316 lines
11 KiB
Python
316 lines
11 KiB
Python
"""
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盈利信号组合策略 — 只保留回测验证盈利的3种信号
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信号1: EMA交叉 (83笔, +1773) — 趋势变化捕捉
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信号2: 吞没形态 (1909笔, +2471) — K线反转形态
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信号3: BB反弹 (438笔, +171) — 均值回归
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去掉: 三分之一(-17290)、PinBar(-1936) — 亏损信号
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条件: 同一时间只持1个仓, 100U保证金, 100x杠杆, 90%返佣
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"""
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import sys, time, datetime, sqlite3
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from pathlib import Path
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from collections import defaultdict
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class EMA:
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__slots__ = ('k', 'v')
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def __init__(self, p):
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self.k = 2.0 / (p + 1); self.v = None
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def update(self, x):
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self.v = x if self.v is None else x * self.k + self.v * (1 - self.k)
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return self.v
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def load():
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db = Path(__file__).parent.parent / 'models' / 'database.db'
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s = int(datetime.datetime(2025,1,1).timestamp()) * 1000
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e = int(datetime.datetime(2026,1,1).timestamp()) * 1000
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conn = sqlite3.connect(str(db))
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rows = conn.cursor().execute(
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"SELECT id,open,high,low,close FROM bitmart_eth_1m WHERE id>=? AND id<? ORDER BY id", (s,e)
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).fetchall()
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conn.close()
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return [(datetime.datetime.fromtimestamp(r[0]/1000.0), r[1], r[2], r[3], r[4]) for r in rows]
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def calc_bb(closes, period=20, nstd=2.0):
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if len(closes) < period: return None, None, None
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rec = closes[-period:]
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mid = sum(rec) / period
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var = sum((x - mid)**2 for x in rec) / period
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std = var ** 0.5
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return mid + nstd * std, mid, mid - nstd * std
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def calc_rsi(closes, period=14):
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if len(closes) < period + 1: return None
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g = 0; l = 0
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for i in range(-period, 0):
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d = closes[i] - closes[i-1]
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if d > 0: g += d
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else: l -= d
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if l == 0: return 100.0
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return 100 - 100 / (1 + (g/period)/(l/period))
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def run_combo(data, notional, engulf_body_min, engulf_ratio, engulf_sl, engulf_tp,
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bb_rsi_long, bb_rsi_short, bb_sl, bb_tp, bb_atr_min,
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ema_atr_min, ema_sl):
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N = len(data)
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FEE = notional * 0.0006 * 2
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REB = FEE * 0.9
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NFEE = FEE - REB
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MIN_HOLD = 200; MAX_HOLD = 1800
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ema_f = EMA(8); ema_s = EMA(21); ema_b = EMA(120)
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pf_ = None; ps_ = None
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CB = []; HB = []; LB = []
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pos = 0; op = 0.0; ot = None; st = ""; sl = 0; tp = 0
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trades = []
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def close_(price, dt_, reason):
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nonlocal pos, op, ot, st
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pp = (price-op)/op if pos==1 else (op-price)/op
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trades.append((st, 'L' if pos==1 else 'S', op, price, notional*pp,
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(dt_-ot).total_seconds(), reason, ot, dt_))
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pos=0; op=0; ot=None; st=""
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for i in range(N):
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dt, o_, h_, l_, c_ = data[i]
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p = c_
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CB.append(p); HB.append(h_); LB.append(l_)
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if len(CB) > 300: CB=CB[-300:]; HB=HB[-300:]; LB=LB[-300:]
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fast = ema_f.update(p); slow = ema_s.update(p); big = ema_b.update(p)
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atr = 0.0
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if len(HB) > 15:
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s=0
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for j in range(-14, 0):
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tr=HB[j]-LB[j]; d1=abs(HB[j]-CB[j-1]); d2=abs(LB[j]-CB[j-1])
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if d1>tr: tr=d1
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if d2>tr: tr=d2
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s+=tr
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atr = s/(14*p) if p>0 else 0
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cu = pf_ is not None and pf_<=ps_ and fast>slow
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cd = pf_ is not None and pf_>=ps_ and fast<slow
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pf_=fast; ps_=slow
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bb_u, bb_m, bb_l = calc_bb(CB, 20, 2.0)
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rsi = calc_rsi(CB, 14)
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# 持仓管理
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if pos!=0 and ot:
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pp=(p-op)/op if pos==1 else (op-p)/op
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hsec=(dt-ot).total_seconds()
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hsl = max(sl*1.5, 0.006)
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if -pp>=hsl: close_(p, dt, "硬止损"); continue
