126 lines
4.0 KiB
Python
126 lines
4.0 KiB
Python
"""
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evolution/auto_iterator.py — 策略自动迭代
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健康度低时生成参数变体，跑回测，记录结果
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"""
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import sys, os, json, sqlite3, copy
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from datetime import datetime
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sys.path.insert(0, '/home/hmo/MoFin')
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import strategy_lab as lab
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DB = '/home/hmo/MoFin/data/mofin.db'
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# 可迭代的参数空间
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PARAM_SPACE = {
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'max_hold_days': [40, 60, 80, 100, 120],
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'reentry_days': [5, 10, 15, 20],
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'sl_atr': [1.0, 1.5, 2.0, 2.5],
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}
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def get_current_health(version='v_next4', days=7):
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"""获取当前策略健康度"""
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conn = sqlite3.connect(DB)
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conn.row_factory = sqlite3.Row
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rows = conn.execute("""
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SELECT health_score, date FROM strategy_health
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WHERE strategy_version=? ORDER BY date DESC LIMIT ?
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""", (version, days)).fetchall()
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conn.close()
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if not rows:
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return 50 # 无数据，中性
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return round(sum(r['health_score'] for r in rows) / len(rows), 1)
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def propose_variants(parent_version, health):
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"""根据健康度生成变体参数建议"""
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if health >= 70:
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print(f"健康度{health}≥70，无需迭代", flush=True)
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return []
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variants = []
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severity = 'minor' if health >= 50 else 'major'
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if severity == 'minor':
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# 小幅调参
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variants.append({
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'parent': parent_version,
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'params': {'max_hold_days': 80, 'reentry_days': 15, 'sl_atr': 1.5},
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'description': '微调：确保当前最优参数',
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})
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else:
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# 大幅调参（扫参数网格）
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base_hold = 60
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base_reentry = 10
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for hold in PARAM_SPACE['max_hold_days']:
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for reentry in PARAM_SPACE['reentry_days']:
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variants.append({
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'parent': parent_version,
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'params': {'max_hold_days': hold, 'reentry_days': reentry, 'sl_atr': 1.5},
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'description': f'网格扫描: h{hold}/r{reentry}',
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})
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return variants
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def test_variant(variant):
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"""测试单个变体"""
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name = f"auto_h{variant['params']['max_hold_days']}_r{variant['params']['reentry_days']}"
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# 克隆基座配置
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base = lab.STRATEGIES.get(variant['parent'])
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if not base:
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return None
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cfg = copy.deepcopy(base)
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cfg['version'] = name
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cfg['name'] = f"自进化-{variant['description']}"
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for k, v in variant['params'].items():
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cfg['config']['exit'][k] = v
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lab.STRATEGIES[name] = cfg
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results = {}
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for tag, start, end in [('5y', '2021-07-01', '2026-07-24')]:
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r = lab.run_backtest(name, start, end, 913000, save=False, universe='a', period_tag=tag)
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pf = r['summary'].get('portfolio_full', {})
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results[tag] = {
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'full': pf.get('total_return_pct'),
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'cagr': pf.get('cagr_pct'),
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'dd': pf.get('portfolio_max_dd_pct'),
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}
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return {'name': name, 'description': variant['description'], 'results': results}
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def run_iteration(version='v_next4'):
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"""执行一次迭代检查"""
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health = get_current_health(version)
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print(f"{version} 健康度: {health}", flush=True)
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variants = propose_variants(version, health)
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if not variants:
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return []
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conn = sqlite3.connect(DB)
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results = []
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for v in variants[:3]: # 最多测3个
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print(f"测试: {v['description']}", flush=True)
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r = test_variant(v)
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if r:
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results.append(r)
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# 记录到 evolution 表
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conn.execute("""
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INSERT INTO strategy_evolution (parent_version, child_version, change_description, backtest_result, promoted)
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VALUES (?, ?, ?, ?, 0)
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""", (version, r['name'], r['description'], json.dumps(r['results'], ensure_ascii=False)))
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conn.commit()
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# 打印对比
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for r in results:
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rs = r['results'].get('5y', {})
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print(f" {r['name']}: full={rs.get('full')}% cagr={rs.get('cagr')}% dd={rs.get('dd')}%", flush=True)
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conn.close()
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return results
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if __name__ == '__main__':
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run_iteration()
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