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eth_ema_rejection_hedge VALIDATED PASS

Auto-discovered strategy

Symbol: ETH | Exchange: Bitfinex | Role: hedge

6/6
Profitable Years
+502.9%
Total Return
70.1%
Avg Win Rate
4.54
Avg Sharpe

Year-by-Year Results

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Year Return Win Rate Trades Max DD Sharpe
2020 +55.6% 63.6% 44 2.9% 3.26
2021 +119.0% 76.3% 38 2.8% 6.15
2022 +115.6% 77.2% 57 5.5% 5.62
2023 +50.4% 70.6% 51 2.3% 3.72
2024 +86.5% 69.4% 49 3.6% 4.63
2025 +75.8% 63.6% 55 3.4% 3.86

Performance Chart

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Walk-Forward Validation PASS

1/1 Windows Profitable
+48.7% OOS Return
0.00 Median Sharpe
0.000 Score
Window Train Period Val Period Val Return Val Test Period Test Return Status
WF-1 2024-01→2025-06 2025-07→2025-12 +48.7% OK 2026-01→ongoing +0.0% PASS

AI Review Score: 85/100

execution
## Strategy Assessment: eth_ema_rejection_hedge ### Strengths **Robust Design Philosophy** - Uses only relative indicators (EMAs, RSI) with standard periods (10, 20, 50, 100, 14) - No magic numbers or curve-fitted parameters - Clean logic: death cross + EMA rejection + weak momentum + red bar confirmation - Appropriate hedge role with asymmetric risk/reward (4% stop, 6% take profit) - Good warmup period (200) matching indicator requirements - Clear exit logic with multiple failure modes (golden cross, RSI recovery, time stop) **Cross-Regime Performance** - Works consistently across all years in train period (2020-2025) - Returns range from 50-120% annually with no single "lucky" year dominating - Win rates stay in healthy 63-77% range across different market conditions - Low drawdowns (2-5%) indicate good risk control across regimes - Strong Sharpe ratios (3.26-6.15) show consistent risk-adjusted performance **Risk Management** - Tight stop loss (4%) appropriate for short-term hedge - High trade frequency (38-57 trades/year) ensures diversification - No concentration risk - returns distributed across many trades - Multiple exit conditions prevent holding losers ### Issues Identified **Execution Concern (Minor)** - Entry condition checks "current bar is red" (closes[i] < opens[i]) - This implicitly requires knowing the close price before entering - While documented as "trade on next bar open", the logic evaluates completed bar patterns - **Recommendation**: Entry should explicitly signal on bar close, execute next bar open - This is a documentation/clarity issue more than a true lookahead bias **Complexity at Acceptable Limit** - Has 6 entry conditions (death_cross, rejection, rsi_weak, rsi_declining, ema50_flat_down, red_bar) - Right at the recommended 5-6 condition maximum - Each condition adds surface area for overfitting - However, all conditions are logically connected to the core thesis ### Verification Against Rules ✅ **No Forbidden Patterns** - No specific price levels - No specific dates or events - No magic numbers - Standard indicator periods only ✅ **Robustness Requirements Met** - Relative indicators only - Works across multiple regimes (bull 2020-2021, bear 2022, consolidation 2023-2024) - Year-over-year consistency demonstrates regime-independence ✅ **Hedge Role Requirements** - Max DD 5.5% < 50% threshold ✓ - Validation return positive ✓ - Sharpe > 0.3 ✓ - Trades > 2 minimum ✓ ✅ **Trade Distribution** - 38-57 trades per year ensures no concentration risk - No way 3 trades could dominate with this volume ### Statistical Significance - Total trades across train period: ~294 trades (6 years × 49 avg) - Win rate: 63-77% with consistent execution - Multiple regime types tested - Strong evidence this is not curve-fitted noise ### Final Assessment This is a **well-designed hedge strategy** with strong fundamentals. The execution clarity issue is minor and doesn't invalidate the approach. The consistent performance across bull/bear/consolidation regimes (2020-2025) with no single dominant year demonstrates genuine edge rather than overfitting. The strategy concept is sound: shorting failed rallies at resistance after death crosses is a classical technical pattern with logical market structure reasoning. The tight risk controls and multiple exit conditions show mature risk management. **Score Justification**: 85/100 (Good tier) - Would be 90+ if execution timing were explicitly clarified - Strong regime-independence and trade distribution - Clean, readable code with proper warmup - Meets all hedge role requirements with margin
Reviewed: 2026-01-14T14:14:47.635703

Source Code

"""
ETH EMA Rejection Hedge Strategy
================================

A hedge strategy that shorts ETH when uptrends show exhaustion and price
rejects from key EMA levels. Captures trend failures by detecting EMA
rejections after short-term death crosses.

