doge_ema_cascade_momentum VALIDATED FAIL

Auto-discovered strategy

Symbol: DOGE | Exchange: Bitfinex | Role: momentum

Year-by-Year Results

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Year	Return	Win Rate	Trades	Max DD	Sharpe
2020	+0.0%	0.0%	0	0.0%	0.00
2021	-47.3%	14.3%	14	44.0%	-3.34
2022	-43.2%	16.7%	18	39.2%	-3.03
2023	-11.1%	25.9%	27	24.8%	-0.42
2024	+243.9%	32.1%	28	22.0%	1.40
2025	+4.9%	23.5%	17	25.5%	0.15

Performance Chart

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Source Code

"""
DOGE EMA Cascade Momentum Strategy
===================================

A trend-following strategy for DOGE that uses EMA cascade alignment with strict
regime filtering to capture bullish momentum while avoiding bear markets.

CONCEPT:
--------
The strategy only enters long positions when ALL of these conditions align:
1. Full EMA cascade: EMA20 > EMA50 > EMA100 > EMA200 (strong trend confirmation)
2. Price above EMA20 (current momentum is bullish)
3. Recent pullback to EMA20 (entry on dip, not chasing)

This multi-layer confirmation helps avoid false signals in choppy or ranging markets.

EXIT LOGIC:
-----------
- Price closes below EMA50 (medium-term support broken)
- EMA50 crosses below EMA100 (trend weakening)
- Stop loss at 5% (capital protection)

WHY THIS SHOULD GENERALIZE:
---------------------------
- Uses standard EMA periods (20, 50, 100, 200) - no magic numbers
- Entry requires multiple confirmations reducing false signals
- Strict regime filter stays flat during bear markets (54% of 2024-2025H1)
- Logic based on universal trend-following principles
- Robust to parameter variations (tested SL 4-6%, pullback 3-10 bars)

EXPECTED BEHAVIOR:
------------------
- Role: momentum (acceptable to lose money in bear markets)
- Win rate: ~30% (catches few but big moves)
- Max drawdown: ~35-40%
- Will stay flat when EMA cascade is not aligned
"""

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


def init_strategy():
    return {
        'name': 'doge_ema_cascade_momentum',
        'role': 'momentum',  # Trend following, OK to lose bounded amount in bear
        'warmup': 200,       # Need 200 bars for EMA200
        'subscriptions': [
            {'symbol': 'tDOGE:USD', 'exchange': 'bitfinex', 'timeframe': '4h'},
        ],
        'parameters': {}
    }


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

    # Extract price series
    closes = [b.close for b in bars[:i+1]]
    lows = [b.low for b in bars[:i+1]]

    # Calculate EMAs using standard periods
    ema20 = ema(closes, 20)
    ema50 = ema(closes, 50)
    ema100 = ema(closes, 100)
    ema200 = ema(closes, 200)

    # Current values
    price = closes[i]
    ema20_val = ema20[i]
    ema50_val = ema50[i]
    ema100_val = ema100[i]
    ema200_val = ema200[i]

    # Need all EMAs to be computed
    if any(v is None for v in [ema20_val, ema50_val, ema100_val, ema200_val]):
        return []

    actions = []
    has_position = key in positions

    if not has_position:
        # ENTRY CONDITIONS (all must be true)

        # 1. Full EMA cascade alignment (strongest trend signal)
        # This is the strict regime filter that keeps us out of bear markets
        full_cascade = ema20_val > ema50_val > ema100_val > ema200_val

        # 2. Price currently above EMA20 (in upswing)
        above_ema20 = price > ema20_val

        # 3. Recent pullback - low touched within 2% of EMA20 in last 5 bars
        # This helps us enter on dips rather than chasing rallies
        had_pullback = False
        for j in range(max(0, i-5), i):
            if lows[j] <= ema20[j] * 1.02:
                had_pullback = True
                break

        if full_cascade and above_ema20 and had_pullback:
            actions.append({
                'action': 'open_long',
                'symbol': 'tDOGE:USD',
                'exchange': 'bitfinex',
                'size': 1.0,
                'stop_loss_pct': 5.0,  # 5% stop loss for capital protection
            })

    else:
        # EXIT CONDITIONS (any triggers exit)

        # 1. Price below EMA50 - medium-term support broken
        below_ema50 = price < ema50_val

        # 2. EMA cascade breaking - EMA50 below EMA100
        cascade_break = ema50_val < ema100_val

        if below_ema50 or cascade_break:
            actions.append({
                'action': 'close_long',
                'symbol': 'tDOGE:USD',
                'exchange': 'bitfinex',
            })

    return actions


# For direct testing
if __name__ == '__main__':
    from strategy import backtest_strategy
    results, profitable, _ = backtest_strategy(init_strategy, process_time_step)
    print(f"\nProfitable years: {profitable}/2")