dekun
234 lines
8.0 KiB
Python
234 lines
8.0 KiB
Python
# Copyright (c) 2025-2026 马建军. All rights reserved.
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# 专有软件 — 未经授权禁止复制、传播、转售。
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# 严禁用于：带单/代客理财、向他人推荐期货品种或买卖建议、融资配资等业务。
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# 详见 LICENSE.zh-CN.txt 与 docs/软件购买与使用协议.md
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"""趋势回调：纯计算（期货整数手）。"""
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from __future__ import annotations
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import json
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import math
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from typing import Any, Optional, Tuple
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from contract_specs import get_contract_spec
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def validate_trend_bounds(direction: str, stop_loss: float, add_upper: float) -> Optional[str]:
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direction = (direction or "long").strip().lower()
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if direction == "long":
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if not (float(stop_loss) < float(add_upper)):
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return "做多：止损须低于补仓上沿"
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else:
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if not (float(stop_loss) > float(add_upper)):
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return "做空：止损须高于补仓下沿"
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return None
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def build_grid_prices(direction: str, sl: float, upper: float, n_legs: int) -> list[float]:
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sl, upper = float(sl), float(upper)
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out: list[float] = []
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if n_legs <= 0:
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return out
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direction = (direction or "long").strip().lower()
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if direction == "long":
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if upper <= sl:
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return out
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span = upper - sl
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for i in range(1, n_legs + 1):
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out.append(sl + (i / float(n_legs + 1)) * span)
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out.sort(reverse=True)
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else:
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if sl <= upper:
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return out
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span = sl - upper
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for i in range(1, n_legs + 1):
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out.append(upper + (i / float(n_legs + 1)) * span)
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out.sort()
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return [round(p, 4) for p in out]
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def compute_trend_plan_futures(
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*,
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direction: str,
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stop_loss: float,
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add_upper: float,
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take_profit: float,
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risk_percent: float,
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capital: float,
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live_price: float,
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ths_code: str,
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dca_legs: int = 5,
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) -> Tuple[Optional[dict[str, Any]], Optional[str]]:
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err = validate_trend_bounds(direction, stop_loss, add_upper)
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if err:
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return None, err
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spec = get_contract_spec(ths_code)
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mult = spec["mult"]
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d = (direction or "long").strip().lower()
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if d == "short":
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worst_per_lot = (float(stop_loss) - float(add_upper)) * mult
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else:
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worst_per_lot = (float(add_upper) - float(stop_loss)) * mult
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if worst_per_lot <= 0:
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return None, "止损与补仓边界无法计算风险"
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budget = float(capital) * float(risk_percent) / 100.0
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total_lots = int(math.floor(budget / worst_per_lot))
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if total_lots < 3:
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return None, f"按 {risk_percent}% 风险，总手数至少需 3 手才能拆分首仓+补仓（当前 {total_lots} 手）"
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first_lots = total_lots // 2
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remainder = total_lots - first_lots
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legs = max(1, min(int(dca_legs), remainder))
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per_leg = remainder // legs
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leg_amounts = [per_leg] * (legs - 1) + [remainder - per_leg * (legs - 1)]
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if any(x < 1 for x in leg_amounts):
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legs = 1
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leg_amounts = [remainder]
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grid = build_grid_prices(d, stop_loss, add_upper, len(leg_amounts))
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margin_rate = spec["margin_rate"]
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plan_margin = float(live_price) * mult * total_lots * margin_rate
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return {
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"direction": d,
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"stop_loss": float(stop_loss),
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"add_upper": float(add_upper),
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"take_profit": float(take_profit),
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"risk_percent": float(risk_percent),
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"capital_snapshot": float(capital),
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"live_price_ref": float(live_price),
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"target_lots": total_lots,
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"first_lots": first_lots,
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"remainder_lots": remainder,
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"dca_legs": len(leg_amounts),
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"leg_amounts": leg_amounts,
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"leg_amounts_json": json.dumps(leg_amounts),
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"grid_prices_json": json.dumps(grid),
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"grid": grid,
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"plan_margin": round(plan_margin, 2),
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"mult": mult,
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}, None
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def trend_dca_level_reached(direction: str, mark_price: float, level: float) -> bool:
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d = (direction or "long").strip().lower()
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pf, lv = float(mark_price), float(level)
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return pf <= lv if d == "long" else pf >= lv
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def trend_strategy_periods() -> list[dict[str, str]]:
