diff --git a/static/index.html b/static/index.html index 7326f9d3..cc49e69f 100644 --- a/static/index.html +++ b/static/index.html @@ -2153,7 +2153,7 @@ function renderStrategyTable(strategies) { html += '' + '' + s.version + (isCurrent ? ' 当前' : '') + ((s.market && s.market !== 'all') ? ' ' + (s.market === 'hk' ? '港' : 'A') + '' : '') + '' + '' + (s.name || '') + (smallSample ? ' ⚠️' : '') + '' + - '' + (st.sizing_slots ? st.sizing_slots + '仓' : '10仓') + '' + + '' + (st.sizing_slots ? st.sizing_slots + '仓' : '10仓') + (st.conviction_model ? '⚡' : '') + '' + '' + ((s.description && s.description.title) ? '' : '—') + '' + cell('composite', s._composite, v => v + (s._confidence != null && s._confidence < 1 ? '×' + s._confidence.toFixed(2) + '' : ''), 'font-bold text-amber-300') + cell('universality_score', (st.universality || {}).score, v => v + '/' + (st.universality || {}).months + '月') + diff --git a/strategy_lab.py b/strategy_lab.py index 38712c1c..95916f11 100644 --- a/strategy_lab.py +++ b/strategy_lab.py @@ -494,6 +494,47 @@ def get_strategy(version): # 各策略的最优仓位模型（仓位扫描实证，2026-07-29） # 波段/结构出场适合大仓少股，固定出场适合小仓多股 +def _v81_conviction(version, name, summary, hypothesis, conviction): + """v8.1波段基座 + 信念分级仓位配置（2026-07-30 正式注册，替代临时脚本）""" + s = _v40_branch(version, name, summary, hypothesis, + entry_overrides={"vol_ratio_min": 0.9, "vol_ratio_max": 2.0, "sector_slope_max": 1.0, + "hl_only": True, "rsi_delta_min": 6}, + exit_overrides={"tp_pct": None, "exit_mode": "swing", "sl_atr": 1.5, + "max_hold_days": 60, "reentry_days": 10}) + s['config']['conviction'] = conviction + s['created'] = '2026-07-30' + return s + +STRATEGIES.update({ + "v_next": _v81_conviction("v_next", "v8.1+三重信念×2(平铺)", + "v8.1波段基座; 任一信念因子命中(DNA/行业ADX>=20/资金加速度)仓位×2, 不叠乘", + "v8.1波段单笔最优(均赢+21.78%), 信念因子区分好坏票——命中即加倍, 简单稳健", + {"model": "平铺: DNA or 行业ADX>=20 or flow_delta>0 → ×2", + "stack": False, "dna_mult": 2.0, "sector_adx_min": 20, "sector_mult": 2.0, + "flow_delta_min": 0, "flow_mult": 2.0}), + "v_next3": _v81_conviction("v_next3", "v8.1+信念叠乘+行业牛杠杆", + "v8.1波段基座; DNA×2 + 行业ADX>25×2 + flow_delta>0×2 叠乘, 封顶×4", + "多因子共振的票才是极品配最重仓; 行业ADX>25=行业级确认牛, 比>=20更精准", + {"model": "叠乘封顶×4: DNA×2 + 行业ADX>25×2 + flow_delta>0×2", + "stack": True, "cap": 4.0, "dna_mult": 2.0, "sector_adx_min": 25, "sector_mult": 2.0, + "flow_delta_min": 0, "flow_mult": 2.0}), +}) + +STRATEGY_DESCRIPTIONS.update({ + "v_next": { + "title": "v8.1+三重信念×2 平铺版（DNA/行业ADX≥20/资金加速度, 任一命中即×2）", + "algorithm": "v8.1波段出场基座 + 三重信念信号平铺重仓: 动量基因DNA、行业趋势强(行业ADX≥20)、资金加速(flow_delta>0)——任一命中仓位×2, 多命中不叠乘。基准3仓。", + "rationale": "v8.1波段单笔最优(均赢+21.78%), 信念因子区分好坏票——命中即加倍, 规则简单稳健。与v_next3的区别: 平铺只分'有没有信念', 不区分'信念有多强'。", + "evidence": "5年全参与+48.3%(年化8.8%)/回撤4.1%。