi.org (100/day)
MARKETAUX_API_KEY= # https://marketaux.com
# Firebase Auth (optional)
FIREBASE_API_KEY=
FIREBASE_AUTH_DOMAIN=yourproject.firebaseapp.com
FIREBASE_PROJECT_ID=yourproject
FIREBASE_APP_ID=1:123:web:abc
REQUIRE_LOGIN=False # set True to force login for all pages| Category | Count | Examples |
|---|---|---|
| US Tech | 27 | AAPL, MSFT, NVDA, GOOGL, AMZN, TSM, ASML |
| US Finance | 14 | JPM, V, GS, BLK |
| US Consumer/Industrial | 21 | DIS, WMT, KO, LLY, JNJ |
| Indian NSE | 35 | RELIANCE.NS, TCS.NS, HDFCBANK.NS, SBIN.NS |
| Major Crypto | 16 | BTC, ETH, SOL, BNB, XRP, DOGE |
| Crypto DeFi & L1 | 20 | NEAR, APT, ARB, OP, MKR, AAVE, LDO |
| Crypto Meme & Alt | 22 | PEPE, BONK, WIF, BCH, XMR |
| Precious Metals & Miners | 16 | Gold/Silver/Platinum/Palladium futures, GLD, GDX, NEM |
| Energy & Agri Commodities | 18 | WTI, Brent, Nat Gas, Copper, Wheat, Coffee |
| ETFs & Indices | 24 | SPY, QQQ, VIX, Nifty, Sensex, Nikkei, DAX |
| Forex | 18 | EUR/USD, GBP/USD, USD/INR, USD/JPY |
| Endpoint | Description |
|---|---|
GET /api/health/ |
Provider status + cache + Firebase config |
GET /api/quote/{symbol}/ |
Real-time quote |
GET /api/candles/{symbol}/?interval=5m&period=5d |
OHLCV candles |
GET /api/scalp/{symbol}/?interval=5m&period=5d&account=10000&risk=1&htf=1 |
Full scalp signal with HTF confluence |
GET /api/analyze/{symbol}/ |
Combined analysis (scalp + sentiment + composite) |
GET /api/backtest/{symbol}/?bars=300 |
Historical hit rate |
GET /api/search/?q=BTC |
Asset search |
GET /api/assets/ |
Full asset universe |
POST /auth/session/ |
Exchange Firebase ID token for Django session |
GET /auth/whoami/ |
Current session user |
- Core scoring (0-100 per direction): EMA-9/21 cross, VWAP position, Supertrend, MACD histogram + acceleration, RSI zones, volume ratio, ADX strength + DI directionality, Stochastic reversal, Bollinger %B.
- Pattern adjustment: +8 per aligned candlestick pattern, -10 per counter-trend pattern.
- Regime adjustment: +5 in STRONG_TREND, -10 in VOLATILE_CHOP.
- HTF confluence: +12 when higher timeframe aligns, -15 when counter to HTF trend.
- Level snapping: SL/TP adjusted to support/resistance when within 0.5 × ATR.
- Position sizing: Dollar risk = account × risk_pct; shares = dollar_risk ÷ (entry - stop).
Breakeven hit rate at 2:1 R/R = 33.3%. Any hit rate above that is profitable.
docker-compose up --build- Set
DJANGO_DEBUG=Falseand a strongDJANGO_SECRET_KEY - Add your domain to
DJANGO_ALLOWED_HOSTS - Configure API keys in
.env - Set up Firebase project + enable Email/Password and Google providers
- Use Redis via
REDIS_URLfor shared cache across workers - Behind nginx/Cloudflare, HTTPS auto-detected via
X-Forwarded-Proto
config/ Django settings + routing
apps/
market/ Multi-provider data + 20+ indicators
providers/ yfinance, finnhub, alpha_vantage, twelve_data, coingecko
services.py Unified facade: retry/failover/caching/rate-limit
indicators.py Canonical formulas (RSI, MACD, BB, ADX, Stoch, etc.)
assets.py 230+ curated symbols
predictor/ Bidirectional LSTM (24 features, multi-step)
signals/ Scalp engine + patterns + regime + sentiment + composite
scalper.py Confluence scoring + ATR SL/TP + position sizing
patterns.py Candlestick patterns + regime + S/R levels
sentiment.py 4 news providers with TextBlob
composite.py Combined scalp + LSTM + sentiment
auth/ Firebase ID token verification + session auth
dashboard/ Views, REST API, templates
For educational purposes only. Trading involves substantial risk of loss. Past performance does not guarantee future results. This software provides technical analysis based on historical data and indicator confluence; it does not account for fundamentals, breaking news, or black-swan events. Always do your own research and consult a licensed financial advisor before trading.
MIT