Direktvergleich
Financial TimesvsHandelsblatt
Financial Times (37.4% Genauigkeit) vs Handelsblatt (37.5% Genauigkeit) — detaillierter Vergleich der Marktprognose-Zuverlässigkeit.
Beide Quellen zeigen ähnliche Genauigkeit
Basierend auf 503 bzw. 104 ausgewerteten Prognosen
Genauigkeit
37.4%vs37.5%
Ausgewertete Prognosen
503vs104
Analysierte Artikel
0vs0
Durchschn. Relevanz
-vs-
Stimmungs- & Tendenzanalyse
Wie bullisch oder bärisch die Prognosen jeder Quelle tendenziell sind.
Stimmungsverteilung
Financial Times
Durchschn. Stimmung: 0.31
Bullisch 64%Neutral 5%Bärisch 32%
Handelsblatt
Durchschn. Stimmung: 0.26
Bullisch 58%Neutral 11%Bärisch 31%
Genauigkeit in gemeinsamen Märkten
Genauigkeitsvergleich für Märkte, die sowohl Financial Times als auch Handelsblatt abdecken.
Genauigkeit nach Marktkontext
Genauigkeit im Zeitverlauf
90-Tage-Genauigkeitstrend beider Quellen übereinander dargestellt.
90-Tage-Genauigkeitstrend
Marktkontext-Abdeckung
| Genauigkeit nach Markt | Financial Times | Handelsblatt |
|---|---|---|
| Asia markets | 1 (0%) | — |
| Asian equities | 2 (0%) | — |
| Asian markets | 2 (0%) | — |
| Asian stocks | 2 (0%) | — |
| Australia | 1 (0%) | — |
| Bitcoin | 12 (2%) | 3 (3%) |
| China | 1 (0%) | — |
| China stocks | 1 (0%) | — |
| DAX | 9 (2%) | 37 (33%) |
| Euro Bonds | 1 (0%) | — |
| European stocks | 1 (0%) | — |
| India | 1 (0%) | — |
| India's banking sector | 1 (0%) | — |
| India's economic growth | 1 (0%) | — |
| India's economy | 1 (0%) | — |
| India's export market | 1 (0%) | — |
| Japan equities | 1 (0%) | — |
| Oil | 1 (0%) | — |
| Thailand's manufacturing and investment appeal | 1 (0%) | — |
| UK markets | 1 (0%) | — |
| USA | 106 (19%) | 15 (13%) |
| credit markets | 1 (0%) | — |
| cryptocurrencies (Crypto) | 3 (1%) | — |
| emerging markets | 5 (1%) | — |
| emerging-market assets | 1 (0%) | — |
| emerging-market currencies and stocks | 1 (0%) | — |
| emerging-market stocks | 1 (0%) | — |
| energy ETFs | 1 (0%) | — |
| global markets | 75 (14%) | 12 (11%) |
| other | 5 (1%) | — |
| other (AI investment) | 1 (0%) | — |
| other (ASX Ltd.) | 2 (0%) | — |
| other (Adidas AG) | 1 (0%) | — |
| other (Adidas stock) | — | 2 (2%) |
| other (Adidas) | — | 1 (1%) |
| other (African dollar bonds) | 1 (0%) | — |
| other (Airbnb) | — | 1 (1%) |
| other (Allianz) | 1 (0%) | — |
| other (Asian equities) | 1 (0%) | — |
| other (Asian junk bonds) | 1 (0%) | — |
| other (Asian markets) | — | 1 (1%) |
| other (AstraZeneca) | 1 (0%) | — |
| other (Australia corporate earnings) | 1 (0%) | — |
| other (Australian dollar) | 2 (0%) | — |
| other (Australian stocks) | 1 (0%) | — |
| other (Bank of England interest rate expectations) | 1 (0%) | — |
| other (Beiersdorf AG) | 1 (0%) | — |
| other (Beiersdorf) | — | 1 (1%) |
| other (Blue Owl Capital Inc.) | 1 (0%) | — |
| other (Brightline bonds) | 1 (0%) | — |
| other (British Airways/IAG SA) | 1 (0%) | — |
| other (British pound) | 1 (0%) | — |
| other (Canadian energy stocks) | 1 (0%) | — |
| other (Chile's monetary policy and economic outlook) | 1 (0%) | — |
| other (China stocks) | 1 (0%) | — |
| other (China's electric-vehicle sector) | 1 (0%) | — |
| other (Chinese AI stocks) | 1 (0%) | — |
| other (Chinese Tech Stocks) | 1 (0%) | — |
| other (Chinese Yuan) | 1 (0%) | — |
| other (Chinese assets) | 1 (0%) | — |
