Concentration · portefeuille d’exemple

Les Magnificent 7 en portefeuille.

Sept des plus grandes entreprises du monde, détenues à parts égales. Cela paraît diversifié parce qu’il y a sept noms. Le moteur mesure ce que les sept ont en commun.

Le portefeuille

AAPL14%
MSFT14%
GOOGL14%
AMZN14%
NVDA14%
META14%
TSLA14%

Pondérations comme indiqué, profil de risque Moyen. Renoté automatiquement environ une fois par semaine ; la date et la version du moteur figurent sur le résultat.

63.0 / 100

Score de portefeuille Neutre

Preuves contrastées.

Les composantes se contredisent. Lisez-les séparément plutôt que de vous fier au seul chiffre.

Faible Neutre Bon Solide

7 positions résolues · profil de risque Moyen · moteur 2026-03-07-v5 · trajectoire en détérioration (27% de confiance)

Qu’est-ce qu’un bon score ? → Noter mon propre portefeuille

Plus grosse position: 14.3% AAPL · limite 30%
Positions effectives: 7.0 sur 7 détenues · cible 8
Secteur principal: 42.9% Technologie
Bêta pondéré: 1.45 sensibilité au marché
Plan d’exposition: 71% investi 30% de liquidités · équilibrée
Vous êtes à: 100% investi 0% de liquidités

Scores par composante

Diversification94
Équilibre du risque93
Qualité61
Signal53
Tendance31
Contexte de marché0

Une composante affiche « pas de données » quand le moteur manque de preuves pour elle : c’est signalé, pas deviné.

Quoi regarder en premier

À surveiller Un secteur domine
Technologie représente 42.9% de la valeur investie. Quand un secteur pèse autant, un seul thème macro détermine l’essentiel du résultat.
Priorité Le plan d’exposition privilégie un coussin de liquidités
Compte tenu des preuves actuelles de signal, de tendance et de concentration, le plan vise environ 70.5% investi et 29.5% de liquidités, déployés à un rythme progressif.
À surveiller Le score pondéré des positions est bas
Le score pondéré par la valeur sur l’ensemble des positions est de 0.13. Le mix s’appuie sur des titres aux lectures faibles.
À surveiller Preuves factorielles limitées
Les preuves factorielles manquent pour 100.0% de la valeur investie, ce qui limite le contexte prospectif que le moteur peut soutenir.
À surveiller La confiance prospective est limitée
La confiance de lentille est en moyenne de 55.1%. Considérez les composantes tendance et contexte de marché comme provisoires.
Priorité Positions importantes aux lectures faibles
NVDA, GOOGL pèsent lourd avec des scores de position bas. Ce sont elles qui tirent le plus le score composite vers le bas.

Positions

Ticker	Secteur	Valeur	Poids	Signal	Score	Profil
AAPL	Technologie	10,000	14.3%	ACHETER	6.20	cœur
MSFT	Technologie	10,000	14.3%	CONSERVER	1.36	cœur
GOOGL	Services de communication	10,000	14.3%	CONSERVER	-1.80	redressement
AMZN	Consommation cyclique	10,000	14.3%	CONSERVER	-0.98	bêta élevé
NVDA	Technologie	10,000	14.3%	VENDRE	-4.47	bêta élevé
META	Services de communication	10,000	14.3%	CONSERVER	0.60	cœur
TSLA	Consommation cyclique	10,000	14.3%	CONSERVER	0.02	bêta élevé

Limites des preuves :

Données de qualité du dividende manquantes pour une partie du portefeuille
Faible confiance dans la classification du type d’action pour une partie du portefeuille
Preuves factorielles propres à la lentille manquantes pour une grande partie du portefeuille
La faible confiance dans les preuves factorielles réduit la fiabilité prospective

POST /evaluate

Chaque chiffre ci-dessus provient d’un seul appel à l’API.

Cette page est le JSON ci-dessous, mis en forme. Construisez la même chose dans un tableau de bord, un outil pour conseillers ou un agent IA. Même moteur sur toutes les offres, cinq évaluations gratuites par mois avec une clé API.

