集中度 · 示例组合

受伯克希尔启发的示例组合评分

2026年9月17日发布的示例组合。所示权重是用于研究集中度的固定输入，并非经核实的伯克希尔·哈撒韦当前持仓或某份13F申报的内容。重新评分会更新分析，不会更新组合持仓。

组合构成

AAPL40%
AXP15%
BAC12%
KO10%
CVX8%
OXY5%
MCO3%
KHC3%
CB3%
DVA1%

权重如图所示，中风险档。约每周自动重新评分；日期和引擎版本见结果。

74.0 / 100

投资组合评分良好

扎实，但有几处需要收紧。

结构站得住。有一两个分项拉低了评分，下面已按优先级列出。

弱中性良好强

已解析 10 个持仓 · 中风险档 · 引擎 2026-03-07-v5 · 走势改善（置信度 36%）

多少分算好？ → 为我的组合评分

最大持仓: 40.0% AAPL · 上限 30%
有效持仓数: 4.6 共持有 10 个 · 目标 8
最大行业: 40.0% 科技
加权贝塔: 0.88 市场敏感度
仓位计划: 投资 74% 现金 26% · 均衡
您目前: 投资 100% 现金 0%

分项评分

分散度80
风险平衡91
质量59
信号96
趋势59
市场环境0

当引擎缺乏某分项的证据时，会显示“无数据”——如实报告，而非猜测。

优先关注

优先 最大持仓超过风险档上限
AAPL 占投资市值的 40.0%。中风险档将 30.0% 视为单一持仓的上限。
关注 有效持仓数比看起来少
按仓位大小计算，本组合的集中度相当于约 4.6 个等权持仓，低于风险档目标。
优先 负面信号持仓占比较大
投资市值的 30.0% 处于信号读数为负的持仓中，超出该风险档的容忍范围。
关注 仓位计划倾向于保留现金缓冲
根据当前的信号、趋势和集中度证据，计划目标约为投资 73.7%、现金 26.3%，以渐进节奏投入。
关注 因子证据有限
投资市值的 100.0% 缺少因子证据，这限制了引擎能够支持的前瞻性判断。
关注 前瞻置信度有限
透镜置信度平均为 46.3%。请将趋势和市场环境分项视为暂定结论。

持仓明细

代码	行业	市值	权重	信号	得分	类型
AAPL	科技	40,000	40.0%	买入	6.20	核心
AXP	金融服务	15,000	15.0%	卖出	-2.00	困境反转
BAC	金融服务	12,000	12.0%	卖出	-4.86	困境反转
KO	防御性消费	10,000	10.0%	买入	5.80	核心
CVX	能源	8,000	8.0%	持有	0.00	周期型
OXY	能源	5,000	5.0%	买入	2.44	周期型
MCO	金融服务	3,000	3.0%	持有	-1.30	困境反转
KHC	防御性消费	3,000	3.0%	卖出	-2.49	困境反转
CB	金融服务	3,000	3.0%	买入	3.63	核心
DVA	医疗保健	1,000	1.0%	持有	-1.04	防御型

证据限制：

部分持仓缺少评级数据
部分持仓缺少股息质量数据
部分持仓的股票类型分类置信度较低
大部分持仓缺少透镜专属的因子证据
因子证据置信度低，削弱了前瞻判断的可靠性

POST /evaluate

上面的每个数字都来自一次 API 调用。

本页面就是下方 JSON 的可视化呈现。把同样的内容构建到仪表板、顾问工具或 AI 代理中。所有方案使用同一引擎，使用 API 密钥每月可免费评估五次。

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显示原始响应

{
    "ok": true,
    "evaluation": {
        "engine_version": "2026-03-07-v5",
        "score": 74,
        "health_score": 74,
        "status": "Good",
        "status_key": "good",
        "count": 10,
        "weighted_score": 2.279999999999999804600747665972448885440826416015625,
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        "effective_positions": 4.57000000000000028421709430404007434844970703125,
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        "trend_alignment_pct": 58,
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            {
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                "profile": "cyclical",
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                "low_confidence_tickers": [
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            },
            "factor_evidence": {
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            "sector_context": {
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            "market_regime": {
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            "data_gaps": [
                "Missing grade data for part of the portfolio",
                "Missing dividend quality data for part of the portfolio",
                "Weak stock-type classification confidence for part of the portfolio",
                "Missing lens-specific factor evidence for large parts of the portfolio",
                "Weak factor evidence confidence reduces forward-looking reliability"
            ]
        },
        "insights": [
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            {
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            {
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            },
            {
                "id": "largest_position",
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                "ticker": "AAPL",
                "tone": "risk"
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            {
                "id": "top_sector",
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                "sector": "Technology",
                "tone": "warn"
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            {
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                "buy": 58,
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            },
            {
                "id": "portfolio_trajectory",
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            {
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        ],
        "suggestions": [
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                "code": "reduce_single_position",
                "ticker": "AAPL",
                "weight_pct": 40,
                "target_pct": 30,
                "risk_level": "medium"
            },
            {
                "tone": "warn",
                "code": "increase_diversification",
                "effective_positions": 4.5999999999999996447286321199499070644378662109375
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            {
                "tone": "risk",
                "code": "lower_sell_exposure",
                "sell_pct": 30
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            {
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                "code": "hold_higher_cash_buffer",
                "cash_pct": 26.300000000000000710542735760100185871124267578125,
                "invested_pct": 73.7000000000000028421709430404007434844970703125,
                "deployment_speed": "gradual"
            },
            {
                "tone": "warn",
                "code": "expand_factor_coverage",
                "missing_weight_pct": 100
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            {
                "tone": "warn",
                "code": "lower_forward_confidence",
                "lens_confidence": 46.2999999999999971578290569595992565155029296875
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        ],
        "portfolio_input": {
            "cash_balance": 0,
            "holdings_value": 100000,
            "total_value": 100000,
            "cash_pct": 0,
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            "missing_tickers": []
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    }
}

PORTIQA 的输出为定量分析，仅供参考，不构成投资建议。请参阅金融免责声明。