Financial TimesvsFXStreet
Financial Times (37.5 % Trefferquote) vs. FXStreet (36.4 % Trefferquote): wie oft der Schlagzeilen-Ton jeder Quelle zur späteren Kursbewegung passte.
Keine schnitt gegen den Zufall besser ab als die andere
Basierend auf 3149 bzw. 11412 geprüften Schlagzeilen
Trefferquote
Geprüfte Meldungen
Analysierte Artikel
Durchschn. Relevanz
Stimmungs- & Tendenzanalyse
Wie bullisch oder bärisch die Schlagzeilen jeder Quelle tendenziell sind.
Stimmungsverteilung
Financial Times
FXStreet
Marktkontext-Abdeckung
| Trefferquote nach Markt | Financial Times | FXStreet |
|---|---|---|
| AI infrastructure bonds | 1 (0%) | — |
| AMD | — | 1 (0%) |
| APAC FX | — | 2 (0%) |
| ASEAN FX | — | 1 (0%) |
| AUD/JPY | — | 35 (1%) |
| AUD/NZD | — | 5 (0%) |
| AUD/USD | — | 87 (2%) |
| Aluminium | — | 5 (0%) |
| Amazon | — | 2 (0%) |
| Anthropic IPO | 1 (0%) | — |
| Apple | — | 1 (0%) |
| Argentine peso | 1 (0%) | — |
| Asia FX | — | 3 (0%) |
| Asian FX | — | 7 (0%) |
| Asian stocks | 85 (6%) | 65 (1%) |
| Australian stocks | 23 (2%) | 114 (2%) |
| BNB | 3 (0%) | 2 (0%) |
| BRL/USD | — | 3 (0%) |
| Bitcoin | 18 (1%) | 77 (2%) |
| Brazilian markets | 1 (0%) | — |
| CAD | — | 7 (0%) |
| CAD/USD | — | 13 (0%) |
| CEE FX | — | 10 (0%) |
| CEE exports | — | 1 (0%) |
| CHF/EUR | — | 1 (0%) |
| CHF/JPY | — | 1 (0%) |
| CNY | — | 1 (0%) |
| CNY/USD | — | 2 (0%) |
| Canadian Dollar | — | 5 (0%) |
| Canadian markets | — | 1 (0%) |
| Canadian rates | — | 1 (0%) |
| Cardano | — | 8 (0%) |
| China 10-year government bonds | 1 (0%) | — |
| China macro | — | 1 (0%) |
| Chinese GDP | — | 1 (0%) |
| Chinese Yuan | — | 1 (0%) |
| Chinese credit | — | 1 (0%) |
| Chinese economy | — | 1 (0%) |
| Chinese macro data | — | 1 (0%) |
| Chinese markets | — | 2 (0%) |
| Cocoa Futures | — | 1 (0%) |
| Copper | 2 (0%) | 14 (0%) |
| Czech Crown | — | 1 (0%) |
| DAX | 10 (1%) | 20 (0%) |
| DXY | — | 4 (0%) |
| Denison Mine | — | 1 (0%) |
| Dogecoin | — | 13 (0%) |
| Dollar Index | — | 1 (0%) |
| EUR/CAD | — | 1 (0%) |
| EUR/CHF | — | 1 (0%) |
| EUR/GBP | — | 29 (1%) |
| EUR/JPY | — | 37 (1%) |
| EUR/PLN | — | 1 (0%) |
| EUR/SEK | — | 1 (0%) |
| EUR/USD | 4 (0%) | 572 (11%) |
| Estée Lauder | — | 1 (0%) |
| Ethereum | — | 10 (0%) |
| European Natural Gas | — | 1 (0%) |
| European gas | — | 1 (0%) |
| European natural gas | 1 (0%) | — |
| European stocks | 72 (5%) | 124 (2%) |
| Eurozone macro | — | 2 (0%) |
| Forex | — | 1 (0%) |
| French bond | 1 (0%) | — |
| GBP/JPY | — | 37 (1%) |
| GBP/USD | — | 526 (10%) |
| Glencore | 1 (0%) | — |
| Gold | 44 (3%) | 510 (10%) |
| Goldman Sachs | — | 1 (0%) |
| — | 1 (0%) | |
| Hims & Hers Health | — | 1 (0%) |
| Hong Kong SME Business | — | 1 (0%) |
| Hungarian Forint | — | 6 (0%) |
| Hungarian economy | — | 1 (0%) |
| IDR/USD | — | 5 (0%) |
| INR | — | 1 (0%) |
| INR/USD | — | 4 (0%) |
| Indian stocks | 72 (5%) | 90 (2%) |
| Indonesia | — | 2 (0%) |
| Indonesia Inflation | — | 1 (0%) |
| Indonesian | 1 (0%) | — |
| Indonesian Rupiah | — | 9 (0%) |
| Indonesian macroeconomics | — | 1 (0%) |
| Indonesian markets | — | 1 (0%) |
| Indonesian stock | 1 (0%) | — |
| Japanese stocks | 52 (4%) | 91 (2%) |
| KOSPI | — | 1 (0%) |
| KRW | — | 5 (0%) |
| KRW/KOSPI | — | 1 (0%) |
| KRW/USD | — | 4 (0%) |
