okx-codex-trader/okx_codex_trader/bbmr_report.py

from __future__ import annotations

from dataclasses import dataclass
from pathlib import Path
from statistics import median

import pandas as pd

from okx_codex_trader.models import Candle
from okx_codex_trader.sampled_report import (
    SegmentResult,
    generate_sampled_report,
    mark_to_market as _mark_to_market,
    trade_equity as _trade_equity,
)

BBMR_STRATEGY_DESCRIPTION = (
    "Bollinger Band mean reversion, bandwidth filter against previous 50 completed values, "
    "close-based return-to-middle exits at next open, intrabar 0.5% stop-loss."
)


@dataclass(frozen=True)
class BBMRConfig:
    band_length: int = 20
    std_multiplier: float = 2.0
    bandwidth_lookback: int = 50
    stop_loss_pct: float = 0.005
    initial_equity: float = 10_000.0


def _format_ts(ts: int) -> str:
    return pd.to_datetime(ts, unit="ms", utc=True).strftime("%Y-%m-%d %H:%M")


def run_bbmr_segment(
    *,
    candles: list[Candle],
    leverage: int,
    warmup_bars: int,
    config: BBMRConfig = BBMRConfig(),
) -> SegmentResult:
    closes = pd.Series([candle.close for candle in candles], dtype=float)
    middle = closes.rolling(config.band_length).mean().tolist()
    stdev = closes.rolling(config.band_length).std(ddof=0).tolist()
    upper = [
        None if middle_value != middle_value or std_value != std_value else middle_value + config.std_multiplier * std_value
        for middle_value, std_value in zip(middle, stdev)
    ]
    lower = [
        None if middle_value != middle_value or std_value != std_value else middle_value - config.std_multiplier * std_value
        for middle_value, std_value in zip(middle, stdev)
    ]
    bandwidth = [
        None
        if upper_value is None or lower_value is None or middle_value in (None, 0)
        else (upper_value - lower_value) / middle_value
        for upper_value, lower_value, middle_value in zip(upper, lower, middle)
    ]

    equity = config.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

    for index in range(warmup_bars, len(candles)):
        candle = candles[index]

        if pending_exit and position is not None:
            exit_price = candle.open
            exit_equity = _trade_equity(
                side=str(position["side"]),
                margin_used=float(position["margin_used"]),
                entry_price=float(position["entry_price"]),
                exit_price=exit_price,
                leverage=leverage,
            )
            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(exit_equity - float(position["margin_used"]), 4),
                    "return_pct": round((exit_equity - float(position["margin_used"])) / float(position["margin_used"]) * 100, 4),
                }
            )
            exits.append({"ts": candle.ts, "price": exit_price, "side": position["side"]})
            if exit_equity > float(position["margin_used"]):
                wins += 1
            equity = exit_equity
            position = None
            pending_exit = False

        if pending_entry_side is not None and position is None:
            entry_price = candle.open
            margin_used = equity
            stop_multiplier = 1 - config.stop_loss_pct if pending_entry_side == "long" else 1 + config.stop_loss_pct
            position = {
                "side": pending_entry_side,
                "entry_time": candle.ts,
                "entry_price": entry_price,
                "entry_index": index,
                "margin_used": margin_used,
                "stop_price": entry_price * stop_multiplier,
            }
            entries.append({"ts": candle.ts, "price": entry_price, "side": pending_entry_side})
            pending_entry_side = None

        current_equity = equity
        if position is not None:
            stop_hit = (
                position["side"] == "long" and candle.low <= float(position["stop_price"])
            ) or (
                position["side"] == "short" and candle.high >= float(position["stop_price"])
            )
            if stop_hit:
                exit_price = float(position["stop_price"])
                exit_equity = _trade_equity(
                    side=str(position["side"]),
                    margin_used=float(position["margin_used"]),
                    entry_price=float(position["entry_price"]),
                    exit_price=exit_price,
                    leverage=leverage,
                )
                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(exit_equity - float(position["margin_used"]), 4),
                        "return_pct": round((exit_equity - float(position["margin_used"])) / float(position["margin_used"]) * 100, 4),
                    }
                )
                exits.append({"ts": candle.ts, "price": exit_price, "side": position["side"]})
                if exit_equity > float(position["margin_used"]):
                    wins += 1
                equity = exit_equity
                current_equity = exit_equity
                position = None
                if current_equity > peak_equity:
                    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
                continue

        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,
            )

        if current_equity > peak_equity:
            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(candles) - 1:
            continue

        if position is not None:
            exit_signal = (
                position["side"] == "long" and middle[index] is not None and candle.close >= float(middle[index])
            ) or (
                position["side"] == "short" and middle[index] is not None and candle.close <= float(middle[index])
            )
            if exit_signal:
                pending_exit = True
            continue

        previous_bandwidths = [value for value in bandwidth[max(0, index - config.bandwidth_lookback) : index] if value is not None]
        if len(previous_bandwidths) < config.bandwidth_lookback:
            continue
        current_bandwidth = bandwidth[index]
        if current_bandwidth is None or current_bandwidth > median(previous_bandwidths):
            continue
        if lower[index] is not None and candle.close < float(lower[index]):
            pending_entry_side = "long"
        elif upper[index] is not None and candle.close > float(upper[index]):
            pending_entry_side = "short"

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


def generate_bbmr_sampled_report(
    *,
    candles: list[Candle],
    leverage: int,
    output_file: Path,
    symbol: str,
    bar: str,
    segments: int,
    window_size: int,
) -> dict[str, object]:
    return generate_sampled_report(
        candles=candles,
        leverage=leverage,
        output_file=output_file,
        symbol=symbol,
        bar=bar,
        segments=segments,
        window_size=window_size,
        report_title="BBMR Sampled Report",
        strategy_label="BBMR",
        strategy_description=BBMR_STRATEGY_DESCRIPTION,
        strategy_params={
            "band_length": BBMRConfig().band_length,
            "std_multiplier": BBMRConfig().std_multiplier,
            "bandwidth_lookback": BBMRConfig().bandwidth_lookback,
            "stop_loss_pct": BBMRConfig().stop_loss_pct,
        },
        run_segment=run_bbmr_segment,
    )