Role: hedge
Exchange: bitfinex
Symbol: tETHUSD

Concept:
- When EMA10 < EMA20 (death cross active), the short-term trend is bearish
- When price rallies to test EMA20 or EMA50 but fails to reclaim it, this
  confirms weakness and provides a low-risk short entry
- The strategy profits when these failed recovery attempts lead to continued
  decline

Entry Conditions (all must be met):
1. EMA10 < EMA20 (death cross active - short-term bearish)
2. Price rejected from EMA20 or EMA50 (high touched EMA but close below)
3. RSI in weak zone (35-50) and declining (momentum fading)
4. EMA50 flat or declining (no medium-term support)
5. Current bar is red (bearish confirmation)

Exit Conditions (any triggers exit):
1. EMA10 crosses above EMA20 (golden cross - trend reversal)
2. RSI recovery above 50 (momentum returning)
3. Price closes above EMA20 (failed breakdown)
4. Time stop: 15 bars

Risk Management:
- Stop loss: 4%
- Take profit: 6%

Performance:
- Train 2024: +86.5% | 49 trades | 69% WR
- Train 2025-H1: +21.1% | 23 trades | 56% WR
- Validation 2025-H2: +48.7% | Sharpe 3.47 | PASS
"""

import sys
sys.path.insert(0, '/root/trade_rules')
from lib import ema, rsi


def init_strategy():
    return {
        'name': 'eth_ema_rejection_hedge',
        'role': 'hedge',
        'warmup': 200,
        'subscriptions': [
            {'symbol': 'tETHUSD', 'exchange': 'bitfinex', 'timeframe': '4h'},
        ],
        'parameters': {}
    }


def process_time_step(ctx):
    key = ('tETHUSD', 'bitfinex')
    bars = ctx['bars'][key]
    i = ctx['i']
    positions = ctx['positions']

    # Extract price data
    closes = [b.close for b in bars]
    highs = [b.high for b in bars]
    lows = [b.low for b in bars]
    opens = [b.open for b in bars]

    # Calculate EMAs
    ema_10 = ema(closes, 10)
    ema_20 = ema(closes, 20)
    ema_50 = ema(closes, 50)
    ema_100 = ema(closes, 100)
    rsi_vals = rsi(closes, 14)

    # Check indicator availability
    if ema_10[i] is None or ema_20[i] is None:
        return []
    if ema_50[i] is None or ema_100[i] is None:
        return []
    if rsi_vals[i] is None:
        return []
    if i < 10:
        return []

    actions = []

    if key not in positions:
        # === ENTRY CONDITIONS ===

        # 1. Death cross active: EMA10 < EMA20
        death_cross_active = ema_10[i] < ema_20[i]

        # 2. Price rejected from EMA20 or EMA50
        # High touched EMA but close is below
        rejected_ema20 = highs[i] > ema_20[i] * 0.99 and closes[i] < ema_20[i]
        rejected_ema50 = highs[i] > ema_50[i] * 0.99 and closes[i] < ema_50[i]
        rejection = rejected_ema20 or rejected_ema50

        # 3. RSI weak (35-50) and declining
        rsi_weak = 35 < rsi_vals[i] < 50
        rsi_declining = rsi_vals[i] < rsi_vals[i-1] if i > 0 else False

        # 4. EMA50 flat or declining (no support)
        ema50_flat_down = ema_50[i] <= ema_50[i-5] * 1.005 if i >= 5 else False

        # 5. Red bar (bearish confirmation)
        red_bar = closes[i] < opens[i]

        # All conditions must be met
        if death_cross_active and rejection and rsi_weak and rsi_declining and ema50_flat_down and red_bar:
            actions.append({
                'action': 'open_short',
                'symbol': 'tETHUSD',
                'exchange': 'bitfinex',
                'size': 1.0,
                'stop_loss_pct': 4,
                'take_profit_pct': 6,
            })
    else:
        pos = positions[key]
        if pos.side != 'short':
            return []

        bars_held = i - pos.entry_bar

        # === EXIT CONDITIONS ===

        # 1. Golden cross: EMA10 crosses above EMA20
        golden_cross = (
            ema_10[i] > ema_20[i] and
            i > 0 and ema_10[i-1] <= ema_20[i-1]
        )

        # 2. RSI recovery above 50
        rsi_recovery = rsi_vals[i] > 50

        # 3. Time stop - 15 bars
        time_exit = bars_held >= 15

        # 4. Price closes above EMA20 (trend recovery)
        above_ema20 = closes[i] > ema_20[i]

        if golden_cross or rsi_recovery or time_exit or above_ema20:
            actions.append({
                'action': 'close_short',
                'symbol': 'tETHUSD',
                'exchange': 'bitfinex',
            })

    return actions


# Testing
if __name__ == '__main__':
    from strategy import backtest_strategy, validate_new_strategy

    print("=" * 60)
    print("TRAIN PERIOD BACKTEST")
    print("=" * 60)
    results, profitable, _ = backtest_strategy(init_strategy, process_time_step)

    print("\n" + "=" * 60)
    print("VALIDATION ON UNSEEN DATA")
    print("=" * 60)
    validate_new_strategy(init_strategy, process_time_step)