188 lines
7.7 KiB
Python
188 lines
7.7 KiB
Python
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"""
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EMA趋势策略 - 精简参数优化 v2
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已知：EMA(8/21/120) ATR>0.03% SL=0.4% MaxH=1800 → 方向PnL +327, 净亏 -101
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优化目标：找到净盈利 > 0 的参数组合
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策略核心：减少交易次数（更长EMA/更高ATR门槛），提高每笔质量
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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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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)
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self.v = None
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def update(self, price):
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if self.v is None:
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self.v = price
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else:
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self.v = price * 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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# pre-convert to list of tuples for speed
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out = []
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for r in rows:
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out.append((datetime.datetime.fromtimestamp(r[0]/1000.0), r[1], r[2], r[3], r[4]))
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return out
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def bt(data, fp, sp, bp, atr_min, sl_pct, mh):
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bal = 1000.0
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pos = 0; op = 0.0; ot = None; ps = 0.0; pend = None
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ef = EMA(fp); es = EMA(sp); eb = EMA(bp)
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hs_buf = []; ls_buf = []; cs_buf = []
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pf_ = None; ps_ = None
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tc=0; wc=0; dpnl=0.0; tfee=0.0; treb=0.0
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hsl = sl_pct * 1.5
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LEV=50; RP=0.005; TF=0.0006; RR=0.90; MH=200; AP=14
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for dt, o_, h_, l_, c_ in data:
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p = c_
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hs_buf.append(h_); ls_buf.append(l_); cs_buf.append(p)
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fast = ef.update(p); slow = es.update(p); big = eb.update(p)
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atr_pct = 0.0
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if len(hs_buf) > AP + 1:
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s = 0.0
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for i in range(-AP, 0):
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tr = hs_buf[i] - ls_buf[i]
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d1 = abs(hs_buf[i] - cs_buf[i-1])
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d2 = abs(ls_buf[i] - cs_buf[i-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_pct = s / (AP * 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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if pos != 0 and ot is not None:
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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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if -pp >= hsl:
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pnl_ = ps * pp; cv = ps*(1+pp); cf = cv*TF; of_=ps*TF; tt=of_+cf; rb=tt*RR
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bal += pnl_ - cf + rb; dpnl += pnl_; tfee += tt; treb += rb
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tc += 1; wc += (1 if pnl_ > 0 else 0)
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pos=0; op=0; ot=None; ps=0; pend=None
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continue
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if hsec >= MH:
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do_c = False
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if -pp >= sl_pct: do_c = True
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elif hsec >= mh: do_c = True
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elif pos == 1 and cd: do_c = True
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elif pos == -1 and cu: do_c = True
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elif pend == 'cl' and pos == 1: do_c = True
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elif pend == 'cs' and pos == -1: do_c = True
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if do_c:
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pnl_ = ps * pp; cv = ps*(1+pp); cf = cv*TF; of_=ps*TF; tt=of_+cf; rb=tt*RR
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bal += pnl_ - cf + rb; dpnl += pnl_; tfee += tt; treb += rb
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tc += 1; wc += (1 if pnl_ > 0 else 0)
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pos=0; op=0; ot=None; ps=0; pend=None
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if atr_pct >= atr_min:
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if (cd or fast < slow) and p < big:
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ns = bal * RP * LEV
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if ns >= 1: bal -= ns*TF; pos=-1; op=p; ot=dt; ps=ns
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elif (cu or fast > slow) and p > big:
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ns = bal * RP * LEV
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if ns >= 1: bal -= ns*TF; pos=1; op=p; ot=dt; ps=ns
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continue
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else:
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if pos == 1 and cd: pend = 'cl'
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elif pos == -1 and cu: pend = 'cs'
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if pos == 0 and atr_pct >= atr_min:
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if cu and p > big:
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ns = bal * RP * LEV