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"""策略页可选 K 线周期。"""
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from kline_chart import MARKET_PERIODS
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skip = frozenset({"timeshare", "w"})
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return [p for p in MARKET_PERIODS if p["key"] not in skip]
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def trend_period_label(key: str) -> str:
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k = (key or "").strip()
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for p in trend_strategy_periods():
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if p["key"] == k:
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return p["label"]
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return k or "15分"
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def normalize_trend_period(key: str) -> str:
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valid = {p["key"] for p in trend_strategy_periods()}
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k = (key or "15m").strip()
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return k if k in valid else "15m"
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def _avg_after_entries(entries: list[tuple[float, int]]) -> float:
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total = sum(q for _, q in entries)
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if total <= 0:
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return 0.0
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return sum(p * q for p, q in entries) / total
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def enrich_trend_plan_preview(
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plan: dict,
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*,
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symbol: str,
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symbol_name: str = "",
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period: str = "15m",
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) -> dict[str, Any]:
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"""补全预览：周期、风险金额、分档表格（对齐币圈预览样式）。"""
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out = dict(plan)
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d = (out.get("direction") or "long").strip().lower()
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sl = float(out["stop_loss"])
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tp = float(out["take_profit"])
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mult = float(out.get("mult") or 1)
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entry0 = float(out["live_price_ref"])
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first_lots = int(out["first_lots"])
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leg_amounts = [int(x) for x in (out.get("leg_amounts") or [])]
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grid = [float(x) for x in (out.get("grid") or [])]
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capital = float(out.get("capital_snapshot") or 0)
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risk_pct = float(out.get("risk_percent") or 0)
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budget = capital * risk_pct / 100.0
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remainder = int(out.get("remainder_lots") or sum(leg_amounts))
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out["symbol"] = symbol
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out["symbol_name"] = symbol_name or symbol
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out["period"] = normalize_trend_period(period)
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out["period_label"] = trend_period_label(out["period"])
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out["stop_loss_budget"] = round(budget, 2)
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out["direction_label"] = "做多" if d == "long" else "做空"
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entries: list[tuple[float, int]] = [(entry0, first_lots)]
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rows: list[dict[str, Any]] = []
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def leg_metrics() -> tuple[float, float, float, Optional[float]]:
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total = sum(q for _, q in entries)
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avg = _avg_after_entries(entries)
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if d == "long":
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profit = (tp - avg) * total * mult
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loss = (avg - sl) * total * mult
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else:
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profit = (avg - tp) * total * mult
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loss = (sl - avg) * total * mult
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rr = profit / loss if loss > 0 else None
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return (
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round(avg, 4),
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round(profit, 2),
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round(loss, 2),
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round(rr, 2) if rr is not None else None,
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)
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avg, profit, loss, rr = leg_metrics()
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rows.append({
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"level": "首仓",
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"price": round(entry0, 4),
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"lots": first_lots,
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"avg_after": avg,
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"profit_at_tp": profit,
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"loss_at_sl": loss,
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"rr_ratio": rr,
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})
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out["first_rr_ratio"] = rr
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for i, lots in enumerate(leg_amounts):
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price = grid[i] if i < len(grid) else sl
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entries.append((float(price), int(lots)))
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avg, profit, loss, rr = leg_metrics()
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rows.append({
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"level": f"补仓{i + 1}",
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"price": round(float(price), 4),
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"lots": int(lots),
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"avg_after": avg,
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"profit_at_tp": profit,
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"loss_at_sl": loss,
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"rr_ratio": rr,
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})
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out["preview_rows"] = rows
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out["summary_line"] = (
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f"{out['symbol_name']} {out['symbol']} {out['direction_label']} {out['period_label']}"
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f" | 权益 {capital:.2f} 元"
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f" | 参考价 {entry0}"
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f" | 计划保证金 ≈ {out.get('plan_margin')} 元"
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f" | 总手 {out.get('target_lots')}（首仓 {first_lots} + 补仓 {remainder}）"
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)
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out["detail_line"] = (
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f"止损价 {sl} | 止损金额 {out['stop_loss_budget']} 元（权益 × 风险 {risk_pct}%）"
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f" | 补仓边界 {float(out['add_upper'])} | 止盈价 {tp}"
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f" | 首仓盈亏比 {out['first_rr_ratio'] if out['first_rr_ratio'] is not None else '—'}"
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)
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return out
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