Direktvergleich
CNBCvswallstreet-online Nachrichten
CNBC (38.6 % Trefferquote) vs. wallstreet-online Nachrichten (36.2 % Trefferquote): wie oft der Schlagzeilen-Ton jeder Quelle zur späteren Kursbewegung passte.
Keine schnitt gegen den Zufall besser ab als die andere
Basierend auf 3893 bzw. 1158 geprüften Schlagzeilen
Trefferquote
38.6%vs36.2%
Geprüfte Meldungen
3,893vs1,158
Analysierte Artikel
1,934vs649
Durchschn. Relevanz
-vs-
Stimmungs- & Tendenzanalyse
Wie bullisch oder bärisch die Schlagzeilen jeder Quelle tendenziell sind.
Stimmungsverteilung
CNBC
Durchschn. Stimmung: 0.02
Bullisch 51%Neutral 5%Bärisch 45%
wallstreet-online Nachrichten
Durchschn. Stimmung: 0.00
Bullisch 47%Neutral 3%Bärisch 50%
Marktkontext-Abdeckung
| Trefferquote nach Markt | CNBC | wallstreet-online Nachrichten |
|---|---|---|
| ASOS | — | 1 (0%) |
| AST SpaceMobile | 1 (0%) | — |
| AT&S | — | 1 (0%) |
| AT&T | 1 (0%) | 1 (0%) |
| AXA | — | 1 (0%) |
| Adobe | — | 1 (0%) |
| Adobe, single software | 1 (0%) | — |
| Affirm Holdings | 1 (0%) | — |
| Airbus | — | 2 (0%) |
| Airline | 1 (0%) | — |
| Aixtron | — | 1 (0%) |
| Alibaba | — | 3 (1%) |
| Alibaba/Chinese Tech | — | 1 (0%) |
| Allianz | — | 2 (0%) |
| Alphabet | — | 1 (0%) |
| Aluminum | 2 (0%) | — |
| Amazon | 4 (0%) | 2 (0%) |
| American Express | — | 1 (0%) |
| AppLovin | — | 1 (0%) |
| Apple | 2 (0%) | 3 (1%) |
| Asian stocks | 51 (3%) | 3 (1%) |
| Australian stocks | 6 (0%) | 3 (1%) |
| Auto1 Group | — | 1 (0%) |
| Automotive industry | 1 (0%) | — |
| Autonomous driving | 1 (0%) | — |
| Aviation/Transport | — | 1 (0%) |
| BMW | — | 1 (0%) |
| BNB | 1 (0%) | 1 (0%) |
| BYD | — | 3 (1%) |
| Baidu | 1 (0%) | — |
| Bank | — | 1 (0%) |
| Bayer | — | 1 (0%) |
| Berkshire Hathaway | 1 (0%) | — |
| BioNTech | — | 2 (0%) |
| Biogen | 1 (0%) | 1 (0%) |
| Biotech | 1 (0%) | 1 (0%) |
| Bitcoin | 25 (2%) | 20 (3%) |
| BlackRock | — | 1 (0%) |
| Block Inc | 1 (0%) | — |
| Booking Holdings | 1 (0%) | — |
| Brazilian | 2 (0%) | 1 (0%) |
| Brazilian Real | — | 2 (0%) |
| Brazilian real | 1 (0%) | — |
| Bulgarian | — | 1 (0%) |
| CVS Health, healthcare/managed care | 1 (0%) | — |
| Canadian markets | — | 1 (0%) |
| Cannabis | — | 2 (0%) |
| Carrefour | — | 1 (0%) |
| ChargePoint | 1 (0%) | — |
| China industrial profits | 1 (0%) | — |
| China trade data | 1 (0%) | — |
| Chinese biopharma | 1 (0%) | — |
| Chinese economy | 1 (0%) | — |
| Chinese solar sector | — | 1 (0%) |
| Chipotle Mexican Grill | 1 (0%) | — |
| Coca-Cola | — | 1 (0%) |
| Coinbase | 1 (0%) | — |
| Commodities | 1 (0%) | 1 (0%) |
| Copper | 3 (0%) | 2 (0%) |
| CoreWeave | 4 (0%) | — |
| D-Wave | — | 1 (0%) |
| DAX | 7 (0%) | 54 (8%) |
| DHL Group | — | 1 (0%) |
| Daimler Truck | — | 1 (0%) |
| Dell Technologies | 2 (0%) | 1 (0%) |
| Deutsche Bank | — | 2 (0%) |
| Deutsche Telekom | — | 3 (1%) |
