okx-codex-trader/scripts/search_eth_bb_squeeze_fixed_rr.py

from __future__ import annotations

import argparse
import sys
from dataclasses import dataclass
from pathlib import Path

import pandas as pd

sys.path.insert(0, str(Path(__file__).resolve().parents[1]))

from okx_codex_trader.candles import align_candles_by_ts, load_candles_csv
from okx_codex_trader.models import Candle
from okx_codex_trader.research_metrics import (
    DEFAULT_COSTS,
    DEFAULT_INITIAL_EQUITY,
    DEFAULT_PRIMARY_COST,
    cost_equity_frame,
    equity_metrics,
    format_utc_ts,
    horizon_rows,
    worst_month,
)
from okx_codex_trader.sampled_report import SegmentResult, mark_to_market, trade_equity


ETH_SYMBOL = "ETH-USDT-SWAP"
BTC_SYMBOL = "BTC-USDT-SWAP"
BAR = "15m"
YEARS = 10.0
LEVERAGE = 3
INITIAL_EQUITY = DEFAULT_INITIAL_EQUITY
DATA_DIR = Path("data/okx-candles")
OUTPUT_DIR = Path("reports/eth-exploration")
PRIMARY_COST = DEFAULT_PRIMARY_COST
COSTS = DEFAULT_COSTS
HORIZONS = (
    ("3y", pd.DateOffset(years=3)),
    ("1y", pd.DateOffset(years=1)),
    ("6m", pd.DateOffset(months=6)),
    ("3m", pd.DateOffset(months=3)),
)


@dataclass(frozen=True)
class Variant:
    band_length: int
    bandwidth_lookback: int
    bandwidth_quantile: float
    stop_loss_pct: float
    reward_risk: float
    exit_mode: str
    side_mode: str
    btc_filter: str
    eth_vol_cap: float | None
    dd_overlay: float | None
    cooldown_bars: int
    middle_exit_buffer_pct: float
    middle_exit_confirm_bars: int

    @property
    def take_profit_pct(self) -> float:
        return self.stop_loss_pct * self.reward_risk

    @property
    def name(self) -> str:
        vol = "none" if self.eth_vol_cap is None else f"{self.eth_vol_cap:g}"
        dd = "none" if self.dd_overlay is None else f"{self.dd_overlay:g}"
        return (
            f"bb-squeeze-rr-l{self.band_length}-bw{self.bandwidth_lookback}"
            f"-q{self.bandwidth_quantile:g}-sl{self.stop_loss_pct:g}-rr{self.reward_risk:g}"
            f"-{self.exit_mode}-{self.side_mode}-{self.btc_filter}-vc{vol}-dd{dd}"
            f"-cd{self.cooldown_bars}-mxbuf{self.middle_exit_buffer_pct:g}-mxc{self.middle_exit_confirm_bars}"
        )


def _format_ts(ts: int) -> str:
    return format_utc_ts(ts)


def close_position(
    *,
    trades: list[dict[str, object]],
    exits: list[dict[str, object]],
    position: dict[str, object],
    candle: Candle,
    exit_price: float,
    reason: str,
) -> tuple[float, bool]:
    margin_used = float(position["margin_used"])
    exit_equity = trade_equity(
        side=str(position["side"]),
        margin_used=margin_used,
        entry_price=float(position["entry_price"]),
        exit_price=exit_price,
        leverage=LEVERAGE,
    )
    pnl = exit_equity - margin_used
    trades.append(
        {
            "side": "Long" if position["side"] == "long" else "Short",
            "entry_time": _format_ts(int(position["entry_time"])),
            "exit_time": _format_ts(candle.ts),
            "entry_price": round(float(position["entry_price"]), 4),
            "exit_price": round(exit_price, 4),
            "pnl": round(pnl, 4),
            "return_pct": round(pnl / margin_used * 100.0, 4),
            "cost_weight": 1.0,
            "exit_reason": reason,
        }
    )
    exits.append({"ts": candle.ts, "price": exit_price, "side": position["side"]})
    return exit_equity, pnl > 0.0


