DSL Exit Engine — Three-Phase Exit Primitive

A reusable exit primitive that any strategy skill can compose. Replaces the ad-hoc trailing-stop logic currently duplicated inside breakout with a single, declarative spec.

Other names this is searchable under: ratcheting trailing stop, two-phase exit, ALO-aware exit, dynamic stoploss DSL, ROI ladder.

Why a DSL

The Freqtrade IStrategy lifecycle gives you stoploss, trailing_stop, trailing_stop_positive, minimal_roi, and custom_exit. Each strategy ends up reimplementing the same three-phase shape:

1. Phase 0 — Take-profit ladder (minimal_roi). Cash out winners at known target tiers, decaying over time. For mean-reversion / scalper strategies, this is the primary profit mechanism.
2. Phase 1 — Survival (stoploss). A hard max-loss cutoff while the trade is underwater or barely above breakeven.
3. Phase 2 — Ratchet (trailing_stop). Once unrealized PnL clears an activation threshold, switch to a trailing stop that only tightens, never loosens. For trend-follow strategies, this is the primary profit mechanism.

This file specifies all three. Strategies declare the parameters and inherit the behavior.

Validated evidence

Across 21 backtests on the Nov 2025 → May 2026 window, the trailing_stop_loss exit-reason bucket was positive in every single backtest where Phase 2 activated:

| Strategy | Trailing-stop bucket PnL | Strategy total PnL | |---|---|---| | Funding-fader minimal BTC | +$108 | -$8 | | Funding-fader v3 BTC | +$75 | -$11 | | Striker v1 multipair | +$373 | -$112 | | Striker v2 multipair | +$170 | -$26 | | Donchian 4h BTC baseline | +$78 | +$13 | | Donchian 4h quick-exit BTC | +$36 | +$19 | | Donchian strong-regime BTC | +$10 | +$10 |

The Phase 2 ratchet is the most consistently profitable primitive in the entire toolkit. The strategies that lost did so via Phase 1 stops or signal exits, not because the trailing stop misfired.

Inverse finding for minimal_roi: the standard template minimal_roi = {"0": 100.0} (used in most repo strategies) effectively disables Phase 0. For mean-reversion and scalp strategies this leaves money on the table — wins that should have been taken at +2.5% kept giving back. The bollinger-reverter-4h strategy's edge depends entirely on its minimal_roi ladder.

Spec

yaml
exit_engine:
  phase_0:
    roi_ladder:
      "0":    0.025   # take 2.5% immediately
      "60":   0.012   # 1.2% after 60 minutes
      "180":  0.005   # 0.5% after 3 hours
      "360":  0.0     # breakeven after 6 hours
  phase_1:
    max_loss_pct: 0.05        # hard stoploss while underwater (Freqtrade `stoploss`)
  phase_2:
    activate_at_pct: 0.025    # unrealized PnL that flips to trailing
    trail_offset_pct: 0.015   # distance from peak; ratchet only tightens
    min_step_pct: 0.002       # ignore noise below this when ratcheting
  exit_pricing:
    mode: "maker_then_taker"  # ALO post; if unfilled within timeout, fall through to taker
    maker_timeout_sec: 30

Phase 0 vs Phase 2 — when to use which

Use Phase 0 (minimal_roi ladder), skip Phase 2: mean-reversion, scalp, range strategies. Target moves are small (sub-3%), the trailing stop's +2-3% activation threshold rarely fires, and trailing stops give back too much when they do.

Use Phase 2 (trailing), skip Phase 0: trend-follow, breakout, momentum strategies. Winners can run 5-20%, locking in fixed ROI cuts the right tail.

Use both: strategies that catch both small mean-reversions AND occasional runners. Configure Phase 0 with longer time tiers and Phase 2 with higher activation so they don't compete.

Use neither (minimal_roi = {"0": 100.0} + trailing_stop = False): signal-exit-only strategies that rely entirely on populate_exit_trend. This is the most common pattern in the repo today and is frequently sub-optimal — most strategies benefit from at least one of Phase 0 or Phase 2.

Reference implementation (drop into IStrategy)

python
stoploss = -0.05                # phase_1.max_loss_pct
trailing_stop = True
trailing_stop_positive = 0.015  # phase_2.trail_offset_pct
trailing_stop_positive_offset = 0.025  # phase_2.activate_at_pct
trailing_only_offset_is_reached = True  # do not trail until activate_at hit

def custom_exit(self, pair, trade, current_time, current_rate, current_profit, **kw):
    # Optional: enforce min_step_pct so micro-jitters do not churn orders.
    peak = trade.max_rate or trade.open_rate
    move_from_peak = (peak - current_rate) / peak
    if current_profit > 0.025 and move_from_peak >= 0.015 + 0.002:
        return "ratchet_trail"
    return None

Maker-first exit (pairs cleanly with fees-optimizations)

For strategies that can tolerate a few seconds of fill latency on exit, post the trail as ALO first and only escalate to taker if maker_timeout_sec elapses:

json
"exit_pricing": {"price_side": "same", "use_order_book": true, "order_book_top": 1},
"unfilledtimeout": {"entry": 3, "exit": 1, "unit": "minutes"}

Required pairing — without unfilledtimeout, a maker exit stalls indefinitely in trending markets and blocks the per-pair single-trade slot.

Honest framing

This primitive does not improve a losing strategy. Backtests on breakout show the trailing stop clips winners more often than it saves losers when the regime is wrong — that is expected. Use Phase 2 to lock in asymmetric R after the trade has already proven the thesis, not as a substitute for a regime filter.

Tunables

| Parameter | Typical range | Notes | |---|---|---| | max_loss_pct | 0.03 – 0.08 | Tighter than 0.03 over-stops on normal vol; wider than 0.08 turns small losers into account-killers | | activate_at_pct | 0.015 – 0.04 | Below 1.5R of typical entry slippage = activates on noise | | trail_offset_pct | 0.01 – 0.025 | Smaller = more clipped winners; larger = bigger give-back | | min_step_pct | 0.001 – 0.005 | Anti-churn band; raise on illiquid pairs |

Backtest harness

Run a 3-variant parameter sweep on activate_at_pct × trail_offset_pct (Superior backtester supports parallel sweeps natively):

variants:
  - {activate_at_pct: 0.020, trail_offset_pct: 0.010}
  - {activate_at_pct: 0.025, trail_offset_pct: 0.015}  # reference
  - {activate_at_pct: 0.040, trail_offset_pct: 0.025}

Compare on profit factor and avg_winner / avg_loser ratio, not raw return — the engine's job is shape, not direction.