| other (Chinese consumer stocks) | 1 (0%) | — |
| other (Chinese equities) | 1 (0%) | — |
| other (Chinese government bonds) | 1 (0%) | — |
| other (Chinese stocks) | 2 (0%) | — |
| other (Citigroup Inc.) | 1 (0%) | — |
| other (Commerzbank) | — | 1 (1%) |
| other (Copper market) | 1 (0%) | — |
| other (Coreweave) | — | 1 (1%) |
| other (Covestro) | — | 2 (2%) |
| other (Czech monetary policy) | 2 (0%) | — |
| other (Delta Electronics Thailand Pcl) | 1 (0%) | — |
| other (Dubai stocks) | 1 (0%) | — |
| other (Ebay) | — | 1 (1%) |
| other (Egyptian stock market) | 1 (0%) | — |
| other (Eli Lilly & Co. sales forecast) | 1 (0%) | — |
| other (Emerging Markets) | 1 (0%) | — |
| other (Emerging-market stocks) | 1 (0%) | — |
| other (Enel stock) | — | 1 (1%) |
| other (Europe's economy) | 1 (0%) | — |
| other (European and Japanese stocks) | 1 (0%) | — |
| other (European banks) | 1 (0%) | — |
| other (European construction industry) | — | 2 (2%) |
| other (European junk-rated retail bonds) | 1 (0%) | — |
| other (European natural gas market) | 1 (0%) | — |
| other (European oil and gas stocks) | 1 (0%) | — |
| other (European stocks) | 1 (0%) | 1 (1%) |
| other (FTSE 100) | 2 (0%) | — |
| other (Ferrari NV) | 2 (0%) | — |
| other (Finnish pension funds' stock holdings) | 1 (0%) | — |
| other (France's economy) | 1 (0%) | — |
| other (Generac's market) | 1 (0%) | — |
| other (German Economy) | 1 (0%) | — |
| other (German economy) | — | 2 (2%) |
| other (Germany's economy) | — | 1 (1%) |
| other (Global Weight-Loss Drug Market) | 1 (0%) | — |
| other (Gold market) | 5 (1%) | 1 (1%) |
| other (Gold) | 1 (0%) | — |
| other (Hong Kong economy) | 1 (0%) | — |
| other (Hong Kong luxury home market) | 1 (0%) | — |
| other (Hong Kong property market) | 1 (0%) | — |
| other (India stock market) | 2 (0%) | — |
| other (India's M&A market) | 1 (0%) | — |
| other (India's benchmark stock index) | 1 (0%) | — |
| other (India's economic growth prospects) | 1 (0%) | — |
| other (India's financial markets) | — | 1 (1%) |
| other (India's real estate market) | 1 (0%) | — |
| other (India's stock market) | 2 (0%) | — |
| other (Indian IT stocks) | 1 (0%) | — |
| other (Indian Rupee and foreign-exchange reserves) | 1 (0%) | — |
| other (Indian bonds) | 2 (0%) | — |
| other (Indian domestic shares) | 1 (0%) | — |
| other (Indian equities) | 1 (0%) | — |
| other (Indian imports of Russian oil) | 1 (0%) | — |
| other (Indian shares) | 1 (0%) | — |
| other (Indian small caps) | 1 (0%) | — |
| other (Indian stock market) | 1 (0%) | — |
| other (Indian stocks and Rupee) | 1 (0%) | — |
| other (Indian stocks) | 2 (0%) | — |
| other (Indonesia market) | 1 (0%) | — |
| other (Indonesia's sovereign credit profile) | 1 (0%) | — |
| other (Indonesian bonds) | 1 (0%) | — |
| other (Indonesian corporates) | 2 (0%) | — |
| other (Indonesian markets) | 1 (0%) | — |
| other (Indonesian stocks) | 1 (0%) | — |
| other (Intercontinental Hotels Group) | 1 (0%) | — |
| other (Japan bond market) | 1 (0%) | — |
| other (Japan's stock market) | 4 (1%) | 1 (1%) |
| other (Japanese Yen) | 2 (0%) | — |
| other (Japanese assets) | 1 (0%) | — |
| other (Japanese bonds) | 1 (0%) | — |
| other (Japanese debt market) | 2 (0%) | — |
| other (Japanese equities) | 1 (0%) | — |
| other (Japanese government bonds) | 5 (1%) | — |