def risk_exit_price(position: dict[str, object], candle: Candle) -> tuple[float, str] | None:
    side = str(position["side"])
    stop = float(position["stop_price"])
    take = float(position["take_price"])
    if side == "long":
        if candle.open <= stop:
            return candle.open, "stop_gap"
        if candle.open >= take:
            return candle.open, "take_gap"
        stop_hit = candle.low <= stop
        take_hit = candle.high >= take
    else:
        if candle.open >= stop:
            return candle.open, "stop_gap"
        if candle.open <= take:
            return candle.open, "take_gap"
        stop_hit = candle.high >= stop
        take_hit = candle.low <= take
    if stop_hit:
        return stop, "stop"
    if take_hit:
        return take, "take_profit"
    return None


def run_variant(eth: list[Candle], btc: list[Candle], variant: Variant) -> tuple[SegmentResult, dict[str, int]]:
    eth_close = pd.Series([candle.close for candle in eth], dtype=float)
    btc_close = pd.Series([candle.close for candle in btc], dtype=float)
    middle_series = eth_close.rolling(variant.band_length).mean()
    stdev_series = eth_close.rolling(variant.band_length).std(ddof=0)
    upper_values = middle_series + 2.0 * stdev_series
    lower_values = middle_series - 2.0 * stdev_series
    middle = middle_series.tolist()
    upper = upper_values.tolist()
    lower = lower_values.tolist()
    bandwidth = ((upper_values - lower_values) / middle_series).tolist()
    threshold = pd.Series(bandwidth, dtype=float).rolling(variant.bandwidth_lookback).quantile(variant.bandwidth_quantile).tolist()
    btc_sma = btc_close.rolling(480).mean().tolist()
    btc_momentum = (btc_close / btc_close.shift(96) - 1.0).tolist()
    eth_realized_vol = eth_close.pct_change().rolling(96).std(ddof=0).tolist()
    warmup_bars = max(variant.band_length, variant.bandwidth_lookback, 480, 96)

    equity = INITIAL_EQUITY
    ending_equity = equity
    peak_equity = equity
    max_drawdown = 0.0
    wins = 0
    trades: list[dict[str, object]] = []
    entries: list[dict[str, object]] = []
    exits: list[dict[str, object]] = []
    equity_curve: list[dict[str, float | int]] = []
    position: dict[str, object] | None = None
    pending_entry_side: str | None = None
    pending_exit = False
    middle_exit_streak = 0
    cooldown_until = -1
    exit_counts = {"stop_exits": 0, "take_profit_exits": 0, "signal_exits": 0}

    for index in range(warmup_bars, len(eth)):
        candle = eth[index]
        if pending_exit and position is not None:
            equity, won = close_position(
                trades=trades,
                exits=exits,
                position=position,
                candle=candle,
                exit_price=candle.open,
                reason="signal_middle",
            )
            wins += int(won)
            exit_counts["signal_exits"] += 1
            position = None
            pending_exit = False
            middle_exit_streak = 0
            cooldown_until = index + variant.cooldown_bars
        if pending_entry_side is not None and position is None and equity > 0.0:
            entry_price = candle.open
            position = {
                "side": pending_entry_side,
                "entry_time": candle.ts,
                "entry_price": entry_price,
                "margin_used": equity,
                "stop_price": entry_price * (1.0 - variant.stop_loss_pct if pending_entry_side == "long" else 1.0 + variant.stop_loss_pct),
                "take_price": entry_price * (1.0 + variant.take_profit_pct if pending_entry_side == "long" else 1.0 - variant.take_profit_pct),
            }
            entries.append({"ts": candle.ts, "price": entry_price, "side": pending_entry_side})
            pending_entry_side = None