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if hsec>=MIN_HOLD:
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if -pp>=sl: close_(p, dt, "止损"); continue
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if tp>0 and pp>=tp: close_(p, dt, "止盈"); continue
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if hsec>=MAX_HOLD: close_(p, dt, "超时"); continue
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if st=="EMA":
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if pos==1 and cd: close_(p, dt, "EMA反转"); continue
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if pos==-1 and cu: close_(p, dt, "EMA反转"); continue
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if st=="BB" and bb_m:
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if pos==1 and p>=bb_m: close_(p, dt, "BB回中轨"); continue
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if pos==-1 and p<=bb_m: close_(p, dt, "BB回中轨"); continue
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# 开仓
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if pos==0 and i>20:
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sig=None; s_sl=0; s_tp=0; s_type=""
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# 信号1: EMA
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if atr>=ema_atr_min:
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if cu and p>big: sig='L'; s_type="EMA"; s_sl=ema_sl; s_tp=0
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elif cd and p<big: sig='S'; s_type="EMA"; s_sl=ema_sl; s_tp=0
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# 信号2: 吞没
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if sig is None and i>0:
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pb_o,pb_c = data[i-1][1], data[i-1][4]
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cb_o,cb_c = o_, c_
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pb_body = abs(pb_c-pb_o)
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cb_body = abs(cb_c-cb_o)
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cb_pct = cb_body/p if p>0 else 0
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if cb_pct>=engulf_body_min and cb_body>pb_body*engulf_ratio:
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if pb_c<pb_o and cb_c>cb_o and cb_c>pb_o and cb_o<=pb_c:
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if p>big and atr>=0.001:
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sig='L'; s_type="吞没"; s_sl=engulf_sl; s_tp=engulf_tp
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elif pb_c>pb_o and cb_c<cb_o and cb_c<pb_o and cb_o>=pb_c:
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if p<big and atr>=0.001:
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sig='S'; s_type="吞没"; s_sl=engulf_sl; s_tp=engulf_tp
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# 信号3: BB
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if sig is None and bb_u and rsi is not None:
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if p<=bb_l and rsi<bb_rsi_long and p>big and atr>=bb_atr_min:
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sig='L'; s_type="BB"; s_sl=bb_sl; s_tp=bb_tp
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elif p>=bb_u and rsi>bb_rsi_short and p<big and atr>=bb_atr_min:
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sig='S'; s_type="BB"; s_sl=bb_sl; s_tp=bb_tp
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if sig:
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pos=1 if sig=='L' else -1; op=p; ot=dt; st=s_type; sl=s_sl; tp=s_tp
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if pos!=0: close_(data[-1][4], data[-1][0], "结束")
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return trades
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def analyze_print(trades, notional, label=""):
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if not trades:
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print(f" [{label}] No trades", flush=True); return 0
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n = len(trades)
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FEE = notional * 0.0006 * 2
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REB = FEE * 0.9
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NFEE = FEE - REB
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total_pnl = sum(t[4] for t in trades)
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net = total_pnl - NFEE * n
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total_reb = REB * n
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wins = len([t for t in trades if t[4]>0])
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wr = wins/n*100
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by_type = defaultdict(lambda: {'n':0,'pnl':0,'w':0})
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for t in trades:
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by_type[t[0]]['n']+=1; by_type[t[0]]['pnl']+=t[4]
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if t[4]>0: by_type[t[0]]['w']+=1
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monthly = defaultdict(lambda: {'n':0,'net':0,'w':0})
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for t in trades:
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k = t[8].strftime('%Y-%m')
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monthly[k]['n']+=1
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monthly[k]['net']+=t[4]-NFEE
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if t[4]>0: monthly[k]['w']+=1
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cum=0; peak=0; dd=0
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for t in trades:
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cum+=t[4]-NFEE
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if cum>peak: peak=cum
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if peak-cum>dd: dd=peak-cum
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# 月度盈利月数
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profit_months = len([m for m in monthly.values() if m['net']>0])
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min_month = min(monthly.values(), key=lambda x: x['net'])
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max_month = max(monthly.values(), key=lambda x: x['net'])
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print(f"\n{'='*75}", flush=True)
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print(f" {label}", flush=True)
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print(f"{'='*75}", flush=True)
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print(f" 年净利: {net:>+10.2f} | 月均: {net/12:>+8.2f} | 交易: {n}笔 | 胜率: {wr:.1f}%", flush=True)
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print(f" 返佣: {total_reb:>.0f} | 最大回撤: {dd:>.0f} | 盈利月: {profit_months}/12", flush=True)
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print(f"\n 信号拆分:", flush=True)
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for st in sorted(by_type.keys()):
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d=by_type[st]
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nt=d['pnl']-NFEE*d['n']
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wt=d['w']/d['n']*100 if d['n']>0 else 0
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print(f" {st:<8} {d['n']:>5}笔 净利{nt:>+8.0f} 胜率{wt:.0f}%", flush=True)
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print(f"\n 月度:", flush=True)
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print(f" {'月份':<8} {'笔':>4} {'净利':>9} {'胜率':>6}", flush=True)