| other (Japanese markets) | — | 2 (2%) |
| other (Japanese stock market) | 1 (0%) | 1 (1%) |
| other (Japanese stocks) | 7 (1%) | — |
| other (Japanese yen) | 2 (0%) | — |
| other (Kering/Gucci) | — | 1 (1%) |
| other (Knorr-Bremse) | — | 1 (1%) |
| other (Malaysian ringgit) | 2 (0%) | — |
| other (Mattel Inc.) | 1 (0%) | — |
| other (Mercedes stock) | — | 1 (1%) |
| other (Merck stock) | — | 1 (1%) |
| other (MongoDB) | 1 (0%) | — |
| other (Nestlé SA) | 1 (0%) | — |
| other (Netflix) | 1 (0%) | — |
| other (North Sea crude market) | 1 (0%) | — |
| other (Novo Nordisk A/S shares) | 1 (0%) | — |
| other (Novo Nordisk stock) | — | 1 (1%) |
| other (Oil and metals markets) | 1 (0%) | — |
| other (Oil market) | 2 (0%) | — |
| other (Omani stocks) | 2 (0%) | — |
| other (Palm Oil) | 2 (0%) | — |
| other (Panasonic Holdings Corp.) | 3 (1%) | — |
| other (Peru's economy) | 1 (0%) | — |
| other (Philippine Peso) | 1 (0%) | — |
| other (Philippine peso bonds) | 1 (0%) | — |
| other (Puma) | — | 1 (1%) |
| other (RELX Plc) | 2 (0%) | — |
| other (Rolls-Royce Holdings Plc) | 2 (0%) | — |
| other (SAP) | — | 1 (1%) |
| other (Saudi Arabian equities) | 1 (0%) | — |
| other (Shanghai stock market) | — | 1 (1%) |
| other (Siemens Energy) | — | 1 (1%) |
| other (Silver market) | 2 (0%) | — |
| other (Singapore local stocks) | 1 (0%) | — |
| other (South Africa's rand) | 1 (0%) | — |
| other (South African Rand) | 2 (0%) | — |
| other (South African bonds) | 1 (0%) | — |
| other (South African equity sectors) | 1 (0%) | — |
| other (South African government bonds) | 1 (0%) | — |
| other (South African stocks) | 1 (0%) | — |
| other (South Korea's equity benchmark) | 1 (0%) | — |
| other (South Korean bond market) | 2 (0%) | — |
| other (South Korean equities) | 2 (0%) | — |
| other (South Korean stocks) | 2 (0%) | — |
| other (Soybean market) | 1 (0%) | — |
| other (Soybeans market) | 1 (0%) | — |
| other (Suzano SA shares) | 1 (0%) | — |
| other (Swiss Bond Market) | 1 (0%) | — |
| other (Taiwan stocks) | 1 (0%) | — |
| other (Thailand's stock market and currency) | 1 (0%) | — |
| other (Toronto housing market) | 1 (0%) | — |
| other (Treasury market) | 1 (0%) | — |
| other (Turkey's economic outlook) | 1 (0%) | — |
| other (Turkish bank stocks) | 1 (0%) | — |
| other (UK Stocks) | 1 (0%) | — |
| other (UK bond market) | 2 (0%) | — |
| other (UK bonds) | 2 (0%) | — |
| other (UK construction industry) | 1 (0%) | — |
| other (UK economy) | 1 (0%) | — |
| other (UK housing market) | 1 (0%) | — |
| other (UK market) | 2 (0%) | — |
| other (UK markets) | 3 (1%) | — |
| other (UK property market) | 1 (0%) | — |
| other (US Dollar) | 8 (1%) | — |
| other (US Natural Gas) | 2 (0%) | — |
| other (US energy storage market) | 1 (0%) | — |
| other (US oil market) | 4 (1%) | — |
| other (US soybean futures) | 1 (0%) | — |
| other (US soybean oil market) | 2 (0%) | — |
| other (United Arab Emirates banks) | 1 (0%) | — |
| other (Venezuelan economy) | 1 (0%) | — |
| other (Venezuelan global bonds) | 1 (0%) | — |
| other (Volkswagen Group in China) | — | 1 (1%) |
| other (Walmart's earnings forecast) | 1 (0%) | — |
| other (Yen currency market) | 1 (0%) | — |
| other (Yuan currency market) | 3 (1%) | — |
| other (Yuan vs Indian Rupee) | 1 (0%) | — |
| other (agriculture economy) | 4 (1%) | — |
