339 lines
13 KiB
Python
339 lines
13 KiB
Python
"""
|
||
终极组合策略回测 — 多时间框架 + 波动率自适应
|
||
|
||
核心改进:
|
||
1. 吞没形态用5分钟K线（减少噪音，提高质量）
|
||
2. 加入突破策略（N根K线新高新低突破）
|
||
3. 波动率自适应：高波动用趋势跟踪，低波动用均值回归
|
||
4. 动态止盈：使用ATR倍数作为止盈目标而非固定比例
|
||
5. 趋势强度过滤：EMA斜率+ADX概念
|
||
|
||
信号:
|
||
A) EMA(8/21) 金叉死叉 + ATR>0.3% + EMA(120)趋势方向
|
||
B) 5分钟吞没形态 + EMA趋势方向 + ATR确认
|
||
C) 20根K线高低突破 + 趋势方向
|
||
D) BB反弹 + RSI极值 + 趋势方向（仅逆趋势小单）
|
||
|
||
条件: 同时只持1个仓, 90%返佣, >3分钟持仓
|
||
"""
|
||
import sys, time, datetime, sqlite3
|
||
from pathlib import Path
|
||
from collections import defaultdict
|
||
|
||
class EMA:
|
||
__slots__ = ('k', 'v')
|
||
def __init__(self, p):
|
||
self.k = 2.0 / (p + 1); self.v = None
|
||
def update(self, x):
|
||
self.v = x if self.v is None else x * self.k + self.v * (1 - self.k)
|
||
return self.v
|
||
|
||
def load():
|
||
db = Path(__file__).parent.parent / 'models' / 'database.db'
|
||
s = int(datetime.datetime(2025,1,1).timestamp()) * 1000
|
||
e = int(datetime.datetime(2026,1,1).timestamp()) * 1000
|
||
conn = sqlite3.connect(str(db))
|
||
rows = conn.cursor().execute(
|
||
"SELECT id,open,high,low,close FROM bitmart_eth_1m WHERE id>=? AND id<? ORDER BY id", (s,e)
|
||
).fetchall()
|
||
conn.close()
|
||
return [(datetime.datetime.fromtimestamp(r[0]/1000.0), r[1], r[2], r[3], r[4]) for r in rows]
|
||
|
||
def run(data, notional):
|
||
N = len(data)
|
||
FEE = notional * 0.0006 * 2
|
||
REB = FEE * 0.9
|
||
NFEE = FEE - REB
|
||
MIN_HOLD = 200; MAX_HOLD = 1800
|
||
|
||
# EMA
|
||
ef = EMA(8); es = EMA(21); eb = EMA(120); e50 = EMA(50)
|
||
pf_ = None; ps_ = None
|
||
CB = []; HB = []; LB = []
|
||
|
||
# 5分钟聚合
|
||
b5_o=None; b5_h=None; b5_l=None; b5_c=None; b5_cnt=0
|
||
bars5 = []
|
||
|
||
# 突破追踪
|
||
high_20 = []; low_20 = []
|
||
|
||
pos=0; op=0.0; ot=None; st=""; sl=0; tp_atr=0
|
||
trades = []
|
||
|
||
def close_(price, dt_, reason):
|
||
nonlocal pos, op, ot, st
|
||
pp = (price-op)/op if pos==1 else (op-price)/op
|
||
trades.append((st, 'L' if pos==1 else 'S', op, price, notional*pp,
|
||
(dt_-ot).total_seconds(), reason, ot, dt_))
|
||
pos=0; op=0; ot=None; st=""
|
||
|
||
for i in range(N):
|
||
dt, o_, h_, l_, c_ = data[i]
|
||
p = c_
|
||
CB.append(p); HB.append(h_); LB.append(l_)
|
||
if len(CB)>300: CB=CB[-300:]; HB=HB[-300:]; LB=LB[-300:]
|
||
|
||
fast=ef.update(p); slow=es.update(p); big=eb.update(p); mid50=e50.update(p)
|
||
|
||
# ATR
|
||
atr=0.0; atr_val=0.0
|
||
if len(HB)>15:
|
||
s=0
|
||
for j in range(-14,0):
|
||
tr=HB[j]-LB[j]; d1=abs(HB[j]-CB[j-1]); d2=abs(LB[j]-CB[j-1])
|
||
if d1>tr: tr=d1
|
||
if d2>tr: tr=d2
|
||
s+=tr
|
||
atr_val = s/14
|
||
atr = atr_val/p if p>0 else 0
|
||
|
||
# EMA交叉
|
||
cu = pf_ is not None and pf_<=ps_ and fast>slow
|
||
cd = pf_ is not None and pf_>=ps_ and fast<slow
|
||
pf_=fast; ps_=slow
|
||
|
||
# EMA趋势强度（斜率）
|
||
