知微
9a984dd4dc
1. stock_scorer.py — 共享的6维评分模块
- score_future_outlook(code, data) → (score, reasons)
- rank_by_outlook(holdings, data) → 排序列表
- settlement_delay_note(sell_code, buy_code) → 结算延迟说明
- is_hk_stock(code) → 判断港股通标的
2. stale_push_wlin.py 改用共享模块（去掉本地函数定义）
3. 换仓评估增加港股通结算延迟检测：
- 卖港股→买A股时标注⚠️T+2到账限制
- 本次推荐（招商银行+A股→海博思创）无需标注，全是A股
157 lines
4.6 KiB
Python
157 lines
4.6 KiB
Python
#!/usr/bin/env python3
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"""
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stock_scorer.py — 6维股票前景评分系统
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用于全面评估持仓或自选股的前景。
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评分越低（负数越大）= 前景越差，越值得考虑卖出。
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评分越高（正数越大）= 前景越好，越值得持有或买入。
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使用场景：
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- 换仓评估（决定卖什么）
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- 持仓审查（定期排名）
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- 组合优化（识别需清理的票）
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调用方式：
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from stock_scorer import score_future_outlook
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score, reasons = score_future_outlook(code, decisions_dict)
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# 批量评估
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from stock_scorer import rank_by_outlook
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rankings = rank_by_outlook(portfolio_holdings, decisions_dict)
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"""
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def score_future_outlook(code, decisions_data):
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"""6维评分：基于决策系统分析数据评估股票前景。
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评分维度（按重要度排序）：
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1. timing_signal — 决策系统主信号（买入/持有/深套持有）
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2. 技术形态 — bearish/bullish/neutral
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3. 量价关系 — 买卖盘主导
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4. 行业背景 — 板块强弱
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5. 盈亏比RR — 预期收益/风险
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6. 股票类别 — 蓝筹/深套/题材
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Args:
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code: 股票代码
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decisions_data: decisions.json 的 "decisions" 数组或 dict(code→数据)
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Returns:
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(score, reasons) — score浮点数，reasons字符串列表
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"""
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# 支持两种输入格式
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if isinstance(decisions_data, dict):
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d = decisions_data.get(code, {})
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elif isinstance(decisions_data, list):
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d = {}
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for e in decisions_data:
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if e.get("code") == code:
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d = e
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break
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else:
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return -999, ["无数据"]
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if not d:
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return -999, ["无数据"]
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score = 0.0
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reasons = []
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# 1. timing_signal — 最直接的信号
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signal = (d.get('timing_signal') or '').strip()
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if '买入' in signal or '加仓' in signal:
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score += 3
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reasons.append('有买入信号')
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elif '深套持有' in signal or '弱势持有' in signal:
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score -= 2
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reasons.append('深套/弱势持有')
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elif signal in ('持有', '') or not signal:
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score -= 0.5 # 中性偏弱（没有积极信号就是消极信号）
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reasons.append('无积极信号')
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# 2. 技术形态
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tech = (d.get('tech_snapshot') or '') or ''
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if '/bearish' in tech:
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score -= 1.5
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reasons.append('技术偏空')
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elif '/bullish' in tech:
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score += 1.5
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reasons.append('技术偏多')
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# 3. 量价关系
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if '主动卖盘占优' in tech:
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score -= 1
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reasons.append('卖盘主导')
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elif '主动买盘占优' in tech:
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score += 1
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reasons.append('买盘主导')
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# 4. 行业背景
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sector = (d.get('sector_context') or '') or ''
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if '大跌' in sector or '偏弱' in sector:
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score -= 0.5
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if '大涨' in sector or '偏强' in sector:
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score += 0.5
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# 5. 盈亏比RR
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rr = d.get('rr_ratio', 0) or 0
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if rr >= 2:
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score += 1
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reasons.append(f'RR{rr:.1f}')
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elif rr < 1:
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score -= 0.5
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reasons.append(f'RR{rr:.1f}<1')
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else:
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reasons.append(f'RR{rr:.1f}')
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# 6. 股票类别
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cat = (d.get('stock_category') or '') or ''
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if '蓝筹' in cat or '白马' in cat:
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score += 0.5
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elif '深套' in cat or '弱势' in cat:
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score -= 0.5
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return round(score, 1), reasons
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def rank_by_outlook(holdings_list, decisions_data):
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"""批量评估持仓的前景，返回排序后的列表（最差排前）。
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Args:
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holdings_list: 持仓列表，每项有 code, name, shares, cost, price 等
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decisions_data: decisions.json 数据
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Returns:
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排序后的列表，每项增加了 score, reasons 字段
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"""
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results = []
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for h in holdings_list:
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code = h.get("code", "")
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if not code:
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continue
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score, reasons = score_future_outlook(code, decisions_data)
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results.append({**h, "score": score, "reasons": reasons})
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results.sort(key=lambda x: x["score"])
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return results
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def is_hk_stock(code):
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"""判断是否为港股（港股通标的代码通常5位）"""
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return len(str(code)) <= 5
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def is_a_stock(code):
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"""判断是否为A股（6位代码）"""
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return len(str(code)) == 6
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def settlement_delay_note(sell_code, buy_code):
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"""返回资金结算延迟说明（如有）。"""
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sell_is_hk = is_hk_stock(sell_code)
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buy_is_hk = is_hk_stock(buy_code)
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if sell_is_hk and not buy_is_hk:
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return "（港股通卖出需T+2到账后才能买A股，注意时间差）"
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return ""
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