单一持仓 · 示例组合

一只股票，全部押上。

最纯粹的集中度案例。引擎所有关于分散的指标都收敛为一，评分显示出一家伟大的公司和一个脆弱的组合可以是同一回事。

组合构成

NVDA100%

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。

13.2 / 100

投资组合评分弱

结构性问题占主导。

集中度或证据质量远超出该风险档的范围。请从第一条建议开始。

弱中性良好强

已解析 1 个持仓 · 中风险档 · 引擎 2026-03-07-v5 · 走势恶化（置信度 100%）

多少分算好？ → 为我的组合评分

最大持仓: 100.0% NVDA · 上限 30%
有效持仓数: 1.0 共持有 1 个 · 目标 8
最大行业: 100.0% 科技
加权贝塔: 2.22 市场敏感度
仓位计划: 投资 40% 现金 60% · 防御
您目前: 投资 100% 现金 0%

分项评分

分散度4
风险平衡17
质量72
信号0
趋势0
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
NVDA 占投资市值的 100.0%。中风险档将 30.0% 视为单一持仓的上限。
关注 单一行业占主导
科技占投资市值的 100.0%。当一个行业权重如此之高时，单一宏观主题就决定了大部分结果。
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 1.0 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 100.0% 处于信号读数为负的持仓中，超出该风险档的容忍范围。
优先 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 40.0%、现金 60.0%，以渐进节奏投入。
关注 加权持仓得分偏低
各持仓按市值加权的得分为 -4.47。组合依赖于读数较弱的标的。

