Financial Timesvswallstreet-online Nachrichten
Financial Times (37.5% hit rate) vs wallstreet-online Nachrichten (36.2% hit rate): how often each source’s headline tone matched the later price move.
Neither did better against chance than the other
Based on 3146 and 1158 checked headlines
Hit rate
Checked reports
Articles Analyzed
Avg. Relevance
Sentiment & Bias Analysis
How bullish or bearish each source’s headlines tend to be.
Sentiment Distribution
Financial Times
wallstreet-online Nachrichten
Market Context Coverage
| Hit rate by market | Financial Times | wallstreet-online Nachrichten |
|---|---|---|
| AI infrastructure bonds | 1 (0%) | — |
| ASOS | — | 1 (0%) |
| AT&S | — | 1 (0%) |
| AT&T | — | 1 (0%) |
| AXA | — | 1 (0%) |
| Adobe | — | 1 (0%) |
| Airbus | — | 2 (0%) |
| Aixtron | — | 1 (0%) |
| Alibaba | — | 3 (1%) |
| Alibaba/Chinese Tech | — | 1 (0%) |
| Allianz | — | 2 (0%) |
| Alphabet | — | 1 (0%) |
| Amazon | — | 2 (0%) |
| American Express | — | 1 (0%) |
| AppLovin | — | 1 (0%) |
| Apple | — | 3 (1%) |
| Argentine peso | 1 (0%) | — |
| Asian stocks | 85 (6%) | 3 (1%) |
| Australian stocks | 23 (2%) | 3 (1%) |
| Auto1 Group | — | 1 (0%) |
| Aviation/Transport | — | 1 (0%) |
| BMW | — | 1 (0%) |
| BNB | 3 (0%) | 1 (0%) |
| BYD | — | 3 (1%) |
| Bank | — | 1 (0%) |
| Bayer | — | 1 (0%) |
| BioNTech | — | 2 (0%) |
| Biogen | — | 1 (0%) |
| Biotech | — | 1 (0%) |
| Bitcoin | 18 (1%) | 20 (3%) |
| BlackRock | — | 1 (0%) |
| Brazilian | — | 1 (0%) |
| Brazilian Real | — | 2 (0%) |
| Brazilian markets | 1 (0%) | — |
| Bulgarian | — | 1 (0%) |
| Canadian markets | — | 1 (0%) |
| Cannabis | — | 2 (0%) |
| Carrefour | — | 1 (0%) |
| China 10-year government bonds | 1 (0%) | — |
| Chinese solar sector | — | 1 (0%) |
| Coca-Cola | — | 1 (0%) |
| Copper | 2 (0%) | 2 (0%) |
| DAX | 10 (1%) | 51 (8%) |
| DHL Group | — | 1 (0%) |
| Daimler Truck | — | 1 (0%) |
| Dell Technologies | — | 1 (0%) |
| Deutsche Bank | — | 2 (0%) |
| Deutsche Telekom | — | 3 (1%) |
| EUR/USD | 4 (0%) | 4 (1%) |
| EssilorLuxottica | — | 1 (0%) |
| Estée Lauder | — | 1 (0%) |
| Ethereum | — | 1 (0%) |
| European natural gas | 1 (0%) | — |
| European stocks | 72 (5%) | 37 (6%) |
| Evotec | — | 1 (0%) |
| Fortinet | — | 1 (0%) |
| French bond | 1 (0%) | — |
| French government bonds | — | 2 (0%) |
| General Motors | — | 1 (0%) |
| Glencore | 1 (0%) | — |
| Gold | 44 (3%) | 27 (4%) |
| HP | — | 1 (0%) |
| Hapag-Lloyd | — | 1 (0%) |
| HelloFresh | — | 1 (0%) |
| Hensoldt AG | — | 1 (0%) |
| Honda | — | 1 (0%) |
| Honeywell Aerospace | — | 1 (0%) |
| Hungarian markets | — | 1 (0%) |
| IBM | — | 1 (0%) |
| IMAX | — | 1 (0%) |
| Iambic Therapeutics | — | 1 (0%) |
| Indian stocks | 72 (5%) | 3 (1%) |
| Indonesian | 1 (0%) | — |
| Indonesian stock | 1 (0%) | — |
| IonQ | — | 1 (0%) |
| Iranian Rial | — | 1 (0%) |
| Jakarta Stock Exchange | — | 1 (0%) |
| Japanese stocks | 52 (4%) | 2 (0%) |
| Kazakh tenge | 1 (0%) | — |
| Kraft Heinz | — | 1 (0%) |
| Kupfermarkt | — | 1 (0%) |
| Leonardo | — | 1 (0%) |
| Lithium | — | 1 (0%) |
| Lockheed Martin | — | 2 (0%) |
| Lufthansa stock, aviation sector | — | 1 (0%) |
| Mensch und Maschine | — | 1 (0%) |
| Meta Platforms | — | 2 (0%) |
| Micron | — | 1 (0%) |
| MiniMax | — | 1 (0%) |
| Moderna | — | 1 (0%) |
| NASDAQ | 12 (1%) | 16 (3%) |
| Nanexa | — | 1 (0%) |
| Nebius Group | — | 2 (0%) |
| NetApp | — | 1 (0%) |
| Netflix | — | 2 (0%) |
| NextDC | — | 1 (0%) |
