harwinder
1f076c0b54
Live pipeline: - Drop still-forming candle before analysis (signals no longer repaint) - Direction-aware MTF agreement + opposition gate (no trade against 2-of-3 TF consensus) - SELL volatility gate: block shorts in low/normal vol regimes (config sell_vol_regimes) - Divergence: 40-bar lookback, price/indicator swings must align within ±2 bars (fired on 0.5% of trades before, 29% after), trending weight 2.0→1.0 - RSI regime_aware by default; transitioning regime only signals at extremes - ADX ±DM tie no longer nudges bearish; TP2 clamped beyond TP1 Backtester realism: - Charge $0.30 round-trip spread (--spread), gap-through SL/TP fills at bar open - Resolve trades on RAW price path (cache stores raw bars, cleaning runs on load) - Weekend/session filters use bar-close decision time to match live wall clock Validated per-step on M15 2025-03-30→2026-05-31 under identical pricing: +46.9R → +66.8R, win rate 69.9% → 73.0%, SELL side -2.3R → +9.6R. Tested-and-reverted: ROC weight removal (-13R), BB fade suppression (-11.6R), candlestick de-weight (-2R) — composite thresholds are co-tuned with weight mass.
122 lines
7.0 KiB
Markdown
122 lines
7.0 KiB
Markdown
# ForexBot2
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XAU/USD signal intelligence platform. Analyzes gold across multiple timeframes using 9 technical indicators with regime-adaptive weights, news sentiment, and economic calendar data. Delivers signals via Telegram with full trade setups (entry, SL, TP).
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## Architecture
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```
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Twelve Data REST API + WebSocket
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data_provider.py (fetch, cache, validate OHLCV; rate-limited 55 calls/min)
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engine.py (9 indicators per timeframe → composite score)
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signal_aggregator.py (MTF agreement + news + final signal + trade setup)
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+-----+--------+
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telegram_bot.py main.py
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(Telegram alerts, (CLI single-pair
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auto-scanner, analysis)
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WS monitor)
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```
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## Core Files
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| File | Purpose |
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|------|---------|
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| `config.py` | All configuration dataclasses, XAU/USD pair definition, strategy config |
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| `data_provider.py` | Twelve Data SDK wrapper with in-memory cache and rate limiting |
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| `engine.py` | `TechnicalEngine` — computes EMA, RSI, BB, ADX, ATR, MACD, ROC, Keltner, divergences, candlestick patterns, swing S/R |
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| `signal_aggregator.py` | `SignalAggregator` — MTF analysis, news integration, diminishing penalty cap, trade setup generation |
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| `news_engine.py` | Economic calendar (Forex Factory JSON) + RSS sentiment (keyword-based) |
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| `telegram_bot.py` | Async Telegram bot with auto-scanner (M5/M15/H1/H4), WebSocket price monitor |
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| `main.py` | CLI entry point for XAU/USD analysis |
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| `test_all.py` | Comprehensive QA suite (~137 tests, no live API needed) |
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## Key Concepts
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**Signal Pipeline:** OHLCV → indicators → regime classification → regime-weighted composite score → MTF agreement check → news/event adjustment → diminishing penalty cap → final signal (STRONG_BUY/BUY/NEUTRAL/SELL/STRONG_SELL) → quality grade (A+/A/B/C/D/F) → trade setup if grade C+.
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**Regime-Adaptive Weights:** Market classified as `trending_up`, `trending_down`, `ranging`, or `transitioning` via ADX + EMA + ADX slope. Gold-specific weights per regime:
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- **Trending:** MACD (2.0), EMA (2.0), Keltner (1.5), ROC (1.5), Divergence (1.0)
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- **Ranging:** Divergence (2.5), Keltner (2.0), RSI (1.5), BB (1.5), MACD (1.5)
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- **Transitioning:** Keltner (2.5), MACD (2.5), ROC (2.0), Divergence (2.0), EMA (1.5)
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ROC is directionally redundant with MACD/Keltner/EMA (0.8–0.94 correlation) but its weight is load-bearing: composite thresholds are calibrated with it — removing it backtested 13R worse. Don't zero it without retuning thresholds.
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**RSI (regime-aware, default):** In trends RSI buys pullback zones instead of fading strength (classic mode backtested worse for gold). In `transitioning` only extremes (≥70/≤30) signal.
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**Divergence:** 40-bar lookback; price and indicator swings must align within ±2 bars to count as one divergence observation.
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**Transitioning Regime:** ADX < 25 but ADX slope > 3.0 = trend emerging. Catches trend birth 5-10 bars before ADX crosses 25. Boosts quality grade for early entries.
