from __future__ import annotations import json from dataclasses import dataclass, replace from pathlib import Path from typing import Any from config import BotConfig, PROJECT_ROOT PRESETS_FILE = PROJECT_ROOT / "strategy_presets.json" CONFIG_FIELDS = set(BotConfig.__dataclass_fields__.keys()) @dataclass(frozen=True) class StrategyPreset: strategy_id: str label: str source: str parameters: dict[str, Any] tags: tuple[str, ...] = () def _as_preset(row: dict[str, Any]) -> StrategyPreset: return StrategyPreset( strategy_id=str(row["strategy_id"]), label=str(row.get("label") or row["strategy_id"]), source=str(row.get("source") or "unknown"), parameters=dict(row.get("parameters") or {}), tags=tuple(str(tag) for tag in row.get("tags", ())), ) def build_candidate_presets() -> list[StrategyPreset]: """Hand-picked paper-only challengers derived from V59-V61 lessons. These are deliberately conservative: trade size is capped at current paper size, hard stops stay bounded, and every preset remains suitable for paper/backtest tournaments before any live-risk discussion. """ rows = [ { "strategy_id": "candidate_v62_anti_chop_context", "label": "Candidate V62 Anti-Chop Context", "source": "candidate:context-filter", "tags": ("candidate", "context-aware", "anti-chop"), "parameters": { "max_total_trades": 3, "default_leverage": 5, "trade_size_usd": 50.0, "min_volume_24h": 15_000_000, "cooldown_minutes": 90, "flash_crash_trigger_pct": 5.0, "atr_sl_multiplier": 1.8, "break_even_activation_pct": 0.45, "v_shape_activation_pct": 1.4, "v_shape_trail_dist_pct": 0.65, "dead_fish_time_limit_mins": 20, "max_hard_stop_pct": 3.0, }, }, { "strategy_id": "candidate_v62_scalp_fast_rebound", "label": "Candidate V62 Scalp Fast Rebound", "source": "candidate:fast-rebound", "tags": ("candidate", "scalp", "fast-rebound"), "parameters": { "max_total_trades": 2, "default_leverage": 5, "trade_size_usd": 40.0, "min_volume_24h": 20_000_000, "cooldown_minutes": 45, "flash_crash_trigger_pct": 3.8, "atr_sl_multiplier": 1.2, "break_even_activation_pct": 0.25, "v_shape_activation_pct": 0.9, "v_shape_trail_dist_pct": 0.45, "dead_fish_time_limit_mins": 8, "max_hard_stop_pct": 2.2, }, }, { "strategy_id": "candidate_v62_deep_capitulation", "label": "Candidate V62 Deep Capitulation", "source": "candidate:deep-dip", "tags": ("candidate", "strict-trigger", "deep-dip"), "parameters": { "max_total_trades": 2, "default_leverage": 5, "trade_size_usd": 50.0, "min_volume_24h": 10_000_000, "cooldown_minutes": 120, "flash_crash_trigger_pct": 6.5, "atr_sl_multiplier": 2.0, "break_even_activation_pct": 0.6, "v_shape_activation_pct": 1.8, "v_shape_trail_dist_pct": 0.9, "dead_fish_time_limit_mins": 30, "max_hard_stop_pct": 4.0, }, }, { "strategy_id": "candidate_v62_loose_trend_rebound", "label": "Candidate V62 Loose Trend Rebound", "source": "candidate:trend-rebound", "tags": ("candidate", "trend-up", "looser-stop"), "parameters": { "max_total_trades": 3, "default_leverage": 5, "trade_size_usd": 50.0, "min_volume_24h": 25_000_000, "cooldown_minutes": 60, "flash_crash_trigger_pct": 4.2, "atr_sl_multiplier": 2.2, "break_even_activation_pct": 0.6, "v_shape_activation_pct": 1.6, "v_shape_trail_dist_pct": 0.8, "dead_fish_time_limit_mins": 