| EUR/USD | 3 (0%) | 4 (1%) |
| Eli Lilly | 1 (0%) | — |
| EssilorLuxottica | — | 1 (0%) |
| Estée Lauder | — | 1 (0%) |
| Ethereum | — | 1 (0%) |
| Etsy | 1 (0%) | — |
| European natural gas | — | 1 (0%) |
| European stocks | 57 (3%) | 39 (6%) |
| Evotec | — | 1 (0%) |
| Expedia Group | 1 (0%) | — |
| Ferrari | 1 (0%) | — |
| Ford Motor Company | 1 (0%) | — |
| Fortinet | 1 (0%) | 1 (0%) |
| French government bonds | 1 (0%) | 2 (0%) |
| GBP/USD | 1 (0%) | — |
| Generac Holdings | 1 (0%) | — |
| General Motors | — | 1 (0%) |
| Gold | 34 (2%) | 28 (4%) |
| HP | — | 1 (0%) |
| Hanwha Ocean | 1 (0%) | — |
| Hapag-Lloyd | — | 1 (0%) |
| HelloFresh | — | 1 (0%) |
| Hensoldt AG | — | 1 (0%) |
| Hewlett Packard Enterprise | 1 (0%) | — |
| Homebuilder | 1 (0%) | — |
| Honda | — | 1 (0%) |
| Honeywell Aerospace | — | 1 (0%) |
| Hungarian markets | — | 1 (0%) |
| Hybe | 1 (0%) | — |
| IBM | — | 1 (0%) |
| IMAX | — | 1 (0%) |
| Iambic Therapeutics | — | 1 (0%) |
| Iceland EU vote | 1 (0%) | — |
| Indian stocks | 23 (1%) | 3 (1%) |
| IonQ | — | 1 (0%) |
| Iranian Rial | — | 1 (0%) |
| Jakarta Stock Exchange | — | 1 (0%) |
| Japanese stocks | 20 (1%) | 2 (0%) |
| JetBlue | 1 (0%) | — |
| Johnson & Johnson | 1 (0%) | — |
| Korean | 1 (0%) | — |
| Kraft Heinz | — | 1 (0%) |
| Kupfermarkt | — | 1 (0%) |
| Leonardo | — | 1 (0%) |
| Lithium | 1 (0%) | 1 (0%) |
| Lockheed Martin | — | 2 (0%) |
| Lucid Motors | 1 (0%) | — |
| Lufthansa stock, aviation sector | — | 1 (0%) |
| Luxury sector | 2 (0%) | — |
| MGM Resorts | 1 (0%) | — |
| Madison Air IPO | 1 (0%) | — |
| Mastercard | 1 (0%) | — |
| MaxLinear | 1 (0%) | — |
| Mensch und Maschine | — | 1 (0%) |
| Meta Platforms | 2 (0%) | 2 (0%) |
| Micron | — | 1 (0%) |
| Micron Technology | 1 (0%) | — |
| Microsoft | 1 (0%) | — |
| MiniMax | — | 1 (0%) |
| Moderna | — | 1 (0%) |
| Municipal Bonds | 1 (0%) | — |
| NASDAQ | 48 (3%) | 16 (3%) |
| Nanexa | — | 1 (0%) |
| Nebius Group | — | 2 (0%) |
| NetApp | — | 1 (0%) |
| Netflix | 2 (0%) | 2 (0%) |
| New Zealand exporters | 1 (0%) | — |
| NextDC | — | 1 (0%) |
| Nike | 3 (0%) | 2 (0%) |
| Nordex | — | 1 (0%) |
| Nordex AG | — | 1 (0%) |
| Novo Nordisk | 2 (0%) | 2 (0%) |
| Novo Nordisk, pharmaceutical | — | 1 (0%) |
| Nscale IPO | — | 1 (0%) |
| Nvidia | 1 (0%) | — |
| Oil | 306 (18%) | 96 (15%) |
| Oracle | 2 (0%) | 2 (0%) |
| Palantir | 2 (0%) | 1 (0%) |
| Palantir Technologies | 1 (0%) | — |
| Palantir stock, analyst rating | — | 1 (0%) |
| Palfinger | — | 2 (0%) |
| Palo Alto Networks | — | 1 (0%) |
| Paramount/Warner Bros merger | 1 (0%) | — |
| PayPal | — | 2 (0%) |
| Peloton | 1 (0%) | — |
| Penguin Solutions | 1 (0%) | — |
| PepsiCo | 1 (0%) | — |
| Pharmaceutical | 1 (0%) | — |
| Pharmaceutical ETF | 1 (0%) | — |
| Pop Mart | 1 (0%) | — |
| Private Credit | 1 (0%) | — |
| Procter & Gamble | — | 2 (0%) |
| Puma SE | — | 1 (0%) |
