The Gold – Sample Data dataset captures structured insights into how sentiment, macroeconomic drivers, and market events influence gold prices. Covering multiple themes such as monetary policy, institutional buying, consumer demand, and supply dynamics, the dataset provides a transparent view of narrative flows that act as leading indicators for price direction. For the period 10–17 May 2025, the dataset highlights: Bearish sentiment from U.S. dollar strength and rising mining output. Bullish sentiment from central bank reserve purchases, jewellery demand recovery, and safe-haven flows amid geopolitical tensions. Policy influence with the Federal Reserve’s rate decisions directly impacting gold’s relative attractiveness. Each entry records timestamped events, directional sentiment (up/down), topic classification, and narrative detail, allowing systematic traders and analysts to test correlations between sentiment shifts and subsequent gold price action. This data helps quants and commodity desks integrate structured sentiment into models, evaluate thematic drivers of gold volatility, and identify predictive signals ahead of market moves.

The Seamless API Integration dataset description outlines how Permutable Co-Pilot’s data can be directly embedded into trading workflows, research environments, and analytic platforms. Through a robust and flexible API, users gain access to real-time market intelligence, including: Sentiment scores derived from unstructured data. Forecasts and predictive signals for commodities, equities, currencies, and macro events. Event-driven datasets for fundamental, geopolitical, and narrative analysis. The API is designed for quantitative researchers, systematic traders, and developers, offering: Cross-language support with client libraries in Python, R, and Java. Comprehensive documentation for rapid onboarding. Scalable endpoints for time-series queries, sentiment extraction, and factor modelling. By integrating these data streams programmatically, trading teams can automate ingestion of narrative-driven insights, backtest their impact on portfolios, and deploy models with real-time intelligence as leading indicators.