35, "max_hard_stop_pct": 4.5, }, }, { "strategy_id": "candidate_v62_micro_size_explorer", "label": "Candidate V62 Micro Size Explorer", "source": "candidate:sample-builder", "tags": ("candidate", "sample-builder", "micro-size"), "parameters": { "max_total_trades": 5, "default_leverage": 3, "trade_size_usd": 20.0, "min_volume_24h": 8_000_000, "cooldown_minutes": 30, "flash_crash_trigger_pct": 3.5, "atr_sl_multiplier": 1.4, "break_even_activation_pct": 0.3, "v_shape_activation_pct": 1.0, "v_shape_trail_dist_pct": 0.5, "dead_fish_time_limit_mins": 12, "max_hard_stop_pct": 2.5, }, }, { "strategy_id": "candidate_v62_quality_only", "label": "Candidate V62 Quality Only", "source": "candidate:high-liquidity", "tags": ("candidate", "quality", "high-liquidity"), "parameters": { "max_total_trades": 2, "default_leverage": 4, "trade_size_usd": 50.0, "min_volume_24h": 50_000_000, "cooldown_minutes": 120, "flash_crash_trigger_pct": 5.5, "atr_sl_multiplier": 1.6, "break_even_activation_pct": 0.4, "v_shape_activation_pct": 1.25, "v_shape_trail_dist_pct": 0.6, "dead_fish_time_limit_mins": 18, "max_hard_stop_pct": 3.0, }, }, { "strategy_id": "candidate_v63_loose_fast_decay", "label": "Candidate V63 Loose Fast Decay", "source": "candidate:parameter-sweep:2026-05-29", "tags": ("candidate", "sweep-winner", "loose-rebound", "fast-decay"), "parameters": { "max_total_trades": 3, "default_leverage": 5, "trade_size_usd": 50.0, "min_volume_24h": 25_000_000, "cooldown_minutes": 60, "flash_crash_trigger_pct": 4.0, "atr_sl_multiplier": 2.2, "break_even_activation_pct": 0.6, "v_shape_activation_pct": 1.6, "v_shape_trail_dist_pct": 0.5, "dead_fish_time_limit_mins": 25, "max_hard_stop_pct": 4.5, }, }, { "strategy_id": "candidate_v64_squeeze_survival_strict", "label": "Candidate V64 Squeeze Survival Strict", "source": "candidate:pre-handover-lessons:squeeze-breakout", "tags": ("candidate", "paper-only", "pre-handover-lessons", "squeeze-breakout", "tight-survival"), "parameters": { "max_total_trades": 2, "default_leverage": 5, "trade_size_usd": 40.0, "min_volume_24h": 20_000_000, "cooldown_minutes": 90, "flash_crash_trigger_pct": 4.8, "atr_sl_multiplier": 1.4, "break_even_activation_pct": 0.4, "v_shape_activation_pct": 1.2, "v_shape_trail_dist_pct": 0.45, "dead_fish_time_limit_mins": 12, "max_hard_stop_pct": 2.6, }, }, { "strategy_id": "candidate_v64_squeeze_survival_wide", "label": "Candidate V64 Squeeze Survival Wide", "source": "candidate:pre-handover-lessons:squeeze-breakout", "tags": ("candidate", "paper-only", "pre-handover-lessons", "squeeze-breakout", "survival"), "parameters": { "max_total_trades": 3, "default_leverage": 5, "trade_size_usd": 50.0, "min_volume_24h": 15_000_000, "cooldown_minutes": 75, "flash_crash_trigger_pct": 4.2, "atr_sl_multiplier": 1.6, "break_even_activation_pct": 0.55, "v_shape_activation_pct": 1.4, "v_shape_trail_dist_pct": 0.65, "dead_fish_time_limit_mins": 15, "max_hard_stop_pct": 3.0, }, }, { "strategy_id": "candidate_v65_signal_sampler_conservative", "label": "Candidate V65 Signal Sampler Conservative", "source": "candidate:research-sampler:near-miss", "tags": ("candidate", "paper-only", "research-sampler", "not-champion", "data-collection"), "parameters": { "max_total_trades": 