| Qantas | 1 (0%) | — |
| RWE | — | 1 (0%) |
| Redcare Pharmacy | — | 1 (0%) |
| Refiner | 1 (0%) | — |
| Renk AG | — | 2 (0%) |
| Restaurant Brands International | 1 (0%) | — |
| Restaurant industry | 1 (0%) | — |
| Rheinmetall | — | 1 (0%) |
| Rheinmetall / defense technology | — | 1 (0%) |
| Riot Platforms | 1 (0%) | — |
| Rivian | 2 (0%) | — |
| Rivian stock, EV maker | — | 1 (0%) |
| Robinhood | 2 (0%) | — |
| Roku | 1 (0%) | — |
| Royal Caribbean Cruises | 1 (0%) | — |
| SAP | — | 1 (0%) |
| SK Hynix | 1 (0%) | 1 (0%) |
| Saab AB | — | 1 (0%) |
| Salesforce | 1 (0%) | 1 (0%) |
| Salzgitter AG | — | 1 (0%) |
| Samsung Electronics | 1 (0%) | 2 (0%) |
| Sandisk | — | 1 (0%) |
| Sartorius | — | 1 (0%) |
| Saudi Aramco | 1 (0%) | — |
| Seven & i Holdings | 1 (0%) | — |
| Sherwin-Williams | 1 (0%) | — |
| Shopify-related e-commerce software | — | 1 (0%) |
| Siemens | — | 1 (0%) |
| Siemens AG | — | 1 (0%) |
| Siemens Energy | — | 3 (1%) |
| Silver | 4 (0%) | 11 (2%) |
| SoFi Technologies | 1 (0%) | — |
| SoftBank | — | 1 (0%) |
| South Korean | — | 1 (0%) |
| South Korean rates | 1 (0%) | — |
| South Korean solar | 1 (0%) | 1 (0%) |
| Space sector | — | 1 (0%) |
| SpaceX | — | 1 (0%) |
| SpaceX IPO | 1 (0%) | — |
| Swiss Franc | 2 (0%) | 1 (0%) |
| Taiwan economy | 1 (0%) | — |
| Take-Two Interactive | 1 (0%) | 2 (0%) |
| Tapestry Inc | 1 (0%) | — |
| Target | — | 1 (0%) |
| Target Corp | 1 (0%) | — |
| Technip Energies | — | 1 (0%) |
| Tesla | 2 (0%) | 3 (1%) |
| Thyssenkrupp | — | 1 (0%) |
| Turkish | 1 (0%) | — |
| UK markets | 21 (1%) | 3 (1%) |
| US Banking Sector | 1 (0%) | — |
| US Real Estate | — | 1 (0%) |
| US Soybean | — | 1 (0%) |
| US apartment rents | 1 (0%) | — |
| US mortgage rates | 1 (0%) | — |
| US-China summit expectations | 1 (0%) | — |
| USA | 460 (27%) | 57 (9%) |
| USD | 2 (0%) | — |
| USD/JPY | 15 (1%) | 1 (0%) |
| Uber Technologies, ride-hailing | — | 1 (0%) |
| Union Pacific | 1 (0%) | 1 (0%) |
| Uranium | — | 1 (0%) |
| Utilities sector | 1 (0%) | — |
| Verbio AG | — | 1 (0%) |
| Verizon | — | 1 (0%) |
| Vertiv | — | 1 (0%) |
| Vestas Wind Systems | — | 1 (0%) |
| Vincorion | — | 1 (0%) |
| Visa | 1 (0%) | — |
| Vonovia | — | 2 (0%) |
| Walmart | 1 (0%) | — |
| Wendy's | 2 (0%) | — |
| West Pharma | 1 (0%) | — |
| XRP | — | 5 (1%) |
| Xiaomi | — | 1 (0%) |
| Xpeng | 1 (0%) | 1 (0%) |
| Zebra Technologies | 1 (0%) | — |
| Zinc | — | 2 (0%) |
| biotech | 1 (0%) | — |
| bond | 1 (0%) | — |
| consumer stock/haircare sector | 1 (0%) | — |
| cryptocurrencies (Crypto) | 15 (1%) | 7 (1%) |
| data storage manufacturer | 1 (0%) | — |
| defense industry | 1 (0%) | — |
| general | — | 1 (0%) |
| global markets | 136 (8%) | 15 (2%) |
| home furnishings | 1 (0%) | — |
| memory | 1 (0%) | — |
| natural gas pipeline operators | 1 (0%) | — |
| online retail / e-commerce | — | 1 (0%) |