| Nike | — | 2 (0%) |
| Nordex | — | 1 (0%) |
| Nordex AG | — | 1 (0%) |
| Novo Nordisk | — | 2 (0%) |
| Novo Nordisk, pharmaceutical | — | 1 (0%) |
| Nscale IPO | — | 1 (0%) |
| Oil | 411 (29%) | 96 (15%) |
| Oracle | — | 2 (0%) |
| Palantir | — | 1 (0%) |
| Palantir stock, analyst rating | — | 1 (0%) |
| Palfinger | — | 2 (0%) |
| Palo Alto Networks | — | 1 (0%) |
| PayPal | — | 2 (0%) |
| Procter & Gamble | — | 2 (0%) |
| Puma SE | — | 1 (0%) |
| Redcare Pharmacy | — | 1 (0%) |
| Renk AG | — | 2 (0%) |
| Rheinmetall | — | 1 (0%) |
| Rheinmetall / defense technology | — | 1 (0%) |
| Rivian stock, EV maker | — | 1 (0%) |
| SAP | — | 1 (0%) |
| SK Hynix | — | 1 (0%) |
| Saab AB | — | 1 (0%) |
| Salesforce | — | 1 (0%) |
| Salzgitter AG | — | 1 (0%) |
| Samsung Electronics | — | 2 (0%) |
| Sandisk | — | 1 (0%) |
| Sartorius | — | 1 (0%) |
| Shopify-related e-commerce software | — | 1 (0%) |
| Siemens | — | 1 (0%) |
| Siemens AG | — | 1 (0%) |
| Siemens Energy | — | 3 (1%) |
| Silver | 3 (0%) | 11 (2%) |
| SoftBank | — | 1 (0%) |
| South Korean | 1 (0%) | 1 (0%) |
| South Korean solar | — | 1 (0%) |
| Space sector | — | 1 (0%) |
| SpaceX | — | 1 (0%) |
| Swiss Franc | — | 1 (0%) |
| Target | — | 1 (0%) |
| Technip Energies | — | 1 (0%) |
| Tesla | — | 3 (1%) |
| Thyssenkrupp | — | 1 (0%) |
| Turkish | 1 (0%) | — |
| UK markets | 79 (6%) | 3 (1%) |
| US Real Estate | — | 1 (0%) |
| US Soybean | — | 1 (0%) |
| US banking sector | 1 (0%) | — |
| US short-term interest rates | 1 (0%) | — |
| USA | 219 (16%) | 55 (9%) |
| USD/JPY | 20 (1%) | 1 (0%) |
| Uber Technologies, ride-hailing | — | 1 (0%) |
| Union Pacific | — | 1 (0%) |
| Uranium | — | 1 (0%) |
| Verbio AG | — | 1 (0%) |
| Verizon | — | 1 (0%) |
| Vertiv | — | 1 (0%) |
| Vestas Wind Systems | — | 1 (0%) |
| Vincorion | — | 1 (0%) |
| Vonovia | — | 2 (0%) |
| XRP | — | 4 (1%) |
| Xiaomi | — | 1 (0%) |
| Xpeng | — | 1 (0%) |
| Zinc | — | 2 (0%) |
| critical minerals | 1 (0%) | — |
| cryptocurrencies (Crypto) | 17 (1%) | 7 (1%) |
| general | — | 1 (0%) |
| global food | 1 (0%) | — |
| global markets | 146 (10%) | 14 (2%) |
| high-yield credit markets | 1 (0%) | — |
| junk-rated corporate bonds | 1 (0%) | — |
| online retail / e-commerce | — | 1 (0%) |
| private | 1 (0%) | — |
| private markets | 1 (0%) | — |
| restaurant | — | 1 (0%) |
| technology stocks (Tech) | 100 (7%) | 97 (16%) |
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Each source’s hit rate, compared with chance
Frequently Asked Questions
Which is more reliable: Financial Times or wallstreet-online Nachrichten?▼
How are these comparisons calculated?▼
What markets do Financial Times and wallstreet-online Nachrichten both cover?▼
Our Methodology
AI classifies each article's tone as up, down or sideways for the market it covers. From the first price a reader could trade after publication we check the move after 1, 3 and 7 days. A source's hit rate is compared with chance for the same calls and outcomes within each market, so covering calm or busy markets earns nothing. Each difference comes with a 95 % interval; checks close in time are resampled together in blocks of 7 or 14 days, because they share market moves. A verdict needs at least 300 checks and must hold after correcting for the number of sources tested (Holm). This answers "did the market move that way?": a hit rate, not a return. AIamond makes no forecasts of its own.