持仓明细

代码	行业	市值	权重	信号	得分	类型
NVDA	科技	50,000	100.0%	卖出	-4.47	高贝塔

证据限制：

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": 13.199999999999999289457264239899814128875732421875,
        "health_score": 13.199999999999999289457264239899814128875732421875,
        "status": "Weak",
        "status_key": "weak",
        "count": 1,
        "weighted_score": -4.46999999999999975131004248396493494510650634765625,
        "max_position_weight": 100,
        "max_position_ticker": "NVDA",
        "effective_positions": 1,
        "weighted_beta": 2.220000000000000195399252334027551114559173583984375,
        "signal_mix": {
            "buy": 0,
            "hold": 0,
            "sell": 100
        },
        "trend_alignment_pct": 0,
        "trend_negative_pct": 100,
        "weighted_grade_score": 5,
        "weighted_dividend_score": 4.4000000000000003552713678800500929355621337890625,
        "top_sector": "Technology",
        "top_sector_weight": 100,
        "score_components": {
            "signal": 0,
            "diversification": 4.20000000000000017763568394002504646778106689453125,
            "risk": 17.10000000000000142108547152020037174224853515625,
            "quality": 72,
            "trend": 0,
            "macro": 0
        },
        "trajectory": {
            "direction": "deteriorating",
            "confidence": 100,
            "summary": "Negative signal concentration or weakening trend"
        },
        "context_alignment": {
            "score": 0,
            "coverage_pct": 100,
            "matched_weight_pct": 100,
            "top_sector_view": null
        },
        "forward_confidence": 78,
        "exposure_plan": {
            "target_invested_pct": 40,
            "target_cash_pct": 60,
            "min_invested_pct": 40,
            "max_invested_pct": 53,
            "min_cash_pct": 47,
            "max_cash_pct": 60,
            "base_invested_pct": 72,
            "stance": "defensive",
            "deployment_speed": "gradual",
            "confidence": 56,
            "market_regime_score": 50,
            "market_regime_code": "",
            "reason_codes": [
                "negative_signal_balance",
                "negative_trend_pressure",
                "high_sell_weight",
                "concentration_risk",
                "strong_forward_confidence"
            ],
            "components": {
                "market_adjustment": 0,
                "signal_adjustment": -14,
                "trend_adjustment": -10,
                "sell_penalty": 16,
                "concentration_penalty": 18
            }
        },
        "holding_analysis": [
            {
                "ticker": "NVDA",
                "weight_pct": 100,
                "score": -4.46999999999999975131004248396493494510650634765625,
                "signal": "SELL",
                "sector": "Technology",
                "profile": "high_beta",
                "lens": "risk_control",
                "classification_confidence": 78,
                "classification_quality": "usable",
                "classification_ambiguous": false,
                "classification_reason_codes": [
                    "high_beta"
                ],
                "factor_evidence_confidence": 0,
                "factor_evidence_score": null,
                "factor_match_count": 0,
                "factor_required_count": 5,
                "factor_has_sufficient_evidence": false,
                "factor_matched_factors": [],
                "top_factor": null,
                "top_factor_direction": null,
                "lens_confidence": 78
            }
        ],
        "coverage": {
            "beta_pct": 100,
            "grade_pct": 100,
            "dividend_pct": 100,
            "trend_pct": 100,
            "macro_pct": 100
        },
        "diagnostics": {
            "risk_level": "medium",
            "risk_profile": {
                "target_max_weight": 0.299999999999999988897769753748434595763683319091796875,
                "target_sector_weight": 0.40000000000000002220446049250313080847263336181640625,
                "target_sell_weight": 0.200000000000000011102230246251565404236316680908203125,
                "target_effective_positions": 8,
                "beta_band_min": 0.75,
                "beta_band_max": 1.25
            },
            "profile_mix": {
                "high_beta": 100
            },
            "lens_mix": {
                "risk_control": 100
            },
            "classification": {
                "avg_confidence": 78,
                "quality": "usable",
                "low_confidence_weight_pct": 0,
                "ambiguous_weight_pct": 0,
                "weak_count": 0,
                "low_confidence_tickers": []
            },
            "factor_evidence": {
                "avg_confidence": 0,
                "quality": "weak",
                "low_confidence_weight_pct": 100,
                "missing_weight_pct": 100,
                "aligned_weight_pct": 0,
                "avg_lens_confidence": 78
            },
            "sector_context": {
                "scores": [],
                "top_sector": "Technology",
                "top_sector_score": null,
                "top_sector_detail": null
            },
            "market_regime": {
                "selected_code": "",
                "mode": "missing",
                "score": null,
                "weights_pct": {
                    "OSL": 0,
                    "US": 0,
                    "GLOBAL": 0
                },
                "selected_regime": null
            },
            "data_gaps": [
                "Missing lens-specific factor evidence for large parts of the portfolio",
                "Weak factor evidence confidence reduces forward-looking reliability"
            ]
        },
        "insights": [
            {
                "id": "weighted_score",
                "value": -4.46999999999999975131004248396493494510650634765625,
                "tone": "risk",
                "status_key": "weak"
            },
            {
                "id": "target_invested_pct",
                "value": 40,
                "cash_pct": 60,
                "stance": "defensive",
                "confidence": 56,
                "tone": "risk"
            },
            {
                "id": "effective_positions",
                "value": 1,
                "tone": "risk"
            },
            {
                "id": "largest_position",
                "value": 100,
                "ticker": "NVDA",
                "tone": "risk"
            },
            {
                "id": "top_sector",
                "value": 100,
                "sector": "Technology",
                "tone": "risk"
            },
            {
                "id": "signal_mix",
                "buy": 0,
                "hold": 0,
                "sell": 100,
                "tone": "risk"
            },
            {
                "id": "portfolio_trajectory",
                "value": "deteriorating",
                "tone": "risk",
                "confidence": 100
            },
            {
                "id": "weighted_beta",
                "value": 2.220000000000000195399252334027551114559173583984375,
                "tone": "risk"
            },
            {
                "id": "macro_alignment",
                "value": 0,
                "tone": "risk"
            },
            {
                "id": "lens_confidence",
                "value": 78,
                "tone": "warn"
            }
        ],
        "suggestions": [
            {
                "tone": "risk",
                "code": "reduce_single_position",
                "ticker": "NVDA",
                "weight_pct": 100,
                "target_pct": 30,
                "risk_level": "medium"
            },
            {
                "tone": "warn",
                "code": "diversify_sector",
                "sector": "Technology",
                "weight_pct": 100
            },
            {
                "tone": "warn",
                "code": "increase_diversification",
                "effective_positions": 1
            },
            {
                "tone": "risk",
                "code": "lower_sell_exposure",
                "sell_pct": 100
            },
            {
                "tone": "risk",
                "code": "hold_higher_cash_buffer",
                "cash_pct": 60,
                "invested_pct": 40,
                "deployment_speed": "gradual"
            },
            {
                "tone": "warn",
                "code": "lift_quality_score",
                "weighted_score": -4.46999999999999975131004248396493494510650634765625
            }
        ],
        "portfolio_input": {
            "cash_balance": 0,
            "holdings_value": 50000,
            "total_value": 50000,
            "cash_pct": 0,
            "invested_pct": 100,
            "missing_tickers": []
        }
    }
}

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。