Bangkok Post Businessvswallstreet-online Nachrichten
Bangkok Post Business (32.6 % de acierto) vs wallstreet-online Nachrichten (36.8 % de acierto): cuántas veces el tono de los titulares de cada fuente coincidió con el movimiento posterior del precio.
Ninguna salió mejor frente al azar que la otra
Basado en 307 y 1181 titulares comprobados
Posición #17 de — fuentes
Posición #13 de — fuentes
Tasa de acierto
Noticias comprobadas
Artículos Analizados
Relevancia Promedio
Análisis de sentimiento y sesgo
Lo alcistas o bajistas que suelen ser los titulares de cada fuente.
Distribución de sentimiento
Bangkok Post Business
wallstreet-online Nachrichten
Cobertura de contextos de mercado
| Acierto por mercado | Bangkok Post Business | wallstreet-online Nachrichten |
|---|---|---|
| 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%) |
| Asian stocks | 27 (13%) | 3 (1%) |
| Australian stocks | — | 3 (1%) |
| Auto1 Group | — | 1 (0%) |
| Automotive/EV import policy | 1 (1%) | — |
| Aviation/Transport | — | 1 (0%) |
| BMW | — | 1 (0%) |
| BNB | — | 1 (0%) |
| BYD | — | 3 (1%) |
| Bank | — | 1 (0%) |
| Bayer | — | 1 (0%) |
| BioNTech | — | 2 (0%) |
| Biogen | — | 1 (0%) |
| Biotech | — | 1 (0%) |
| Bitcoin | 7 (3%) | 21 (3%) |
| BlackRock | — | 1 (0%) |
| Brazilian | — | 1 (0%) |
| Brazilian Real | — | 2 (0%) |
| Bulgarian | — | 1 (0%) |
| Canadian markets | — | 1 (0%) |
| Cannabis | — | 2 (0%) |
| Carrefour | — | 1 (0%) |
| China Economy | 1 (1%) | — |
| Chinese solar sector | — | 1 (0%) |
| Coca-Cola | — | 1 (0%) |
| Commodities | — | 1 (0%) |
| Copper | — | 2 (0%) |
| D-Wave | — | 1 (0%) |
| DAX | 1 (1%) | 54 (8%) |
| DHL Group | — | 1 (0%) |
| Daimler Truck | — | 1 (0%) |
| Dell Technologies | — | 1 (0%) |
| Deutsche Bank | — | 2 (0%) |
| Deutsche Telekom | — | 3 (1%) |
| EUR/USD | — | 4 (1%) |
| Electronics & Tourism | 1 (1%) | — |
| EssilorLuxottica | — | 1 (0%) |
| Estée Lauder | — | 1 (0%) |
| Ethereum | — | 1 (0%) |
| European natural gas | — | 1 (0%) |
| European stocks | 4 (2%) | 40 (6%) |
| Evotec | — | 1 (0%) |
| Fortinet | — | 1 (0%) |
| French government bonds | — | 2 (0%) |
| General Motors | — | 1 (0%) |
| Gold | 23 (11%) | 28 (4%) |
| HP | — | 1 (0%) |
| Hapag-Lloyd | — | 1 (0%) |
| HelloFresh | — | 1 (0%) |
| Hensoldt AG | — | 1 (0%) |
| Home improvement sector | 1 (1%) | — |
| Honda | — | 1 (0%) |
| Honeywell Aerospace | — | 1 (0%) |
| Hungarian markets | — | 1 (0%) |
| IBM | — | 1 (0%) |
| IMAX | — | 1 (0%) |
| Iambic Therapeutics | — | 1 (0%) |
| Indian stocks | — | 3 (1%) |
| IonQ | — | 1 (0%) |
| Iranian Rial | — | 1 (0%) |
| Jakarta Stock Exchange | — | 1 (0%) |
| Japanese stocks | 4 (2%) | 2 (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 | — | 16 (3%) |
| Nanexa | — | 1 (0%) |
| Nebius Group | — | 2 (0%) |
| NetApp | — | 1 (0%) |
| Netflix | — | 2 (0%) |
| NextDC | — | 1 (0%) |
| Nike | 1 (1%) | 2 (0%) |
| Nordex | — | 1 (0%) |
| Nordex AG | — | 1 (0%) |
| Novo Nordisk | — | 2 (0%) |
| Novo Nordisk, pharmaceutical | — | 1 (0%) |
| Nscale IPO | — | 1 (0%) |
| Oil | 31 (15%) | 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%) |
| RWE | — | 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 | — | 11 (2%) |
| SoftBank | — | 1 (0%) |
| South Korean | — | 1 (0%) |
| South Korean solar | — | 1 (0%) |
| Space sector | — | 1 (0%) |
| SpaceX | — | 1 (0%) |
| Swiss Franc | — | 1 (0%) |
| Take-Two Interactive | — | 2 (0%) |
| Target | — | 1 (0%) |
| Technip Energies | — | 1 (0%) |
| Tesla | — | 3 (1%) |
| Thai | 8 (4%) | — |
| Thai Airways | 2 (1%) | — |
| Thai Baht | 4 (2%) | — |
| Thai GDP growth outlook | 1 (1%) | — |
| Thai banking sector | 1 (1%) | — |
| Thai banks | 1 (1%) | — |
| Thai bond | 1 (1%) | — |
| Thai bonds | 1 (1%) | — |