trend_up = fast > slow and slow > big # 三线多头
|
||
trend_dn = fast < slow and slow < big # 三线空头
|
||
|
||
# BB & RSI
|
||
bb_u=None; bb_m=None; bb_l=None; rsi=None
|
||
if len(CB)>=20:
|
||
rec=CB[-20:]; mid=sum(rec)/20
|
||
var=sum((x-mid)**2 for x in rec)/20; std=var**0.5
|
||
bb_u=mid+2*std; bb_m=mid; bb_l=mid-2*std
|
||
if len(CB)>=15:
|
||
g=0; l=0
|
||
for j in range(-14,0):
|
||
d=CB[j]-CB[j-1]
|
||
if d>0: g+=d
|
||
else: l-=d
|
||
rsi = 100-100/(1+(g/14)/(l/14)) if l>0 else 100
|
||
|
||
# 5分钟聚合
|
||
if b5_o is None:
|
||
b5_o=o_; b5_h=h_; b5_l=l_; b5_c=c_; b5_cnt=1
|
||
else:
|
||
b5_h=max(b5_h,h_); b5_l=min(b5_l,l_); b5_c=c_; b5_cnt+=1
|
||
new_b5 = False
|
||
if b5_cnt>=5:
|
||
bars5.append({'o':b5_o,'h':b5_h,'l':b5_l,'c':b5_c})
|
||
if len(bars5)>30: bars5=bars5[-30:]
|
||
b5_o=None; b5_cnt=0; new_b5=True
|
||
|
||
# 20根K线高低（用于突破）
|
||
high_20.append(h_); low_20.append(l_)
|
||
if len(high_20)>21: high_20=high_20[-21:]; low_20=low_20[-21:]
|
||
breakout_high = max(high_20[:-1]) if len(high_20)>1 else None
|
||
breakout_low = min(low_20[:-1]) if len(low_20)>1 else None
|
||
|
||
# ===== 持仓管理 =====
|
||
if pos!=0 and ot:
|
||
pp=(p-op)/op if pos==1 else (op-p)/op
|
||
hsec=(dt-ot).total_seconds()
|
||
|
||
# 动态止损/止盈（基于ATR）
|
||
hard_sl = max(sl*1.5, 0.006)
|
||
if -pp>=hard_sl: close_(p,dt,"硬止损"); continue
|
||
|
||
if hsec>=MIN_HOLD:
|
||
if -pp>=sl: close_(p,dt,"止损"); continue
|
||
|
||
# 动态止盈：盈利超过 tp_atr 倍ATR值
|
||
if tp_atr>0 and atr_val>0:
|
||
tp_target = tp_atr * atr_val / op # 转为百分比
|
||
if pp>=tp_target: close_(p,dt,f"ATR止盈({pp*100:.2f}%)"); continue
|
||
|
||
if hsec>=MAX_HOLD: close_(p,dt,"超时"); continue
|
||
|
||
# 趋势跟踪出场
|
||
if st in ("EMA","突破"):
|
||
if pos==1 and cd: close_(p,dt,"反向交叉"); continue
|
||
if pos==-1 and cu: close_(p,dt,"反向交叉"); continue
|
||
# 价格跌破慢线止盈
|
||
if pos==1 and p<slow and pp>0.001: close_(p,dt,"破慢线止盈"); continue
|
||
if pos==-1 and p>slow and pp>0.001: close_(p,dt,"破慢线止盈"); continue
|
||
|
||
if st=="BB" and bb_m:
|
||
if pos==1 and p>=bb_m: close_(p,dt,"BB回中轨"); continue
|
||
if pos==-1 and p<=bb_m: close_(p,dt,"BB回中轨"); continue
|
||
|
||
if st=="5m吞没":
|
||
if pos==1 and cd: close_(p,dt,"反向交叉"); continue
|
||
if pos==-1 and cu: close_(p,dt,"反向交叉"); continue
|
||
|
||
# ===== 开仓 =====
|
||
if pos==0 and i>120:
|
||
sig=None; s_sl=0; s_tp_atr=0; s_type=""
|
||
|
||
# 信号A: EMA交叉（最高质量）
|
||
if atr>=0.003:
|
||
if cu and p>big:
|
||
sig='L'; s_type="EMA"; s_sl=0.004; s_tp_atr=3.0
|
||
elif cd and p<big:
|
||
sig='S'; s_type="EMA"; s_sl=0.004; s_tp_atr=3.0
|
||
|
||
# 信号B: 5分钟吞没（仅在新5分钟K线完成时检查）
|
||
if sig is None and new_b5 and len(bars5)>=3:
|
||
prev5 = bars5[-2]; cur5 = bars5[-1]
|
||
pb = abs(prev5['c']-prev5['o'])
|
||
cb = abs(cur5['c']-cur5['o'])
|
||
cb_pct = cb/p if p>0 else 0
|
||
|
||
if cb_pct>=0.0015 and cb>pb*1.5 and atr>=0.0015:
|
||
# 看涨吞没
|
||