2, "default_leverage": 3, "trade_size_usd": 20.0, "wallet_equity_usdc": 500.0, "risk_per_trade_pct": 0.5, "position_sizing_mode": "risk", "max_position_margin_pct": 10.0, "max_position_notional_pct": 45.0, "min_order_notional_usd": 12.0, "min_volume_24h": 8_000_000, "cooldown_minutes": 45, "flash_crash_trigger_pct": 3.0, "crash_roe_trigger_pct": 9.0, "atr_sl_multiplier": 1.0, "break_even_activation_pct": 0.35, "v_shape_activation_pct": 1.0, "v_shape_trail_dist_pct": 0.4, "dead_fish_time_limit_mins": 10, "max_hard_stop_pct": 2.0, "max_scan_coins": 30, }, }, { "strategy_id": "candidate_v65_signal_sampler_aggressive", "label": "Candidate V65 Signal Sampler Aggressive", "source": "candidate:research-sampler:near-miss", "tags": ("candidate", "paper-only", "research-sampler", "not-champion", "data-collection", "aggressive-sampler"), "parameters": { "max_total_trades": 2, "default_leverage": 3, "trade_size_usd": 10.0, "wallet_equity_usdc": 500.0, "risk_per_trade_pct": 0.5, "position_sizing_mode": "risk", "max_position_margin_pct": 10.0, "max_position_notional_pct": 45.0, "min_order_notional_usd": 12.0, "min_volume_24h": 6_000_000, "cooldown_minutes": 30, "flash_crash_trigger_pct": 2.5, "crash_roe_trigger_pct": 7.5, "atr_sl_multiplier": 0.9, "break_even_activation_pct": 0.25, "v_shape_activation_pct": 0.8, "v_shape_trail_dist_pct": 0.35, "dead_fish_time_limit_mins": 8, "max_hard_stop_pct": 2.0, "max_scan_coins": 30, }, }, { "strategy_id": "candidate_v66_squeeze_breakout_sampler", "label": "Candidate V66 Squeeze Breakout Sampler", "source": "candidate:strategy-lab:grid_squeeze_w2p5_b1p2", "tags": ("candidate", "paper-only", "research-sampler", "not-champion", "squeeze-breakout", "non-drop"), "parameters": { "strategy_family": "volatility_squeeze_breakout", "max_total_trades": 2, "default_leverage": 3, "trade_size_usd": 15.0, "wallet_equity_usdc": 500.0, "risk_per_trade_pct": 0.75, "position_sizing_mode": "risk", "max_position_margin_pct": 20.0, "max_position_notional_pct": 60.0, "min_order_notional_usd": 12.0, "min_volume_24h": 10_000_000, "cooldown_minutes": 45, "squeeze_lookback_ticks": 24, "squeeze_max_band_width_pct": 2.5, "squeeze_breakout_pct": 1.2, "atr_sl_multiplier": 1.0, "break_even_activation_pct": 0.35, "v_shape_activation_pct": 1.0, "v_shape_trail_dist_pct": 0.45, "dead_fish_time_limit_mins": 10, "max_hard_stop_pct": 2.0, "max_scan_coins": 30, }, }, { "strategy_id": "candidate_v67_trend_pullback_sma_vwap", "label": "Candidate V67 Trend Pullback SMA/VWAP", "source": "candidate:indicator-expansion:trend-pullback", "tags": ("candidate", "paper-only", "research-sampler", "not-champion", "indicator", "trend-pullback", "sma", "vwap"), "parameters": { "strategy_family": "trend_pullback_sma_vwap", "max_total_trades": 2, "default_leverage": 3, "trade_size_usd": 15.0, "wallet_equity_usdc": 500.0, "risk_per_trade_pct": 0.5, "position_sizing_mode": "risk", "max_position_margin_pct": 12.0, "max_position_notional_pct": 45.0, "min_order_notional_usd": 12.0, "min_volume_24h": 15_000_000, "cooldown_minutes": 60, "trend_pullback_min_rsi": 35.0, "trend_pullback_max_rsi": 70.0, "trend_pullback_max_distance_pct": 1.5, "atr_sl_multiplier": 1.2, "break_even_activation_pct": 0.45, "v_shape_activation_pct": 