×2票69%胜率/+14.23% vs ×1票48%/+5.99%。规则经逆向验证103/103笔精确复现(平铺×2)。", + }, + "v_next3": { + "title": "v8.1+信念叠乘+行业牛杠杆（DNA×2·行业ADX>25×2·资金加速度×2, 封顶×4）【当前最优】", + "algorithm": "v8.1波段出场基座 + 信念因子叠乘重仓: 动量基因DNA×2、行业确认牛(行业ADX>25)×2、资金加速度(flow_delta>0)×2; 多因子同时命中则叠乘, 封顶×4; 均不命中×1。基准3仓, 单票最大4倍基准仓。", + "rationale": "v_next平铺只区分'有没有信念', 叠乘区分'信念有多强'——多因子共振的票是极品, 配最重仓位。行业ADX>25是行业级确认牛(比≥20更严格), 对应生产端行业牛杠杆(ADX>25升一档仓位)。", + "evidence": "5年103笔/57.3%胜率, 全参与+55.6%(年化9.1%)/回撤4.1%, 收益/回撤比12.4全场最优。boost分布×1:56笔/×2:37笔/×4:10笔。规则经逆向验证102/103笔精确复现。", + }, +}) + STRATEGY_SIZING = { 'v7.1': 4, # 固定15%出场，4仓+74.6%最优(10仓+59.8%) 'v7.2': 3, # 分批止盈，3仓+60.7% @@ -505,6 +546,8 @@ STRATEGY_SIZING = { 'v7.1b': 4, # 同v7.1，4仓 'v11.0': 3, # 枢轴波段，3仓+116.4% 'v11.1': 3, # 枢轴强压/弱撑，3仓+55.8% + 'v_next': 3, # 信念平铺×2，同v8.1基座3仓 + 'v_next3': 3, # 信念叠乘封顶×4，同v8.1基座3仓 } @@ -937,6 +980,7 @@ def run_backtest(strategy_version, start_date, end_date, capital=913000, save=Tr factors['sector_inflow'] = sc_ctx.get('inflow') factors['sector_above_ma20'] = sc_ctx.get('above_ma20') factors['sector_slope'] = sc_ctx.get('slope') + factors['sector_adx'] = sc_ctx.get('adx') # 资金面因子 fl = flow_ctx(code, date, None, i) factors.update(fl) @@ -1236,10 +1280,40 @@ def run_backtest(strategy_version, start_date, end_date, capital=913000, save=Tr _y0 = datetime.strptime(start_date, '%Y-%m-%d') _y1 = datetime.strptime(end_date, '%Y-%m-%d') _bt_years = max((_y1 - _y0).days / 365.0, 0.5) - # 信念缩放（通用，2026-07-29验证全策略+7~16pp）：动量基因票默认×2.5 - boost_k = cfg.get('exit', {}).get('dna_boost', 2.5) - for t in trades: - t['boost'] = boost_k if t.get('dna') else 1.0 + # 信念缩放：优先 conviction 多因子配置，否则默认动量基因×2.5（2026-07-29验证全策略+7~16pp） + conv = cfg.get('conviction') + if conv: + _dna_m = conv.get('dna_mult', 2.0) + _sec_t = conv.get('sector_adx_min', 25) + _sec_m = conv.get('sector_mult', 2.0) + _flo_t = conv.get('flow_delta_min', 0) + _flo_m = conv.get('flow_mult', 2.0) + _cap = conv.get('cap') + _stack = conv.get('stack', True) + for t in trades: + _f = t.get('factors') or {} + _sa = _f.get('sector_adx') + _sec_hit = _sa is not None and _sa > _sec_t + _fd = _f.get('flow_delta') + _flo_hit = _fd is not None and _fd > _flo_t + if _stack: + b = 1.0 + if t.get('dna'): + b *= _dna_m + if _sec_hit: + b *= _sec_m + if _flo_hit: + b *= _flo_m + if _cap: + b = min(b, _cap) + else: + b = _dna_m if (t.get('dna') or _sec_hit or _flo_hit) else 1.0 + t['boost'] = b + summary['conviction_model'] = conv.get('model', '') + else: + boost_k = cfg.get('exit', {}).get('dna_boost', 2.5) + for t in trades: + t['boost'] = boost_k if t.get('dna') else 1.0 # 集中仓位（该策略最优激进仓位） slots = STRATEGY_SIZING.get(strategy_version, 10) summary['portfolio'] = portfolio_sim(trades, capital, slots)