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print(f" {'-'*30}", flush=True)
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for m in sorted(monthly.keys()):
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d=monthly[m]
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wr_m=d['w']/d['n']*100 if d['n']>0 else 0
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mark=" <<" if d['net']<0 else ""
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print(f" {m:<8} {d['n']:>4} {d['net']:>+9.0f} {wr_m:>5.1f}%{mark}", flush=True)
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print(f" {'-'*30}", flush=True)
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print(f" {'合计':<8} {n:>4} {net:>+9.0f}", flush=True)
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print(f"{'='*75}", flush=True)
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return net
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def main():
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print("Loading...", flush=True)
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data = load()
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print(f"{len(data)} bars\n", flush=True)
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# === 测试多种参数组合 ===
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configs = [
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# (label, notional, engulf_body_min, engulf_ratio, engulf_sl, engulf_tp,
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# bb_rsi_long, bb_rsi_short, bb_sl, bb_tp, bb_atr_min, ema_atr_min, ema_sl)
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# 基线：上一轮参数
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("v1: 基线", 10000,
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0.001, 1.5, 0.004, 0.005,
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30, 70, 0.003, 0.002, 0.0008,
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0.003, 0.004),
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# v2: 更严格的吞没（减少低质量交易）
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("v2: 严格吞没", 10000,
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0.0015, 2.0, 0.004, 0.006,
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30, 70, 0.003, 0.002, 0.0008,
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0.003, 0.004),
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# v3: 更严格吞没 + 更宽BB RSI
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("v3: 严格吞没+宽BB", 10000,
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0.0015, 2.0, 0.004, 0.006,
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25, 75, 0.003, 0.003, 0.001,
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0.003, 0.004),
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# v4: 最严格吞没 + 最严BB
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("v4: 超严格", 10000,
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0.002, 2.5, 0.005, 0.008,
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20, 80, 0.004, 0.003, 0.001,
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0.003, 0.004),
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# v5: 中等吞没 + 更大止盈
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("v5: 大止盈", 10000,
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0.0012, 1.8, 0.005, 0.008,
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28, 72, 0.004, 0.003, 0.001,
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0.003, 0.004),
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# v6: 去掉BB（只用EMA+吞没）
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("v6: 仅EMA+吞没", 10000,
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0.0015, 2.0, 0.004, 0.006,
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999, -999, 0.003, 0.002, 999, # BB不会触发
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0.003, 0.004),
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# v7: 放宽EMA的ATR
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("v7: EMA ATR>0.2%", 10000,
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0.0015, 2.0, 0.004, 0.006,
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25, 75, 0.003, 0.003, 0.001,
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0.002, 0.004),
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# v8: v3的最优 x 300U仓位
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("v8: v3 x 300U仓位", 30000,
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0.0015, 2.0, 0.004, 0.006,
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25, 75, 0.003, 0.003, 0.001,
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0.003, 0.004),
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# v9: v3 x 500U
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("v9: v3 x 500U仓位", 50000,
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0.0015, 2.0, 0.004, 0.006,
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25, 75, 0.003, 0.003, 0.001,
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0.003, 0.004),
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# v10: v4 x 500U
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("v10: v4 x 500U", 50000,
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0.002, 2.5, 0.005, 0.008,
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20, 80, 0.004, 0.003, 0.001,
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0.003, 0.004),
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]
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best_net = -99999; best_label = ""
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summary = []
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for cfg in configs:
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label = cfg[0]
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trades = run_combo(data, *cfg[1:])
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net = analyze_print(trades, cfg[1], label)
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summary.append((label, cfg[1], len(trades), net))
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if net > best_net:
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best_net = net; best_label = label
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# 总览
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print(f"\n\n{'='*80}", flush=True)
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print(f" SUMMARY — 目标: 月均 1000 USDT", flush=True)
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print(f"{'='*80}", flush=True)
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print(f" {'方案':<25} {'名义值':>10} {'交易数':>6} {'年净利':>10} {'月均':>8} {'达标':>4}", flush=True)
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print(f" {'-'*72}", flush=True)
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for label, notional, n, net in summary:
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mavg = net/12
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ok = "Yes" if mavg>=1000 else "No"
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print(f" {label:<25} {notional:>10,.0f} {n:>6} {net:>+10.0f} {mavg:>+8.0f} {ok:>4}", flush=True)
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print(f" {'-'*72}", flush=True)
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print(f" Best: {best_label} → {best_net:+.0f}/年 = {best_net/12:+.0f}/月", flush=True)
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print(f"{'='*80}", flush=True)
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if __name__=='__main__':
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main()
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