1.2, "v_shape_trail_dist_pct": 0.5, "dead_fish_time_limit_mins": 45, "max_hard_stop_pct": 2.0, "max_scan_coins": 20, }, }, { "strategy_id": "candidate_v68_bollinger_rsi_mean_reversion", "label": "Candidate V68 Bollinger RSI Mean Reversion", "source": "candidate:indicator-expansion:mean-reversion", "tags": ("candidate", "paper-only", "research-sampler", "not-champion", "indicator", "bollinger", "rsi", "mean-reversion"), "parameters": { "strategy_family": "bollinger_rsi_mean_reversion", "max_total_trades": 2, "default_leverage": 3, "trade_size_usd": 12.0, "wallet_equity_usdc": 500.0, "risk_per_trade_pct": 0.5, "position_sizing_mode": "risk", "max_position_margin_pct": 10.0, "max_position_notional_pct": 40.0, "min_order_notional_usd": 12.0, "min_volume_24h": 15_000_000, "cooldown_minutes": 45, "mean_reversion_max_rsi": 35.0, "mean_reversion_band_tolerance_pct": 0.3, "atr_sl_multiplier": 1.1, "break_even_activation_pct": 0.35, "v_shape_activation_pct": 0.9, "v_shape_trail_dist_pct": 0.4, "dead_fish_time_limit_mins": 30, "max_hard_stop_pct": 2.0, "max_scan_coins": 20, }, }, { "strategy_id": "candidate_v69_squeeze_breakout_confirmed", "label": "Candidate V69 Confirmed Squeeze Breakout", "source": "candidate:indicator-expansion:confirmed-squeeze", "tags": ("candidate", "paper-only", "research-sampler", "not-champion", "indicator", "squeeze-breakout", "confirmed", "non-drop"), "parameters": { "strategy_family": "confirmed_squeeze_breakout", "max_total_trades": 2, "default_leverage": 3, "trade_size_usd": 15.0, "wallet_equity_usdc": 500.0, "risk_per_trade_pct": 0.5, "position_sizing_mode": "risk", "max_position_margin_pct": 12.0, "max_position_notional_pct": 45.0, "min_order_notional_usd": 12.0, "min_volume_24h": 15_000_000, "cooldown_minutes": 60, "squeeze_lookback_ticks": 24, "squeeze_max_band_width_pct": 2.2, "squeeze_breakout_pct": 1.0, "atr_sl_multiplier": 1.0, "break_even_activation_pct": 0.35, "v_shape_activation_pct": 1.0, "v_shape_trail_dist_pct": 0.45, "dead_fish_time_limit_mins": 20, "max_hard_stop_pct": 2.0, "max_scan_coins": 20, }, }, { "strategy_id": "candidate_v73_multi_day_trend_investment", "label": "Candidate V73 Multi-Day Trend Investment", "source": "candidate:indicator-expansion:multi-day-trend", "tags": ("candidate", "paper-only", "research-sampler", "not-champion", "indicator", "multi-day", "trend-investment"), "parameters": { "strategy_family": "multi_day_trend_investment", "max_total_trades": 1, "default_leverage": 1, "trade_size_usd": 20.0, "wallet_equity_usdc": 500.0, "risk_per_trade_pct": 0.5, "position_sizing_mode": "risk", "max_position_margin_pct": 12.0, "max_position_notional_pct": 35.0, "min_order_notional_usd": 12.0, "min_volume_24h": 25_000_000, "cooldown_minutes": 240, "multi_day_min_trend_pct": 2.0, "multi_day_max_pullback_distance_pct": 3.0, "atr_sl_multiplier": 2.0, "break_even_activation_pct": 1.2, "v_shape_activation_pct": 3.0, "v_shape_trail_dist_pct": 1.0, "dead_fish_time_limit_mins": 1440, "max_hard_stop_pct": 4.0, "max_scan_coins": 8, }, }, { "strategy_id": "candidate_v74_relative_strength_breadth_guard", "label": "Candidate V74 Relative Strength Breadth