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Refocus on XAU/USD: add momentum indicators, tune TP, exhaustion block

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Strip EUR/USD, GBP/USD, USD/JPY pairs and strategies from entire codebase.
Add 3 new scored indicators (ROC, Keltner/TTM Squeeze, ADX slope) and
enable MACD-as-pillar + divergence detection for early trend entry.
Introduce "transitioning" regime (ADX < 25, slope > 3.0) to catch trend
births before ADX confirms. Gold-specific composite weights per regime.

Tune TP multipliers: quality-tiered scaling (A+/A get 1.5-2.0x ATR via
XAU ATR method, B/C use swing-level targeting). Backtest: +24R total,
65% WR, PF 1.12 over 365 days.

Add momentum-confirmed exhaustion block: hard-reject trades when 2+
static exhaustion signals fire AND ROC/MACD confirm fading momentum.
Prevents late trend entries without killing strong trend trades.

Telegram: simplify buttons to timeframe-only labels, add "Scan All TFs"
multi-timeframe summary, add /scan command, fix BB/KC level breach keys,
fix price formatting (.2f for gold), fix deprecated asyncio call, fix
"1 pairs" grammar and 60s/30s dashboard refresh mismatch.
This commit is contained in:
harwinder
2026-05-15 10:51:51 -04:00
parent bb3c475f22
commit 04328eaeab
15 changed files with 852 additions and 2108 deletions
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CLAUDE.md
+29 -26
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@@ -1,6 +1,6 @@
# ForexBot2
Automated forex signal intelligence platform. Analyzes 4 currency pairs (EUR/USD, GBP/USD, USD/JPY, XAU/USD) across multiple timeframes using technical indicators, news sentiment, and economic calendar data. Delivers signals via Telegram with full trade setups (entry, SL, TP).
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).
## Architecture
@@ -9,7 +9,7 @@ Twelve Data REST API + WebSocket
|
data_provider.py (fetch, cache, validate OHLCV; rate-limited 55 calls/min)
|
engine.py (6 indicators per timeframe → composite score)
engine.py (9 indicators per timeframe → composite score)
|
signal_aggregator.py (MTF agreement + news + final signal + trade setup)
|
@@ -26,31 +26,36 @@ telegram_bot.py main.py
| File | Purpose |
|------|---------|
| `config.py` | All configuration dataclasses, pair definitions, strategy configs |
| `config.py` | All configuration dataclasses, XAU/USD pair definition, strategy config |
| `data_provider.py` | Twelve Data SDK wrapper with in-memory cache and rate limiting |
| `engine.py` | `TechnicalEngine` — computes EMA, RSI, BB, ADX, ATR, MACD, divergences, candlestick patterns, swing S/R |
| `signal_aggregator.py` | `SignalAggregator` — MTF analysis, news integration, final signal scoring, trade setup generation |
| `engine.py` | `TechnicalEngine` — computes EMA, RSI, BB, ADX, ATR, MACD, ROC, Keltner, divergences, candlestick patterns, swing S/R |
| `signal_aggregator.py` | `SignalAggregator` — MTF analysis, news integration, diminishing penalty cap, trade setup generation |
| `news_engine.py` | Economic calendar (Forex Factory JSON) + RSS sentiment (keyword-based) |
| `telegram_bot.py` | Async Telegram bot with auto-scanner (M5/M15/H1/H4), WebSocket price monitor, live dashboard |
| `main.py` | CLI entry point for single USD/JPY analysis |
| `test_all.py` | Comprehensive QA suite (~90 tests, no live API needed) |
| `main.py` | CLI entry point for XAU/USD analysis |
| `test_all.py` | Comprehensive QA suite (~137 tests, no live API needed) |
## Key Concepts
**Signal Pipeline:** OHLCV → indicators → regime classification → regime-weighted composite score → MTF agreement check → news/event adjustment → confidence penalties → final signal (STRONG_BUY/BUY/NEUTRAL/SELL/STRONG_SELL) → quality grade (A+/A/B/C/D/F) → trade setup if grade C+.
**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+.
**Regime-Adaptive Weights:** Market classified as `trending_up`, `trending_down`, or `ranging` via ADX + EMA. Trending boosts EMA weight (2.0x), ranging boosts RSI/BB (2.0x). This is the core edge.
**Regime-Adaptive Weights:** Market classified as `trending_up`, `trending_down`, `ranging`, or `transitioning` via ADX + EMA + ADX slope. Gold-specific weights per regime:
- **Trending:** MACD (2.0), EMA (2.0), Divergence (2.0), Keltner (1.5), ROC (1.5)
- **Ranging:** Divergence (2.5), Keltner (2.0), RSI (1.5), BB (1.5), MACD (1.5)
- **Transitioning:** Keltner (2.5), MACD (2.5), ROC (2.0), Divergence (2.0), EMA (1.5)
