Systematic traders operate in a market reality where narrative, sentiment and geopolitics reshape risk in real time.
Permutable transforms global information flow into structured, explainable intelligence, helping teams uncover signals earlier, monitor regimes continuously and scale systematic research with greater precision.
Our intelligence engine turns complex global information into transparent, actionable signals. By analysing news, media, macro and market-related data, our platform helps systematic teams detect emerging narratives, track sentiment changes and understand the context behind market movements in real time.
This signal layer is backed by our own live trading strategy, giving systematic teams a practical view of how narrative and sentiment intelligence can be translated into market-tested research signals.
Transform global news, macro developments, geopolitical events and sentiment shifts into structured intelligence and identify emerging signals earlier.
Understand the narratives behind market movements with transparent, auditable insights across media, macro and market-related data.
Real-time intelligence identifying macroeconomic, geopolitical, policy, and narrative developments shaping commodities, FX, rates, volatility regimes, and broader institutional market positioning.
Detect when narrative momentum evolves from temporary market noise into structural repricing, macro regime change, and persistent cross-market transmission.
Generate structured, decision-ready signals engineered for quantitative research, portfolio construction, systematic execution, and live trading environments.
Permutable delivers AI-native market intelligence designed for systematic trading workflows. Our platform transforms millions of global narratives, macroeconomic developments, geopolitical events, and sentiment signals into structured, research-grade intelligence that quantitative teams can integrate into trading models, research pipelines, portfolio construction frameworks, and execution environments.
Permutable provides cross-asset intelligence across commodities, FX, rates, macro markets, and broader financial markets.
Coverage includes energy markets such as WTI, Brent, Henry Hub, LNG, and TTF, alongside metals, agriculture, foreign exchange, and macroeconomic indicators across developed and emerging economies.
Traditional market data providers primarily focus on price, volume, and economic releases. Traditional quant and sentiment datasets are often limited in their ability to model how narrative propagation and information velocity reshape markets in real time.
Permutable focuses on the information and narrative layer influencing market behaviour before repricing fully appears in traditional datasets.
Our infrastructure analyses narrative persistence, macro sentiment, geopolitical developments, and cross-market transmission to help systematic teams identify regime shifts and emerging market drivers earlier.
Narrative persistence modelling measures whether market narratives are temporary reactions or developing into structural market repricing events.
Rather than treating all news or sentiment equally, Permutable identifies when themes such as inflation expectations, geopolitical tensions, supply disruptions, policy changes, or recession fears demonstrate sustained influence across assets and market regimes.
Permutable generates structured systematic intelligence including:
Signals are designed for quantitative research, systematic portfolio construction, and live execution environments.
Permutable supports multiple delivery methods depending on workflow requirements, including:
Our Intelligence Engine processes millions of daily narratives from more than 250,000 global information sources across 80+ languages, 90 + languages and 70 + assets in real time.
This enables broad coverage of local and global macro developments, geopolitical events, financial narratives, and market-moving information across regions and asset classes.
Yes. Permutable’s intelligence is designed to integrate directly into quantitative research and systematic trading environments, including Python research environments, APIs, cloud infrastructure, and institutional data pipelines.
Signals can be incorporated into:
Yes. Permutable supports historical analysis and research workflows designed for systematic strategy development, signal validation, and regime analysis across macro and commodity markets.
Historical point-in-time datasets over 11+ years can be used to analyse narrative persistence, sentiment behaviour, macro regime transitions, and cross-market relationships over time.
Our intelligence framework has been validated through live systematic trading strategies operating across commodity and macro markets over an 18-month period.
This live validation process helped refine how narrative flow, macro sentiment, and geopolitical developments are transformed into structured systematic signals designed for real-world trading environments.
Modern markets increasingly react to information flow, geopolitical developments, policy expectations, and narrative momentum before traditional indicators fully adjust.
As a result, systematic strategies relying solely on price, volume, or lagging economic data may struggle to identify emerging regime shifts early enough.
Narrative intelligence provides an additional contextual information layer designed to help quantitative teams model how markets absorb, propagate, and respond to information in real time across assets and macro regimes.
Yes, we use advanced natural language processing, machine learning, and large language model architectures to analyse global narrative flow, detect emerging market themes, classify sentiment, identify event significance, and construct structured systematic intelligence.
Permutable Global Macro Sentiment Indices are designed to identify changing macroeconomic expectations, policy sentiment, inflation narratives, and geopolitical developments before those shifts fully appear in traditional economic releases, consensus forecasts, or market pricing.
This helps systematic teams monitor evolving macro conditions in real time rather than relying solely on lagging indicators.