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if ns >= 1: bal -= ns*TF; pos=1; op=p; ot=dt; ps=ns
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elif cd and p < big:
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ns = bal * RP * LEV
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if ns >= 1: bal -= ns*TF; pos=-1; op=p; ot=dt; ps=ns
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if pos != 0:
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p = data[-1][4]
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pp = (p - op) / op if pos == 1 else (op - p) / op
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pnl_ = ps * pp; cv = ps*(1+pp); cf = cv*TF; of_=ps*TF; tt=of_+cf; rb=tt*RR
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bal += pnl_ - cf + rb; dpnl += pnl_; tfee += tt; treb += rb
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tc += 1; wc += (1 if pnl_ > 0 else 0)
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net = bal - 1000.0
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wr = wc/tc*100 if tc > 0 else 0
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return net, tc, wr, dpnl, treb, tfee - treb
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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 loaded\n", flush=True)
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# 精简参数网格 - 只测最有潜力的范围
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combos = []
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for fp in [8, 13, 20, 30]:
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for sp in [21, 34, 55, 80]:
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if fp >= sp: continue
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for bp in [120, 200]:
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for am in [0.0003, 0.0006, 0.001, 0.0015, 0.002]:
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for sl in [0.004, 0.006, 0.008, 0.01]:
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for mh in [1200, 1800, 3600]:
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combos.append((fp, sp, bp, am, sl, mh))
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print(f"Combos: {len(combos)}", flush=True)
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results = []
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t0 = time.time()
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for idx, (fp, sp, bp, am, sl, mh) in enumerate(combos):
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net, tc, wr, dp, reb, nf = bt(data, fp, sp, bp, am, sl, mh)
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results.append((net, tc, wr, dp, reb, nf, fp, sp, bp, am, sl, mh))
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if (idx+1) % 30 == 0:
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el = time.time() - t0
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eta = el/(idx+1)*(len(combos)-idx-1)
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print(f" [{idx+1}/{len(combos)}] {el:.0f}s done, ~{eta:.0f}s left", flush=True)
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tt = time.time() - t0
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print(f"\nAll done! {len(results)} combos in {tt:.1f}s\n", flush=True)
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results.sort(key=lambda x: x[0], reverse=True)
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profitable = [r for r in results if r[0] > 0]
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print(f"Profitable: {len(profitable)} / {len(results)} ({len(profitable)/len(results)*100:.1f}%)\n", flush=True)
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print(f"{'='*130}", flush=True)
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print(f" TOP 30", flush=True)
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print(f"{'='*130}", flush=True)
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print(f" {'#':>3} {'F':>3} {'S':>3} {'B':>4} {'ATR':>6} {'SL':>5} {'MH':>5} | {'Net%':>7} {'Net$':>9} {'#Trd':>6} {'WR':>6} {'DirPnL':>9} {'Rebate':>9} {'NetFee':>8}", flush=True)
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print(f" {'-'*120}", flush=True)
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for i, (net, tc, wr, dp, reb, nf, fp, sp, bp, am, sl, mh) in enumerate(results[:30]):
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mk = " <-- $$" if net > 0 else ""
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print(f" {i+1:>3} {fp:>3} {sp:>3} {bp:>4} {am*100:>5.2f}% {sl*100:>4.1f}% {mh:>5} | {net/10:>+6.2f}% {net:>+8.2f} {tc:>6} {wr:>5.1f}% {dp:>+8.2f} {reb:>8.2f} {nf:>8.2f}{mk}", flush=True)
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if profitable:
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print(f"\n{'='*130}", flush=True)
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print(f" ALL PROFITABLE COMBOS", flush=True)
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print(f"{'='*130}", flush=True)
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for i, (net, tc, wr, dp, reb, nf, fp, sp, bp, am, sl, mh) in enumerate(profitable):
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print(f" {i+1:>3} EMA({fp}/{sp}/{bp}) ATR>{am*100:.2f}% SL={sl*100:.1f}% MH={mh}s | net={net:+.2f} ({net/10:+.2f}%) trades={tc} WR={wr:.1f}% dirPnL={dp:+.2f} rebate={reb:.2f} netFee={nf:.2f}", flush=True)
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# Save
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csv = Path(__file__).parent.parent / 'param_results.csv'
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with open(csv, 'w', encoding='utf-8-sig') as f:
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f.write("fast,slow,big,atr_min,stop_loss,max_hold,net_pct,net_usd,trades,win_rate,dir_pnl,rebate,net_fee\n")
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for net, tc, wr, dp, reb, nf, fp, sp, bp, am, sl, mh in results:
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f.write(f"{fp},{sp},{bp},{am},{sl},{mh},{net/10:.4f},{net:.4f},{tc},{wr:.2f},{dp:.4f},{reb:.4f},{nf:.4f}\n")
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print(f"\nSaved: {csv}", flush=True)
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if __name__ == '__main__':
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main()
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