        current_equity = equity
        if position is not None:
            risk_exit = risk_exit_price(position, candle)
            if risk_exit is not None:
                exit_price, reason = risk_exit
                equity, won = close_position(
                    trades=trades,
                    exits=exits,
                    position=position,
                    candle=candle,
                    exit_price=exit_price,
                    reason=reason,
                )
                wins += int(won)
                if reason.startswith("stop"):
                    exit_counts["stop_exits"] += 1
                else:
                    exit_counts["take_profit_exits"] += 1
                current_equity = equity
                position = None
                middle_exit_streak = 0
                cooldown_until = index + variant.cooldown_bars
        if position is not None:
            current_equity = mark_to_market(
                side=str(position["side"]),
                margin_used=float(position["margin_used"]),
                entry_price=float(position["entry_price"]),
                mark_price=candle.close,
                leverage=LEVERAGE,
            )
        peak_equity = max(peak_equity, current_equity)
        max_drawdown = max(max_drawdown, (peak_equity - current_equity) / peak_equity)
        equity_curve.append({"ts": candle.ts, "equity": current_equity, "close": candle.close})
        ending_equity = current_equity
        if index == len(eth) - 1 or equity <= 0.0:
            continue

        values = (middle[index], upper[index], lower[index], bandwidth[index], threshold[index], btc_sma[index], btc_momentum[index], eth_realized_vol[index])
        if any(value != value for value in values):
            continue
        if position is not None:
            if variant.exit_mode != "fixed_rr_only":
                middle_exit = (
                    position["side"] == "long" and candle.close < float(middle[index]) * (1.0 - variant.middle_exit_buffer_pct)
                ) or (
                    position["side"] == "short" and candle.close > float(middle[index]) * (1.0 + variant.middle_exit_buffer_pct)
                )
                middle_exit_streak = middle_exit_streak + 1 if middle_exit else 0
                if middle_exit_streak >= variant.middle_exit_confirm_bars:
                    pending_exit = True
            continue
        if index < cooldown_until:
            continue
        if variant.eth_vol_cap is not None and float(eth_realized_vol[index]) > variant.eth_vol_cap:
            continue
        if variant.dd_overlay is not None and (peak_equity - current_equity) / peak_equity > variant.dd_overlay:
            continue
        if variant.btc_filter == "btc-up" and not (btc_close.iloc[index] > float(btc_sma[index])):
            continue
        if variant.btc_filter == "btc-up-momo" and not (
            btc_close.iloc[index] > float(btc_sma[index]) and float(btc_momentum[index]) > 0.0
        ):
            continue

        if bandwidth[index] <= threshold[index]:
            if candle.close > float(upper[index]):
                pending_entry_side = "long"
            elif variant.side_mode == "both" and candle.close < float(lower[index]):
                pending_entry_side = "short"

    trade_count = len(trades)
    result = SegmentResult(
        trade_count=trade_count,
        total_return=(ending_equity - INITIAL_EQUITY) / INITIAL_EQUITY,
        win_rate=wins / trade_count if trade_count else 0.0,
        max_drawdown=max_drawdown,
        trades=trades,
        open_position=position,
        candles=eth[warmup_bars:],
        equity_curve=equity_curve,
        entries=entries,
        exits=exits,
    )
    return result, exit_counts


def build_variants() -> list[Variant]:
    bases = (
        (96, 960, 0.25, "both", "none", 0.006, None),
        (96, 960, 0.25, "both", "btc-up", 0.006, 0.25),
        (96, 960, 0.25, "both", "btc-up-momo", 0.006, 0.25),
        (48, 960, 0.25, "long", "btc-up", 0.006, 0.25),
        (48, 960, 0.25, "both", "none", 0.006, None),
        (96, 480, 0.15, "both", "none", 0.006, None),
    )
    variants: list[Variant] = []
    for length, bandwidth_lookback, quantile, side_mode, btc_filter, vol_cap, dd_overlay in bases:
        for stop_loss_pct in (0.006, 0.008, 0.01, 0.012):
            for reward_risk in (1.0, 1.5, 2.0, 2.5, 3.0):
                for exit_mode in ("fixed_rr_only", "hybrid_signal_rr"):
                    for middle_exit_buffer_pct, middle_exit_confirm_bars in ((0.0, 1), (0.001, 1), (0.001, 2)):
                        variants.append(
                            Variant(
                                band_length=length,
                                bandwidth_lookback=bandwidth_lookback,
                                bandwidth_quantile=quantile,
                                stop_loss_pct=stop_loss_pct,
                                reward_risk=reward_risk,
                                exit_mode=exit_mode,
                                side_mode=side_mode,
                                btc_filter=btc_filter,
                                eth_vol_cap=vol_cap,
                                dd_overlay=dd_overlay,
                                cooldown_bars=24,
                                middle_exit_buffer_pct=middle_exit_buffer_pct,
                                middle_exit_confirm_bars=middle_exit_confirm_bars,
                            )
                        )
    return variants