| Thai brokerage industry | 1 (1%) | — |
| Thai corporate bond | 1 (1%) | — |
| Thai domestic vehicle sales | 1 (1%) | — |
| Thai economic growth | 1 (1%) | — |
| Thai economy | 1 (1%) | — |
| Thai economy GDP growth | 1 (1%) | — |
| Thai exports | 1 (1%) | — |
| Thai insurance industry | 1 (1%) | — |
| Thai macroeconomics | 1 (1%) | — |
| Thai restaurant industry | 1 (1%) | — |
| Thai retail sector | 1 (1%) | — |
| Thai rice exports | 1 (1%) | — |
| Thai stock | 6 (3%) | — |
| Thai stock exchange, SET | 1 (1%) | — |
| Thai tourism | 2 (1%) | — |
| Thai tourism revenue | 1 (1%) | — |
| Thai tourism sector | 1 (1%) | — |
| Thailand IT | 1 (1%) | — |
| Thailand SET | 1 (1%) | — |
| Thailand auto sales | 1 (1%) | — |
| Thailand automotive | 1 (1%) | — |
| Thailand banking sector | 1 (1%) | — |
| Thailand digital infrastructure | 1 (1%) | — |
| Thailand e-commerce | 1 (1%) | — |
| Thailand inbound tourism | 1 (1%) | — |
| Thailand luxury retail | 1 (1%) | — |
| Thailand national economy | 1 (1%) | — |
| Thailand sovereign credit rating | 1 (1%) | — |
| Thailand stock | 1 (1%) | — |
| Thailand tourism | 1 (1%) | — |
| Thailand tourism industry | 1 (1%) | — |
| Thailand tourism revenue | 1 (1%) | — |
| Thailand tourism sector | 2 (1%) | — |
| Thyssenkrupp | — | 1 (0%) |
| UK markets | 3 (1%) | 3 (1%) |
| US Real Estate | — | 1 (0%) |
| US Soybean | — | 1 (0%) |
| USA | 11 (5%) | 57 (9%) |
| USD/JPY | 1 (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%) |
| Vietnamese | 1 (1%) | — |
| Vincorion | — | 1 (0%) |
| Vonovia | — | 2 (0%) |
| XRP | — | 5 (1%) |
| Xiaomi | — | 1 (0%) |
| Xpeng | — | 1 (0%) |
| Zinc | — | 2 (0%) |
| compact digital cameras | 1 (1%) | — |
| computer hardware | 1 (1%) | — |
| cryptocurrencies (Crypto) | 3 (1%) | 7 (1%) |
| electricity | 1 (1%) | — |
| ethanol | 1 (1%) | — |
| general | — | 1 (0%) |
| global markets | 17 (8%) | 15 (2%) |
| insurance | 1 (1%) | — |
| online retail / e-commerce | — | 1 (0%) |
| restaurant | — | 1 (0%) |
| road freight transport rates | 1 (1%) | — |
| technology stocks (Tech) | 8 (4%) | 98 (15%) |
La situación informativa de hoy, no una previsión
Un breve correo diario gratuito con las noticias de mercado más relevantes y hacia dónde se inclinan, con fuentes.
Obtén Información de Mercado con IA Gratis
El panorama de las noticias de tus mercados, leídas por IA. Gratis, sin tarjeta de crédito.
Tendencias de mercado analizadas por IA
Consulta gratis las tendencias analizadas
Tu Propio Panel
Listas de seguimiento y el panorama de noticias, cuando quieras
Cuántas veces acertaron las noticias
La tasa de acierto de cada fuente frente al azar
Preguntas Frecuentes
¿Qué es más fiable: Bangkok Post Business o wallstreet-online Nachrichten?▼
¿Cómo se calculan estas comparaciones?▼
¿Qué mercados cubren en común Bangkok Post Business y wallstreet-online Nachrichten?▼
Nuestra Metodología
Una IA clasifica el tono de cada artículo como alcista, bajista o lateral para el mercado que trata. Desde el primer precio al que un lector podía operar tras la publicación, comprobamos el movimiento a los 1, 3 y 7 días. La tasa de acierto de una fuente se compara con el azar para las mismas valoraciones y resultados dentro de cada mercado, de modo que cubrir mercados tranquilos o agitados no aporta nada. Cada diferencia lleva un intervalo del 95 %; las comprobaciones cercanas en el tiempo se remuestrean juntas en bloques de 7 o 14 días, porque comparten movimientos del mercado. Un veredicto requiere al menos 300 comprobaciones y debe mantenerse tras corregir por el número de fuentes probadas (Holm). Responde a «¿se movió el mercado así?»: una tasa de acierto, no una rentabilidad. AIamond no hace previsiones propias.