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Afficher la réponse brute

{
    "ok": true,
    "evaluation": {
        "engine_version": "2026-03-07-v5",
        "score": 63,
        "health_score": 63,
        "status": "Neutral",
        "status_key": "neutral",
        "count": 7,
        "weighted_score": 0.13000000000000000444089209850062616169452667236328125,
        "max_position_weight": 14.28999999999999914734871708787977695465087890625,
        "max_position_ticker": "AAPL",
        "effective_positions": 7,
        "weighted_beta": 1.4499999999999999555910790149937383830547332763671875,
        "signal_mix": {
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            "hold": 71.400000000000005684341886080801486968994140625,
            "sell": 14.300000000000000710542735760100185871124267578125
        },
        "trend_alignment_pct": 14.300000000000000710542735760100185871124267578125,
        "trend_negative_pct": 42.89999999999999857891452847979962825775146484375,
        "weighted_grade_score": 4.5,
        "weighted_dividend_score": 3.470000000000000195399252334027551114559173583984375,
        "top_sector": "Technology",
        "top_sector_weight": 42.89999999999999857891452847979962825775146484375,
        "score_components": {
            "signal": 52.7000000000000028421709430404007434844970703125,
            "diversification": 93.900000000000005684341886080801486968994140625,
            "risk": 93.2000000000000028421709430404007434844970703125,
            "quality": 60.7999999999999971578290569595992565155029296875,
            "trend": 31.39999999999999857891452847979962825775146484375,
            "macro": 0.200000000000000011102230246251565404236316680908203125
        },
        "trajectory": {
            "direction": "deteriorating",
            "confidence": 27.199999999999999289457264239899814128875732421875,
            "summary": "Negative signal concentration or weakening trend"
        },
        "context_alignment": {
            "score": 0.200000000000000011102230246251565404236316680908203125,
            "coverage_pct": 100,
            "matched_weight_pct": 100,
            "top_sector_view": null
        },
        "forward_confidence": 55.10000000000000142108547152020037174224853515625,
        "exposure_plan": {
            "target_invested_pct": 70.5,
            "target_cash_pct": 29.5,
            "min_invested_pct": 57.60000000000000142108547152020037174224853515625,
            "max_invested_pct": 83.400000000000005684341886080801486968994140625,
            "min_cash_pct": 16.60000000000000142108547152020037174224853515625,
            "max_cash_pct": 42.39999999999999857891452847979962825775146484375,
            "base_invested_pct": 72,
            "stance": "balanced",
            "deployment_speed": "gradual",
            "confidence": 57.10000000000000142108547152020037174224853515625,
            "market_regime_score": 50,
            "market_regime_code": "",
            "reason_codes": [
                "negative_trend_pressure",
                "low_forward_confidence"
            ],
            "components": {
                "market_adjustment": 0,
                "signal_adjustment": 0.729999999999999982236431605997495353221893310546875,
                "trend_adjustment": -2.859999999999999875655021241982467472553253173828125,
                "sell_penalty": 0,
                "concentration_penalty": 0
            }
        },
        "holding_analysis": [
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                "weight_pct": 14.300000000000000710542735760100185871124267578125,
                "score": 6.20000000000000017763568394002504646778106689453125,
                "signal": "BUY",
                "sector": "Technology",
                "profile": "core",
                "lens": "core_quality",
                "classification_confidence": 28,
                "classification_quality": "weak",
                "classification_ambiguous": false,
                "classification_reason_codes": [
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                "factor_evidence_confidence": 0,
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                "factor_match_count": 0,
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                "factor_matched_factors": [],
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            },
            {
                "ticker": "MSFT",
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                "score": 1.3600000000000000976996261670137755572795867919921875,
                "signal": "HOLD",
                "sector": "Technology",
                "profile": "core",
                "lens": "core_quality",
                "classification_confidence": 28,
                "classification_quality": "weak",
                "classification_ambiguous": false,
                "classification_reason_codes": [
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                ],
                "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,
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                "lens_confidence": 28
            },
            {
                "ticker": "GOOGL",
                "weight_pct": 14.300000000000000710542735760100185871124267578125,
                "score": -1.8000000000000000444089209850062616169452667236328125,
                "signal": "HOLD",
                "sector": "Communication Services",
                "profile": "turnaround",
                "lens": "recovery",
                "classification_confidence": 68,
                "classification_quality": "usable",
                "classification_ambiguous": false,
                "classification_reason_codes": [
                    "negative_medium_score"
                ],
                "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": 68
            },
            {
                "ticker": "AMZN",
                "weight_pct": 14.300000000000000710542735760100185871124267578125,
                "score": -0.979999999999999982236431605997495353221893310546875,
                "signal": "HOLD",
                "sector": "Consumer Cyclical",
                "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
            },
            {
                "ticker": "NVDA",
                "weight_pct": 14.300000000000000710542735760100185871124267578125,
                "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": [
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                ],
                "factor_evidence_confidence": 0,
                "factor_evidence_score": null,
                "factor_match_count": 0,
                "factor_required_count": 5,
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                "factor_matched_factors": [],