if prev5['c']<prev5['o'] and cur5['c']>cur5['o']:
|
||
if cur5['c']>prev5['o'] and cur5['o']<=prev5['c']:
|
||
if p>big:
|
||
sig='L'; s_type="5m吞没"; s_sl=0.005; s_tp_atr=2.5
|
||
# 看跌吞没
|
||
elif prev5['c']>prev5['o'] and cur5['c']<cur5['o']:
|
||
if cur5['c']<prev5['o'] and cur5['o']>=prev5['c']:
|
||
if p<big:
|
||
sig='S'; s_type="5m吞没"; s_sl=0.005; s_tp_atr=2.5
|
||
|
||
# 信号C: 突破（20根K线新高新低）
|
||
if sig is None and breakout_high and atr>=0.002:
|
||
if h_>breakout_high and trend_up:
|
||
sig='L'; s_type="突破"; s_sl=0.005; s_tp_atr=2.5
|
||
elif l_<breakout_low and trend_dn:
|
||
sig='S'; s_type="突破"; s_sl=0.005; s_tp_atr=2.5
|
||
|
||
# 信号D: BB反弹（要求RSI极值 + ATR适中）
|
||
if sig is None and bb_u and rsi is not None and 0.001<=atr<=0.004:
|
||
if p<=bb_l and rsi<25 and p>big:
|
||
sig='L'; s_type="BB"; s_sl=0.003; s_tp_atr=0
|
||
elif p>=bb_u and rsi>75 and p<big:
|
||
sig='S'; s_type="BB"; s_sl=0.003; s_tp_atr=0
|
||
|
||
if sig:
|
||
pos=1 if sig=='L' else -1; op=p; ot=dt
|
||
st=s_type; sl=s_sl; tp_atr=s_tp_atr
|
||
|
||
if pos!=0: close_(data[-1][4], data[-1][0], "结束")
|
||
return trades
|
||
|
||
def report(trades, notional, label):
|
||
if not trades: print(f" [{label}] No trades"); return 0,{}
|
||
n=len(trades)
|
||
FEE=notional*0.0006*2; REB=FEE*0.9; NFEE=FEE-REB
|
||
total_pnl=sum(t[4] for t in trades)
|
||
net=total_pnl-NFEE*n; total_reb=REB*n
|
||
wins=len([t for t in trades if t[4]>0]); wr=wins/n*100
|
||
|
||
by_type=defaultdict(lambda:{'n':0,'pnl':0,'w':0})
|
||
for t in trades:
|
||
by_type[t[0]]['n']+=1; by_type[t[0]]['pnl']+=t[4]
|
||
if t[4]>0: by_type[t[0]]['w']+=1
|
||
|
||
monthly=defaultdict(lambda:{'n':0,'net':0,'w':0})
|
||
for t in trades:
|
||
k=t[8].strftime('%Y-%m')
|
||
monthly[k]['n']+=1; monthly[k]['net']+=t[4]-NFEE
|
||
if t[4]>0: monthly[k]['w']+=1
|
||
|
||
cum=0;peak=0;dd=0
|
||
for t in trades:
|
||
cum+=t[4]-NFEE
|
||
if cum>peak:peak=cum
|
||
if peak-cum>dd:dd=peak-cum
|
||
|
||
pm=len([m for m in monthly.values() if m['net']>0])
|
||
min_m=min(monthly.values(),key=lambda x:x['net'])['net']
|
||
max_m=max(monthly.values(),key=lambda x:x['net'])['net']
|
||
|
||
print(f"\n{'='*75}", flush=True)
|
||
print(f" {label} | 名义值={notional:,.0f}U", flush=True)
|
||
print(f"{'='*75}", flush=True)
|
||
print(f" 年净利: {net:>+10.0f} | 月均: {net/12:>+8.0f} | 交易: {n}笔 | 胜率: {wr:.1f}%", flush=True)
|
||
print(f" 返佣: {total_reb:>.0f} | 回撤: {dd:>.0f} | 盈利月: {pm}/12", flush=True)
|
||
print(f" 最佳月: {max_m:>+.0f} | 最差月: {min_m:>+.0f}", flush=True)
|
||
|
||
print(f"\n 信号:", flush=True)
|
||
for st in sorted(by_type.keys()):
|
||
d=by_type[st]; nt=d['pnl']-NFEE*d['n']
|
||
wt=d['w']/d['n']*100 if d['n']>0 else 0
|
||
avg=nt/d['n'] if d['n']>0 else 0
|
||
mk="+" if nt>0 else "-"
|
||
print(f" {st:<8} {d['n']:>5}笔 净{nt:>+8.0f} 胜{wt:.0f}% 均{avg:>+.1f}/笔 {mk}", flush=True)
|
||
|
||