def format_cell(value: object) -> str:
    if isinstance(value, float):
        return f"{value:.6g}"
    return str(value).replace("|", "\\|")


def markdown_table(frame: pd.DataFrame) -> str:
    columns = list(frame.columns)
    rows = [columns, ["---" for _ in columns]]
    for record in frame.to_dict("records"):
        rows.append([record[column] for column in columns])
    return "\n".join("| " + " | ".join(format_cell(value) for value in row) + " |" for row in rows)


def write_report(*, summary: pd.DataFrame, horizon: pd.DataFrame, first_ts: int, last_ts: int, requested_years: float, command: str) -> str:
    primary = summary[summary["cost"] == PRIMARY_COST]
    top = primary.head(10)
    by_mode = primary.sort_values(["exit_mode", "net_calmar", "net_annualized_return"], ascending=[True, False, False]).groupby("exit_mode").head(5)
    horizon_top = (
        horizon[horizon["cost"] == PRIMARY_COST]
        .sort_values(["horizon", "net_calmar", "net_annualized_return"], ascending=[True, False, False])
        .groupby("horizon", observed=True)
        .head(3)
    )
    lines = [
        "# ETH BB squeeze fixed R:R exploration",
        "",
        f"Run command: `{command}`",
        f"Requested years: {requested_years:g}",
        f"Actual continuous local history: `{_format_ts(first_ts)}` to `{_format_ts(last_ts)}`.",
        "",
        "Exit modes:",
        "- `fixed_rr_only`: fixed stop-loss and take-profit only.",
        "- `hybrid_signal_rr`: fixed stop-loss/take-profit plus original middle-band signal exit.",
        "",
        "Top 10 by maker_taker Calmar:",
        markdown_table(
            top[
                [
                    "name",
                    "exit_mode",
                    "trades",
                    "stop_loss_pct",
                    "take_profit_pct",
                    "reward_risk",
                    "net_total_return",
                    "net_annualized_return",
                    "net_max_drawdown",
                    "net_calmar",
                    "worst_month_return",
                ]
            ]
        ),
        "",
        "Top by exit mode:",
        markdown_table(
            by_mode[
                [
                    "exit_mode",
                    "name",
                    "trades",
                    "net_annualized_return",
                    "net_max_drawdown",
                    "net_calmar",
                    "worst_month_return",
                ]
            ]
        ),
        "",
        "Recent horizon leaders:",
        markdown_table(
            horizon_top[
                [
                    "horizon",
                    "name",
                    "exit_mode",
                    "trades",
                    "net_total_return",
                    "net_annualized_return",
                    "net_max_drawdown",
                    "net_calmar",
                ]
            ]
        ),
    ]
    return "\n".join(lines) + "\n"


def main() -> int:
    parser = argparse.ArgumentParser()
    parser.add_argument("--bar", default=BAR)
    parser.add_argument("--years", type=float, default=YEARS)
    parser.add_argument("--output-dir", type=Path, default=OUTPUT_DIR)
    args = parser.parse_args()

    eth = load_candles_csv(DATA_DIR, ETH_SYMBOL, args.bar)
    btc = load_candles_csv(DATA_DIR, BTC_SYMBOL, args.bar)
    eth, btc = align_candles_by_ts(eth, btc)
    requested_bars = int(args.years * 365 * 24 * 60 / 15)
    eth = eth[-requested_bars:]
    btc = btc[-requested_bars:]