| Kazakh tenge | 1 (0%) | — |
| Korean Won | — | 2 (0%) |
| Korean markets | — | 1 (0%) |
| MENA FX | — | 1 (0%) |
| MYR | — | 1 (0%) |
| MYR/USD | — | 4 (0%) |
| Mastercard Inc | — | 1 (0%) |
| Meta | — | 1 (0%) |
| Mexican Peso | — | 1 (0%) |
| NASDAQ | 12 (1%) | 45 (1%) |
| NBCC | — | 1 (0%) |
| NOK | — | 2 (0%) |
| NOK/EUR | — | 1 (0%) |
| NOK/SEK | — | 1 (0%) |
| NOK/USD | — | 2 (0%) |
| NZD | — | 5 (0%) |
| NZD/USD | — | 18 (0%) |
| Natural Gas | — | 3 (0%) |
| New Zealand | — | 1 (0%) |
| New Zealand Trade Balance | — | 1 (0%) |
| New Zealand markets | — | 2 (0%) |
| Norwegian Krone | — | 5 (0%) |
| Novo Nordisk | — | 1 (0%) |
| OKLO | — | 1 (0%) |
| Oil | 411 (29%) | 522 (10%) |
| PBR | — | 1 (0%) |
| PHP | — | 1 (0%) |
| PHP/USD | — | 1 (0%) |
| PLN/EUR | — | 1 (0%) |
| Pfizer | — | 1 (0%) |
| Philippine Peso | — | 1 (0%) |
| Pi Network | — | 3 (0%) |
| Polish Zloty | — | 4 (0%) |
| Ralph Lauren | — | 1 (0%) |
| Romanian Leu | — | 1 (0%) |
| SEK | — | 1 (0%) |
| SEK/USD | — | 1 (0%) |
| SGD | — | 2 (0%) |
| SGD/SGDNEER | — | 1 (0%) |
| SGD/USD | — | 6 (0%) |
| Silver | 3 (0%) | 222 (4%) |
| Singapore CPI | — | 1 (0%) |
| Singapore Economy | — | 1 (0%) |
| Singapore GDP | — | 1 (0%) |
| Singapore macro | — | 1 (0%) |
| Solana | — | 5 (0%) |
| South African Rand | — | 2 (0%) |
| South Korean | 1 (0%) | — |
| South Korean Won | — | 1 (0%) |
| South Korean markets | — | 2 (0%) |
| South Korean monetary policy | — | 1 (0%) |
| Swedish Krona | — | 1 (0%) |
| Swedish interest rates | — | 1 (0%) |
| Swiss Franc | — | 3 (0%) |
| Synthetix | — | 1 (0%) |
| THB/USD | — | 1 (0%) |
| Taiwan Dollar | — | 1 (0%) |
| Taiwan macro | — | 1 (0%) |
| Taiwan tech exports | — | 1 (0%) |
| Thai Baht | — | 7 (0%) |
| Travelers Insurance | — | 1 (0%) |
| Turkish | 1 (0%) | — |
| Turkish Lira | — | 3 (0%) |
| UK markets | 79 (6%) | 127 (2%) |
| US Dollar | — | 9 (0%) |
| US Dollar Index | — | 19 (0%) |
| US banking sector | 1 (0%) | — |
| US short-term interest rates | 1 (0%) | — |
| USA | 221 (16%) | 540 (10%) |
| USD | — | 19 (0%) |
| USD Index | — | 3 (0%) |
| USD/CAD | — | 45 (1%) |
| USD/CHF | — | 16 (0%) |
| USD/CNH | — | 14 (0%) |
| USD/CNY | — | 1 (0%) |
| USD/IDR | — | 8 (0%) |
| USD/INR | — | 7 (0%) |
| USD/JPY | 20 (1%) | 693 (13%) |
| USD/MXN | — | 3 (0%) |
| USD/MYR | — | 3 (0%) |
| USD/PHP | — | 2 (0%) |
| USD/SGD | — | 13 (0%) |
| USD/TRY | — | 1 (0%) |
| USD/TWD | — | 2 (0%) |
| USD/VND | — | 1 (0%) |
| USD/ZAR | — | 2 (0%) |
| USDCAD | — | 1 (0%) |
| XRP | — | 30 (1%) |
| critical minerals | 1 (0%) | — |
| cryptocurrencies (Crypto) | 17 (1%) | 34 (1%) |
| forex markets | — | 1 (0%) |
| global food | 1 (0%) | — |
| global markets | 147 (10%) | 76 (2%) |
| high-yield credit markets | 1 (0%) | — |
| junk-rated corporate bonds | 1 (0%) | — |
| private | 1 (0%) | — |
| private markets | 1 (0%) | — |
| technology stocks (Tech) | 101 (7%) | 49 (1%) |
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Wie oft die Nachrichten richtig lagen
Die Trefferquote jeder Quelle im Vergleich zum Zufall
Häufig gestellte Fragen
Was ist zuverlässiger: Financial Times oder FXStreet?▼
Wie werden diese Vergleiche berechnet?▼
Welche Märkte decken Financial Times und FXStreet gemeinsam ab?▼
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.