print(f"\n 月度:", flush=True)
|
||
for m in sorted(monthly.keys()):
|
||
d=monthly[m]; wr_m=d['w']/d['n']*100 if d['n']>0 else 0
|
||
bar = "+" * max(0, int(d['net']/200)) + "-" * max(0, int(-d['net']/200))
|
||
print(f" {m} {d['n']:>4}笔 {d['net']:>+8.0f} {wr_m:>4.0f}% {bar}", flush=True)
|
||
print(f" {'合计':>7} {n:>4}笔 {net:>+8.0f}", flush=True)
|
||
print(f"{'='*75}", flush=True)
|
||
return net, monthly
|
||
|
||
def main():
|
||
print("Loading...", flush=True)
|
||
data = load()
|
||
print(f"{len(data)} bars\n", flush=True)
|
||
|
||
# 测试不同仓位大小
|
||
margins = [100, 200, 300, 500, 800, 1000]
|
||
|
||
print("="*80, flush=True)
|
||
print(" 不同保证金下的收益 (100x杠杆)", flush=True)
|
||
print("="*80, flush=True)
|
||
|
||
all_results = []
|
||
for margin in margins:
|
||
notional = margin * 100
|
||
trades = run(data, notional)
|
||
net, monthly = report(trades, notional, f"{margin}U保证金")
|
||
all_results.append((margin, notional, len(trades), net, monthly))
|
||
|
||
# 总览
|
||
print(f"\n\n{'='*80}", flush=True)
|
||
print(f" 总览 — 目标: 每月 1000 USDT", flush=True)
|
||
print(f"{'='*80}", flush=True)
|
||
print(f" {'保证金':>6} {'杠杆':>4} {'名义值':>10} {'交易':>5} {'年净利':>10} {'月均':>8} {'达标':>4}", flush=True)
|
||
print(f" {'-'*52}", flush=True)
|
||
for margin, notional, n, net, monthly in all_results:
|
||
mavg = net/12
|
||
ok = "YES" if mavg>=1000 else "no"
|
||
print(f" {margin:>5}U {100:>3}x {notional:>9,}U {n:>5} {net:>+10.0f} {mavg:>+8.0f} {ok:>4}", flush=True)
|
||
|
||
# 找到达标的最小保证金
|
||
print(f"\n 结论:", flush=True)
|
||
for margin, notional, n, net, monthly in all_results:
|
||
if net/12 >= 1000:
|
||
print(f" >>> {margin}U 保证金即可达到月均 {net/12:.0f} USDT <<<", flush=True)
|
||
# 打印该配置的月度
|
||
print(f"\n {margin}U配置月度明细:", flush=True)
|
||
pm = 0
|
||
for m in sorted(monthly.keys()):
|
||
d = monthly[m]
|
||
status = "盈" if d['net']>0 else "亏"
|
||
print(f" {m}: {d['net']:>+8.0f} USDT ({d['n']}笔) [{status}]", flush=True)
|
||
if d['net'] > 0: pm += 1
|
||
print(f" 盈利月份: {pm}/12", flush=True)
|
||
break
|
||
else:
|
||
# 没有达标的，计算需要多少
|
||
base_net = all_results[0][3] # 100U的净利
|
||
if base_net > 0:
|
||
needed = int(12000 / base_net * 100) + 1
|
||
print(f" 100U净利={base_net:.0f}/年 → 达标需约 {needed}U 保证金", flush=True)
|
||
else:
|
||
print(f" 策略本身不盈利，需要继续优化信号质量", flush=True)
|
||
|
||
print(f"{'='*80}", flush=True)
|
||
|
||
# 保存最佳配置的交易记录
|
||
best = max(all_results, key=lambda x: x[3])
|
||
margin, notional = best[0], best[1]
|
||
trades = run(data, notional)
|
||
csv = Path(__file__).parent.parent / 'final_trades.csv'
|
||
with open(csv, 'w', encoding='utf-8-sig') as f:
|
||
f.write("信号,方向,开仓价,平仓价,盈亏,持仓秒,原因,开仓时间,平仓时间\n")
|
||
for t in trades:
|
||
f.write(f"{t[0]},{t[1]},{t[2]:.2f},{t[3]:.2f},{t[4]:.2f},{t[5]:.0f},{t[6]},{t[7]},{t[8]}\n")
|
||
print(f"\n 交易记录: {csv}", flush=True)
|
||
|
||
if __name__=='__main__':
|
||
main()
|