    summary_rows: list[dict[str, object]] = []
    horizon_rows_out: list[dict[str, object]] = []
    variants = build_variants()
    for index, variant in enumerate(variants, start=1):
        result, exit_counts = run_variant(eth, btc, variant)
        if not result.equity_curve:
            print(f"skip {index}/{len(variants)} {variant.name}")
            continue
        for cost_name, cost in COSTS:
            frame = cost_equity_frame(result, cost)
            metrics = equity_metrics(frame, eth[0].ts, eth[-1].ts)
            month, month_return = worst_month(frame)
            row = {
                "family": "bb_squeeze_fixed_rr",
                "cost": cost_name,
                "symbol": ETH_SYMBOL,
                "signal_symbol": BTC_SYMBOL if variant.btc_filter != "none" else "",
                "bar": args.bar,
                "name": variant.name,
                "band_length": variant.band_length,
                "bandwidth_lookback": variant.bandwidth_lookback,
                "bandwidth_quantile": variant.bandwidth_quantile,
                "stop_loss_pct": variant.stop_loss_pct,
                "take_profit_pct": variant.take_profit_pct,
                "reward_risk": variant.reward_risk,
                "exit_mode": variant.exit_mode,
                "side_mode": variant.side_mode,
                "btc_filter": variant.btc_filter,
                "eth_vol_cap": variant.eth_vol_cap,
                "dd_overlay": variant.dd_overlay,
                "cooldown_bars": variant.cooldown_bars,
                "middle_exit_buffer_pct": variant.middle_exit_buffer_pct,
                "middle_exit_confirm_bars": variant.middle_exit_confirm_bars,
                "first_candle": _format_ts(eth[0].ts),
                "last_candle": _format_ts(eth[-1].ts),
                "years": (eth[-1].ts - eth[0].ts) / 86_400_000 / 365,
                "trades": result.trade_count,
                "gross_total_return": result.total_return,
                "gross_max_drawdown_mark_to_market": result.max_drawdown,
                "worst_month": month,
                "worst_month_return": month_return,
                **exit_counts,
                **metrics,
            }
            summary_rows.append(row)
            for horizon_row in horizon_rows(frame, eth[-1].ts, HORIZONS):
                horizon_rows_out.append(
                    {
                        "family": "bb_squeeze_fixed_rr",
                        "cost": cost_name,
                        "symbol": ETH_SYMBOL,
                        "signal_symbol": BTC_SYMBOL if variant.btc_filter != "none" else "",
                        "bar": args.bar,
                        "name": variant.name,
                        "exit_mode": variant.exit_mode,
                        "trades": result.trade_count,
                        **horizon_row,
                    }
                )
        print(f"done {index}/{len(variants)} {variant.name}")

    summary = pd.DataFrame(summary_rows).sort_values(
        ["cost", "net_calmar", "worst_month_return", "net_annualized_return"],
        ascending=[True, False, False, False],
    )
    primary = summary[summary["cost"] == PRIMARY_COST]
    summary = pd.concat([primary, summary[summary["cost"] != PRIMARY_COST]], ignore_index=True)
    horizon = pd.DataFrame(horizon_rows_out)
    horizon["horizon"] = pd.Categorical(horizon["horizon"], categories=[label for label, _ in HORIZONS], ordered=True)
    horizon = horizon.sort_values(["cost", "horizon", "net_calmar", "net_annualized_return"], ascending=[True, True, False, False])

    args.output_dir.mkdir(parents=True, exist_ok=True)
    summary_path = args.output_dir / "eth-bb-squeeze-fixed-rr-summary.csv"
    horizon_path = args.output_dir / "eth-bb-squeeze-fixed-rr-horizon.csv"
    report_path = args.output_dir / "eth-bb-squeeze-fixed-rr-report.md"
    summary.to_csv(summary_path, index=False)
    horizon.to_csv(horizon_path, index=False)
    command = f"rtk .venv/bin/python {Path(__file__).as_posix()} --bar {args.bar} --years {args.years}"
    report_path.write_text(
        write_report(summary=summary, horizon=horizon, first_ts=eth[0].ts, last_ts=eth[-1].ts, requested_years=args.years, command=command),
        encoding="utf-8",
    )
    print(primary.head(10).to_string(index=False))
    return 0


if __name__ == "__main__":
    raise SystemExit(main())