| other (agriculture machinery market) | 1 (0%) | — |
| other (bond markets) | 1 (0%) | — |
| other (carbon credits market) | 1 (0%) | — |
| other (companies in the physical world like miners, power producers, and industrial firms) | 1 (0%) | — |
| other (copper market) | 4 (1%) | — |
| other (credit markets around software) | 1 (0%) | — |
| other (credit markets) | 2 (0%) | — |
| other (currency market) | 1 (0%) | — |
| other (economic growth) | — | 1 (1%) |
| other (electric-vehicle market) | 1 (0%) | — |
| other (emerging markets) | 1 (0%) | 1 (1%) |
| other (emerging-market ETFs) | 1 (0%) | — |
| other (emerging-market debt) | 1 (0%) | — |
| other (emerging-market equities and currencies) | 1 (0%) | — |
| other (emerging-market equities) | 1 (0%) | — |
| other (emerging-market stocks) | 1 (0%) | — |
| other (global Brent oil market) | 1 (0%) | — |
| other (global smartphone market) | 1 (0%) | — |
| other (gold market) | 1 (0%) | — |
| other (high quality large cap stocks) | 1 (0%) | — |
| other (local debt markets in Mexico) | 1 (0%) | — |
| other (memory chip market) | 2 (0%) | — |
| other (municipal bonds) | 2 (0%) | — |
| other (oil and metals markets) | 1 (0%) | — |
| other (oil market) | 6 (1%) | — |
| other (oil-company stocks) | 1 (0%) | — |
| other (potential IPOs of companies like OpenAI, Anthropic, or SpaceX) | — | 1 (1%) |
| other (precious metals) | 1 (0%) | — |
| other (private credit firms) | 1 (0%) | — |
| other (private credit markets) | 1 (0%) | — |
| other (private credit stocks) | 1 (0%) | — |
| other (private debt market) | 1 (0%) | — |
| other (private markets) | 1 (0%) | — |
| other (real estate market) | — | 2 (2%) |
| other (real estate sector in India) | 1 (0%) | — |
| other (retail sector) | — | 1 (1%) |
| other (robotics sector) | — | 1 (1%) |
| other (smartphone market) | 1 (0%) | — |
| other (soybean oil market) | 3 (1%) | — |
| other (stock market with focus on AI-related stocks) | — | 1 (1%) |
| other (sugar market) | 1 (0%) | — |
| other (trucking market) | 1 (0%) | — |
| technology stocks (Tech) | 44 (8%) | 5 (4%) |
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Genauigkeitsmetriken
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Häufig gestellte Fragen
Was ist zuverlässiger: Financial Times oder Handelsblatt?▼
Sowohl Financial Times (37.4%) als auch Handelsblatt (37.5%) zeigen ähnliche Prognosegenauigkeit. Die beste Wahl hängt vom jeweiligen Marktkontext ab.
Wie werden diese Vergleiche berechnet?▼
Wir extrahieren Marktprognosen aus Nachrichtenartikeln mithilfe von KI und bewerten dann jede Vorhersage anhand tatsächlicher Marktdaten. Quellen werden nach Gesamtgenauigkeit, Stimmungsverteilung und Leistung pro Marktkontext verglichen.
Welche Märkte decken Financial Times und Handelsblatt gemeinsam ab?▼
Sie teilen 10 Marktkontexte: Bitcoin, DAX, USA, global markets, other (European stocks), other (Gold market), other (Japan's stock market), other (Japanese stock market), other (emerging markets), technology stocks (Tech). Jede Quelle kann auch zusätzliche Märkte unabhängig abdecken.
Unsere Methodik
Wir verwenden KI, um Marktprognosen aus Nachrichtenartikeln zu extrahieren und bewerten dann jede Vorhersage anhand tatsächlicher Marktdaten mit yfinance. Nur Quellen mit mindestens 3 ausgewerteten Prognosen werden gerankt.