                "top_factor": null,
                "top_factor_direction": null,
                "lens_confidence": 78
            },
            {
                "ticker": "META",
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                "score": 0.59999999999999997779553950749686919152736663818359375,
                "signal": "HOLD",
                "sector": "Communication Services",
                "profile": "core",
                "lens": "core_quality",
                "classification_confidence": 28,
                "classification_quality": "weak",
                "classification_ambiguous": false,
                "classification_reason_codes": [
                    "fallback_core"
                ],
                "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": 28
            },
            {
                "ticker": "TSLA",
                "weight_pct": 14.300000000000000710542735760100185871124267578125,
                "score": 0.0200000000000000004163336342344337026588618755340576171875,
                "signal": "HOLD",
                "sector": "Consumer Cyclical",
                "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": {
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            "grade_pct": 100,
            "dividend_pct": 71.400000000000005684341886080801486968994140625,
            "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": {
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                "high_beta": 42.89999999999999857891452847979962825775146484375,
                "turnaround": 14.300000000000000710542735760100185871124267578125
            },
            "lens_mix": {
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            },
            "classification": {
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                "quality": "weak",
                "low_confidence_weight_pct": 42.89999999999999857891452847979962825775146484375,
                "ambiguous_weight_pct": 0,
                "weak_count": 3,
                "low_confidence_tickers": [
                    "AAPL",
                    "MSFT",
                    "META"
                ]
            },
            "factor_evidence": {
                "avg_confidence": 0,
                "quality": "weak",
                "low_confidence_weight_pct": 100,
                "missing_weight_pct": 100,
                "aligned_weight_pct": 0,
                "avg_lens_confidence": 55.10000000000000142108547152020037174224853515625
            },
            "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 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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                "id": "weighted_score",
                "value": 0.13000000000000000444089209850062616169452667236328125,
                "tone": "risk",
                "status_key": "neutral"
            },
            {
                "id": "target_invested_pct",
                "value": 70.5,
                "cash_pct": 29.5,
                "stance": "balanced",
                "confidence": 57.10000000000000142108547152020037174224853515625,
                "tone": "risk"
            },
            {
                "id": "effective_positions",
                "value": 7,
                "tone": "warn"
            },
            {
                "id": "largest_position",
                "value": 14.300000000000000710542735760100185871124267578125,
                "ticker": "AAPL",
                "tone": "good"
            },
            {
                "id": "top_sector",
                "value": 42.89999999999999857891452847979962825775146484375,
                "sector": "Technology",
                "tone": "warn"
            },
            {
                "id": "signal_mix",
                "buy": 14.300000000000000710542735760100185871124267578125,
                "hold": 71.400000000000005684341886080801486968994140625,
                "sell": 14.300000000000000710542735760100185871124267578125,
                "tone": "good"
            },
            {
                "id": "portfolio_trajectory",
                "value": "deteriorating",
                "tone": "risk",
                "confidence": 27.199999999999999289457264239899814128875732421875
            },
            {
                "id": "weighted_beta",
                "value": 1.4499999999999999555910790149937383830547332763671875,
                "tone": "risk"
            },
            {
                "id": "macro_alignment",
                "value": 0.200000000000000011102230246251565404236316680908203125,
                "tone": "risk"
            },
            {
                "id": "lens_confidence",
                "value": 55.10000000000000142108547152020037174224853515625,
                "tone": "risk"
            }
        ],
        "suggestions": [
            {
                "tone": "warn",
                "code": "diversify_sector",
                "sector": "Technology",
                "weight_pct": 42.89999999999999857891452847979962825775146484375
            },
            {
                "tone": "risk",
                "code": "hold_higher_cash_buffer",
                "cash_pct": 29.5,
                "invested_pct": 70.5,
                "deployment_speed": "gradual"
            },
            {
                "tone": "warn",
                "code": "lift_quality_score",
                "weighted_score": 0.13000000000000000444089209850062616169452667236328125
            },
            {
                "tone": "warn",
                "code": "expand_factor_coverage",
                "missing_weight_pct": 100
            },
            {
                "tone": "warn",
                "code": "lower_forward_confidence",
                "lens_confidence": 55.10000000000000142108547152020037174224853515625
            },
            {
                "tone": "risk",
                "code": "review_weak_positions",
                "tickers": [
                    "NVDA",
                    "GOOGL"
                ]
            }
        ],
        "portfolio_input": {
            "cash_balance": 0,
            "holdings_value": 70000,
            "total_value": 70000,
            "cash_pct": 0,
            "invested_pct": 100,
            "missing_tickers": []
        }
    }
}

Les résultats de PORTIQA constituent une analyse quantitative fournie à titre informatif uniquement et ne constituent pas un conseil en investissement. Voir l’avertissement financier.

Autres portefeuilles d’exemple

Position unique · 1 position

Les Magnificent 7 en portefeuille.

Le portefeuille

Preuves contrastées.

Scores par composante

Quoi regarder en premier

Positions

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