Guard", "source": "candidate:strategy-lab:grid_rs_l24_t4_m3", "tags": ("candidate", "paper-only", "research-sampler", "not-champion", "relative-strength", "breadth-guard", "non-drop"), "parameters": { "strategy_family": "relative_strength_rotation", "max_total_trades": 2, "default_leverage": 2, "trade_size_usd": 12.0, "wallet_equity_usdc": 500.0, "risk_per_trade_pct": 0.4, "position_sizing_mode": "risk", "max_position_margin_pct": 8.0, "max_position_notional_pct": 30.0, "min_order_notional_usd": 12.0, "min_volume_24h": 15_000_000, "cooldown_minutes": 180, "relative_strength_lookback_ticks": 24, "relative_strength_top_n": 4, "relative_strength_min_momentum_pct": 3.0, "relative_strength_min_positive_candidates": 3, "atr_sl_multiplier": 1.2, "break_even_activation_pct": 0.6, "v_shape_activation_pct": 1.8, "v_shape_trail_dist_pct": 0.7, "dead_fish_time_limit_mins": 180, "max_hard_stop_pct": 2.5, "max_scan_coins": 24, }, }, { "strategy_id": "candidate_v75_hybrid_survival_squeeze", "label": "Candidate V75 Hybrid Survival Squeeze", "source": "candidate:paper-learnings:v60-v66-v69", "tags": ("candidate", "paper-only", "research-sampler", "not-champion", "hybrid", "survival", "squeeze-breakout", "quality-whitelist"), "parameters": { "strategy_family": "hybrid_survival_squeeze", "max_total_trades": 2, "default_leverage": 3, "trade_size_usd": 12.0, "wallet_equity_usdc": 500.0, "risk_per_trade_pct": 0.45, "position_sizing_mode": "risk", "max_position_margin_pct": 10.0, "max_position_notional_pct": 40.0, "min_order_notional_usd": 12.0, "min_volume_24h": 12_000_000, "cooldown_minutes": 75, "allowed_coins": ("WLD", "SUI", "ENA", "BTC", "ETH", "LINK", "BCH"), "flash_crash_trigger_pct": 4.0, "crash_roe_trigger_pct": 8.0, "squeeze_lookback_ticks": 24, "squeeze_max_band_width_pct": 2.2, "squeeze_breakout_pct": 1.0, "atr_sl_multiplier": 1.1, "break_even_activation_pct": 0.35, "v_shape_activation_pct": 1.0, "v_shape_trail_dist_pct": 0.45, "dead_fish_time_limit_mins": 15, "max_hard_stop_pct": 2.0, "max_scan_coins": 12, }, }, ] return [_as_preset(row) for row in rows] def load_strategy_presets(path: str | Path = PRESETS_FILE, *, include_candidates: bool = True) -> dict[str, StrategyPreset]: preset_path = Path(path) raw = json.loads(preset_path.read_text(encoding="utf-8")) if preset_path.exists() else {"presets": []} presets = [_as_preset(row) for row in raw.get("presets", [])] if include_candidates: presets.extend(build_candidate_presets()) by_id: dict[str, StrategyPreset] = {} for preset in presets: if preset.strategy_id in by_id: raise ValueError(f"Duplicate strategy_id: {preset.strategy_id}") by_id[preset.strategy_id] = preset return by_id def preset_to_config(preset: StrategyPreset, base: BotConfig | None = None, *, runtime_dir: Path | None = None) -> BotConfig: cfg = base or BotConfig.from_file() overrides = {key: value for key, value in preset.parameters.items() if key in CONFIG_FIELDS} if runtime_dir is not None: overrides["runtime_dir"] = Path(runtime_dir).expanduser().resolve() return replace(cfg, **overrides) def main() -> int: presets = load_strategy_presets() print(f"Strategy presets: {len(presets)}") for preset in presets.values(): print(f"- {preset.strategy_id}: {preset.label} [{', '.join(preset.tags)}]") return 0 if __name__ == "__main__": raise SystemExit(main())