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**Diminishing Penalty Cap:** Penalties sorted by magnitude, applied with exponential decay (1st at 100%, 2nd at 50%, 3rd at 25%). Hard cap at 30% total. Replaces old additive stacking that could gut 30-50% confidence.
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**Indicators (9 scored):** EMA Trend, RSI, Bollinger Bands, MACD, ADX, Keltner Channels (TTM Squeeze), ROC (Rate of Change), Divergence, Candlestick Patterns.
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**Trade Setup:** SL = nearest swing low/high ± 1×ATR buffer (min 1.5×ATR). TP = nearest swing level if RR≥1.2, else calculated from ATR. Minimum RR 0.5:1.
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## How to Run
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```bash
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# CLI (XAU/USD analysis)
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python main.py # H1 default
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python main.py --timeframe M15 --detail --json
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# Telegram bot (auto-scanner)
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TELEGRAM_TOKEN=<token> TELEGRAM_CHAT_ID=<id> python telegram_bot.py
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# Tests
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python test_all.py
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# Backtest
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python backtest/gpu_backtest.py --pair XAUUSD --days 365
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```
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## Environment Variables
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| Variable | Purpose | Default |
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|----------|---------|---------|
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| `TWELVE_DATA_API_KEY` | Market data API key | Hardcoded fallback in config |
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| `TELEGRAM_TOKEN` | Telegram bot token | Hardcoded fallback |
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| `TELEGRAM_CHAT_ID` | Auto-scan chat ID (enables boot auto-scan) | Hardcoded fallback |
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## Dependencies
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`numpy`, `pandas`, `requests`, `twelvedata`, `python-telegram-bot`, `websockets` — see `requirements.txt`.
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## Data Provider
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- **Source:** Twelve Data REST API via `twelvedata` SDK
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- **Rate limit:** 55 credits/min (Grow plan), enforced by sliding-window throttle
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- **Cache:** In-memory dict, TTL = candle duration of the timeframe
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- **Validation:** Drops NaN rows, forward-fills gaps (limit 3), fixes OHLC inconsistencies, removes outliers (>10σ), strips future timestamps, deduplicates
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- **WebSocket:** XAU/USD only
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## Telegram Bot
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- **Auto-scan:** M5, M15, H1, H4 at candle boundaries + 10s buffer (all timeframes alert)
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- **Manual scan:** Buttons for M15/H1/H4 individual scans + "Scan All TFs" multi-timeframe summary
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- **WebSocket:** Streams live ticks for XAU/USD; triggers immediate M15 scan on key level breach (swing S/R, BB, KC, EMA200) with 5-min cooldown
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- **Commands:** `/start`, `/scan`, `/autoscan`, `/status`, `/cache`, `/clearcache`, `/help`
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## Backtesting
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The `backtest/` directory contains `gpu_backtest.py` — a GPU-accelerated backtester (CuPy with NumPy fallback) that replays historical OHLCV through the real SignalAggregator. Pre-computes all indicator series including ROC, Keltner, ADX slope for 100x+ speedup. Uses parquet caching for data persistence.
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Fill realism: charges a round-trip spread per trade (`--spread`, default $0.30 for XAU), fills gap-through SL/TP at the bar open, and resolves trades against the RAW price path (the parquet cache stores raw bars; validation/cleaning runs on load — signals see cleaned data, trade resolution sees real spikes). Entry is at the next bar's open after the signal bar. Weekend/session filters evaluate bar-close (decision) time to match the live bot's wall clock.
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GPU note: CuPy needs the NVIDIA runtime pip wheels (`nvidia-cuda-runtime-cu12`, `nvidia-cuda-nvrtc-cu12`, `nvidia-curand-cu12`, `nvidia-nvjitlink-cu12`) or it silently falls back to NumPy — check the "Backend:" line in the run log. The bar-replay loop itself is single-threaded Python either way (~340 bars/s); GPU only accelerates indicator precompute and SL/TP scanning.
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## Code Conventions
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- Python 3.12, type hints on public methods
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- Dataclasses for all config and output structures
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- `SignalStrength` enum (-2 to +2) is the universal signal currency
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- Indicators stored as `Dict[str, IndicatorSignal]` in `TechnicalAnalysis`
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- Key levels stored as `Dict[str, float]` — prefixed `swing_high_`, `swing_low_`, `ema_`, `bb_`, `kc_`, `atr`
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- Private indicator data attached as `result._rsi_series`, `result._macd_histogram`, `result._adx_slope`, `result._kc_squeeze` (underscore prefix, skipped by composite scorer)
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- Blocking signal computation runs in `ThreadPoolExecutor(max_workers=4)` to avoid blocking the async Telegram event loop
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- Shared `ForexDataProvider` instance across all scans for cache reuse
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