exit-strategies Checked

def percentage_trailing_stop(
    current_price: float,
    highest_since_entry: float,
    trail_pct: float = 0.10,
) -> tuple[float, bool]:
    """Return (stop_level, triggered)."""
    highest = max(highest_since_entry, current_price)
    stop = highest * (1 - trail_pct)
    return stop, current_price <= stop

**ATR trailing (Chandelier Exit):**

def chandelier_exit(
    highs: list[float],
    atr_value: float,
    multiplier: float = 2.5,
    lookback: int = 22,
) -> float:
    """Highest high over lookback minus ATR * multiplier."""
    highest_high = max(highs[-lookback:])
    return highest_high - (atr_value * multiplier)

**EMA trailing:**

# Exit when close < EMA for M consecutive bars
ema = df.ta.ema(length=20)
below_ema = df["close"] < ema
consecutive_below = below_ema.rolling(3).sum() == 3  # 3 bars below

Typical EMA periods: 10 (scalp), 20 (day trade), 50 (swing).

See references/trailing_stops.md for Parabolic SAR, SuperTrend, and step trailing.

### 4. Time-Based Exits

Exit if the trade hasn't moved in your favor within a defined window.

bars_since_entry = current_bar - entry_bar
if bars_since_entry > max_hold_bars and current_pnl <= 0:
    exit_reason = "time_stop"

Guidelines:

• **Scalp**: 5–15 minutes
• **Day trade**: 4–8 hours
• **Swing**: 3–5 days
• **PumpFun snipe**: 2–10 minutes (token-specific)

Time stops prevent capital from sitting in dead trades.

### 5. Signal-Based Exits

Exit when the indicator that generated the entry signal reverses.

# RSI reversal exit
rsi = df.ta.rsi(length=14)
if position == "long" and rsi.iloc[-1] > 70:
    exit_reason = "rsi_overbought"

# MACD crossover exit
macd = df.ta.macd()
if macd["MACDs_12_26_9"].iloc[-1] < macd["MACDh_12_26_9"].iloc[-1]:
    exit_reason = "macd_bearish_cross"

Signal exits work well when combined with trailing stops — the signal triggers

tightening the trail rather than an immediate full exit.

### 6. Liquidity-Based Exits

Exit when volume or liquidity deteriorates, signaling reduced ability to exit cleanly.

recent_vol = df["volume"].rolling(10).mean().iloc[-1]
baseline_vol = df["volume"].rolling(50).mean().iloc[-1]

if recent_vol < baseline_vol * 0.3:  # Volume dropped to 30% of baseline
    exit_reason = "liquidity_deterioration"

Critical for low-cap Solana tokens where liquidity can evaporate rapidly.

PumpFun-Specific Exit Rules

PumpFun tokens have unique dynamics requiring specialized exit logic.

### Pre-Graduation Exits

Tokens on the bonding curve before reaching 85 SOL fill:

bonding_fill_pct = current_fill_sol / 85.0

if bonding_fill_pct > 0.90:
    # Near graduation — decide: hold through or exit before
    # Graduation creates volatility spike, both up and down
    pass

if bonding_fill_pct < 0.50 and time_since_entry > 300:  # 5 min
    exit_reason = "stalled_bonding_curve"

### Volume Decay Exits

buy_vol_1m = get_buy_volume(token, "1m")
buy_vol_5m = get_buy_volume(token, "5m") / 5  # Normalize to per-minute

if buy_vol_1m < buy_vol_5m * 0.3:
    exit_reason = "buy_volume_decay"

### Time Decay for PumpFun

Most PumpFun tokens that will succeed show momentum within the first few minutes:

| Timeframe | Action |

|-----------|--------|

| 0–2 min | Hold — too early to judge |

| 2–5 min | Exit if no 2× from entry |

| 5–10 min | Exit if no 3× from entry |

| 10+ min | Should be trailing, not hoping |

Combining Exit Rules

A complete exit plan layers multiple rules. Here is a recommended template:

exit_plan = {
    "hard_stop": {
        "type": "fixed_percentage",
        "value": 0.20,  # -20% max loss
        "priority": 1,   # Checked first, always honored
    },
    "atr_stop": {
        "type": "atr_trailing",
        "multiplier": 2.5,
        "atr_length": 14,
        "priority": 2,
    },
    "take_profit": {
        "type": "scaled",
        "tranches": [
            {"at_rr": 2, "sell_pct": 0.25},
            {"at_rr": 4, "sell_pct": 0.25},
            {"at_rr": 8, "sell_pct": 0.25},
        ],
        "priority": 3,
    },
    "time_stop": {
        "type": "max_bars",
        "value": 50,
        "condition": "if_not_profitable",
        "priority": 4,
    },
}

**Priority hierarchy**: Hard stop > ATR trailing > Take profit > Time stop.

The hard stop is always active and never overridden. The ATR trailing stop activates

after the first take-profit tranche fills. The time stop only fires if the trade is

not yet profitable.

Common Exit Mistakes

| Mistake | Problem | Fix |

|---------|---------|-----|

| No stop loss | Unlimited downside | Always define max loss before entry |

| Moving stops wider | Increases risk after the fact | Never move stops away from price |

| Not taking profits | Winners become losers | Use scaled exits |

| All-or-nothing exits | Leaves money on the table or exits too early | Scale out in tranches |

| Round-number stops | Cluster with other traders, get hunted | Offset by small random amount |

| Too-tight stops | Stopped out by normal volatility | Use ATR-based stops |

| Hoping instead of trailing | Gives back profits | Activate trail after first