**Pair-Specific Strategies:** XAU/USD (oversold-bounce: RSI<38 + triple-TF EMA200 confirmation), EUR/USD and GBP/USD (pullback-buy: RSI 30-55 + BB<0.75 + dual-TF EMA200). Each has hour-blocked windows from backtest optimization.
**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.
**SELL Suppression:** Forex SELL signals are suppressed for all pairs except XAU/USD. Backtesting showed 0% win rate for forex shorts.
**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.
**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 1.2:1.
**Indicators (9 scored):** EMA Trend, RSI, Bollinger Bands, MACD, ADX, Keltner Channels (TTM Squeeze), ROC (Rate of Change), Divergence, Candlestick Patterns.
**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.
## How to Run
```bash
# CLI (single USD/JPY analysis)
# CLI (XAU/USD analysis)
python main.py # H1 default
python main.py --timeframe M15 --detail --json
@@ -59,6 +64,9 @@ TELEGRAM_TOKEN=<token> TELEGRAM_CHAT_ID=<id> python telegram_bot.py
# Tests
python test_all.py
# Backtest
python backtest/gpu_backtest.py --pair XAUUSD --days 365
```
## Environment Variables
@@ -68,7 +76,6 @@ python test_all.py
| `TWELVE_DATA_API_KEY` | Market data API key | Hardcoded fallback in config |
| `TELEGRAM_TOKEN` | Telegram bot token | Hardcoded fallback |
| `TELEGRAM_CHAT_ID` | Auto-scan chat ID (enables boot auto-scan) | Hardcoded fallback |
| `FB2_EMA_LO` / `FB2_EMA_HI` | EMA200 distance thresholds (%) | 0.5 / 1.5 |
## Dependencies
@@ -80,23 +87,19 @@ python test_all.py
- **Rate limit:** 55 credits/min (Grow plan), enforced by sliding-window throttle
- **Cache:** In-memory dict, TTL = candle duration of the timeframe
- **Validation:** Drops NaN rows, forward-fills gaps (limit 3), fixes OHLC inconsistencies, removes outliers (>10σ), strips future timestamps, deduplicates
- **WebSocket:** EUR/USD and XAU/USD only (Grow plan WS limit); GBP/USD and USD/JPY via REST-only scans
- **WebSocket:** XAU/USD only
## Telegram Bot
- **Auto-scan:** M5 (data-only, no alerts), M15, H1, H4 at candle boundaries + 10s buffer
- **WebSocket:** Streams live ticks for EUR/USD + XAU/USD; triggers immediate M15 scan on key level breach (swing S/R, BB, EMA200) with 5-min cooldown
- **Live dashboard:** Edit-in-place message, 30s refresh, shows all pairs/timeframes/prices/setups
- **Commands:** `/start`, `/autoscan`, `/status`, `/cache`, `/clearcache`, `/help`
- **Correlation warning:** Flags same-direction signals on EUR/USD + GBP/USD (USD-weakness group)
- **Manual scan:** Buttons for M15/H1/H4 individual scans + "Scan All TFs" multi-timeframe summary
- **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
- **Live dashboard:** Edit-in-place message, 30s refresh, shows XAU/USD across timeframes
- **Commands:** `/start`, `/scan`, `/autoscan`, `/status`, `/cache`, `/clearcache`, `/help`
## Backtesting
The `backtest/` directory (gitignored) contains pair-specific backtesting scripts, GPU-accelerated optimizers, and historical parquet data. Strategies were optimized on 1-year M15 data. Results drove the current strategy configs in `config.py`.
## Planned: MT5 Auto-Execution
Documented in `mt5.md`. REST bridge architecture: Linux bot → HTTP → Windows FastAPI server wrapping MetaTrader5 COM. Not yet implemented. Key: `MT5Config` dataclass, idempotent orders, position-size from bridge-side tick values.
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.
## Code Conventions
@@ -104,7 +107,7 @@ Documented in `mt5.md`. REST bridge architecture: Linux bot → HTTP → Windows
- Dataclasses for all config and output structures
- `SignalStrength` enum (-2 to +2) is the universal signal currency
- Indicators stored as `Dict[str, IndicatorSignal]` in `TechnicalAnalysis`
- Key levels stored as `Dict[str, float]` — prefixed `swing_high_`, `swing_low_`, `ema_`, `bb_`, `atr`
- Private indicator data attached as `result._rsi_series`, `result._macd_histogram` (underscore prefix, skipped by composite scorer)
- Key levels stored as `Dict[str, float]` — prefixed `swing_high_`, `swing_low_`, `ema_`, `bb_`, `kc_`, `atr`
- Private indicator data attached as `result._rsi_series`, `result._macd_histogram`, `result._adx_slope`, `result._kc_squeeze` (underscore prefix, skipped by composite scorer)
- Blocking signal computation runs in `ThreadPoolExecutor(max_workers=4)` to avoid blocking the async Telegram event loop
- Shared `ForexDataProvider` instance across all scans for cache reuse