| prediction markets / Robinhood | 1 (0%) | — |
| restaurant | — | 1 (0%) |
| retail | 1 (0%) | — |
| small-cap | 1 (0%) | — |
| software stock / Salesforce | 1 (0%) | — |
| technology stocks (Tech) | 314 (19%) | 98 (15%) |
| uranium | 1 (0%) | — |
Die heutige Nachrichtenlage – keine Prognose
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Wie oft die Nachrichten richtig lagen
Die Trefferquote jeder Quelle im Vergleich zum Zufall
Häufig gestellte Fragen
Was ist zuverlässiger: CNBC oder wallstreet-online Nachrichten?▼
CNBC (38.6 %) und wallstreet-online Nachrichten (36.2 %) erhalten dasselbe Urteil gegen den Zufall, gemessen ab dem ersten handelbaren Kurs. Eine reine Trefferquote spiegelt vor allem, welche Märkte eine Quelle abdeckt; der Abstand der beiden Quoten allein sagt wenig.
Wie werden diese Vergleiche berechnet?▼
Eine KI ordnet den Tenor jeder Schlagzeile für ihren Markt als steigend, fallend oder seitwärts ein. Ab dem ersten Kurs, zu dem ein Leser hätte handeln können, prüfen wir die Bewegung nach 1, 3 und 7 Tagen und vergleichen die Trefferquote jeder Quelle mit dem Zufall für ihre eigene Mischung (Methode unter /how-reliable-is). Verglichen werden dieses Urteil, die Tenor-Verteilung und die abgedeckten Märkte.
Welche Märkte decken CNBC und wallstreet-online Nachrichten gemeinsam ab?▼
Sie teilen 46 Marktkontexte: AT&T, Amazon, Apple, Asian stocks, Australian stocks, BNB, Biogen, Biotech, Bitcoin, Brazilian, Commodities, Copper, DAX, Dell Technologies, EUR/USD, European stocks, Fortinet, French government bonds, Gold, Indian stocks, Japanese stocks, Lithium, Meta Platforms, NASDAQ, Netflix, Nike, Novo Nordisk, Oil, Oracle, Palantir, SK Hynix, Salesforce, Samsung Electronics, Silver, South Korean solar, Swiss Franc, Take-Two Interactive, Tesla, UK markets, USA, USD/JPY, Union Pacific, Xpeng, cryptocurrencies (Crypto), global markets, technology stocks (Tech). Jede Quelle kann auch zusätzliche Märkte unabhängig abdecken.
Unsere Methodik
Eine KI ordnet den Tenor jedes Artikels für den behandelten Markt als steigend, fallend oder seitwärts ein. Ab dem ersten Kurs, zu dem ein Leser nach der Veröffentlichung hätte handeln können, prüfen wir die Bewegung nach 1, 3 und 7 Tagen. Die Trefferquote einer Quelle wird mit dem Zufall für dieselben Einschätzungen und Ergebnisse innerhalb jedes Marktes verglichen; wer über ruhige oder bewegte Märkte schreibt, gewinnt dadurch nichts. Jeder Abstand hat ein 95-%-Intervall; zeitlich nahe Prüfungen werden in Blöcken von 7 oder 14 Tagen gemeinsam neu gezogen, weil sie Marktbewegungen teilen. Ein Urteil braucht mindestens 300 Prüfungen und muss auch nach der Korrektur für die Zahl der getesteten Quellen (Holm) bestehen. Das beantwortet „Bewegte sich der Markt so?“: eine Trefferquote, keine Rendite. AIamond selbst macht keine Prognosen.