[{"data":1,"prerenderedAt":102},["ShallowReactive",2],{"page:\u002Fquantitative-trading\u002F":3,"built-pages":83,"post:\u002Fquantitative-trading\u002F":101},{"page":4,"path":5,"title":6,"description":7,"image":8,"noindex":9,"demoTab":9,"sections":10,"posts":82},"quantitative-trading","\u002Fquantitative-trading\u002F","Perception data as alpha signals for quant models | Atlastic","Trust, sentiment, attention and controversy as ticker-mapped time series for 50,000+ listed companies, with 5+ years of point-in-time history.","\u002Fuploads\u002F2021\u002F05\u002FFinance-bg-img.jpg",false,[11,24,46,55,67,73],{"type":12,"heading":13,"text":14,"glass":15,"align":16,"buttons":17,"background":22},"hero","Quantitative Trading","Atlastic delivers perception data as alpha signals for quant models",true,"center",[18],{"label":19,"to":20,"variant":21},"REQUEST DEMO","#demo","ring",{"image":8,"overlay":23},"tint-light",{"type":25,"heading":26,"text":27,"slides":28},"text-image","Perception as Alpha Signals – for the ==Win==","Markets react to perception before fundamentals adjust. Investor behavior, risk appetite, and capital flows are shaped by trust, narrative momentum, and controversy build-up long before price and volume reflect these forces.\n\nAtlastic delivers a structured, high-resolution dataset on how companies are portrayed and perceived across millions of global media sources. Perception-based data quantifies sentiment, trust, attention, and controversy as measurable, time-series variables mapped to over 50,000 listed companies worldwide – updated in real time.\n\nBy processing 8M+ verified sources in 100+ languages and linking every signal directly to a ticker, Atlastic enables quant researchers to uncover predictive factors, expand models, and integrate market psychology as a forward-looking input to systematic strategies.\n\nThis is not keyword scoring. It is structured perception intelligence – purpose-built for alpha discovery.",[29,34,37,40],{"src":30,"alt":31,"width":32,"height":33},"\u002Fuploads\u002F2023\u002F02\u002FCorrelations-and-casualties.png","Trust Value of Netflix compared with its share price, day by day",980,660,{"src":35,"alt":36,"width":32,"height":33},"\u002Fuploads\u002F2023\u002F02\u002Fceo-ratings.png","Relations overview in the Atlastic platform: how media coverage of Tesla and Elon Musk overlaps",{"src":38,"alt":39,"width":32,"height":33},"\u002Fuploads\u002F2023\u002F02\u002FCorporate-Reputation.png","Trust Asset Valuator: the real-time Trust Value of stock market indexes such as the Nasdaq 100 and the S&P 500",{"src":41,"alt":42,"caption":43,"width":44,"height":45},"\u002Fuploads\u002F2025\u002F08\u002FLinechart-1.png","Line chart of the Trust Value of Sanofi against its share price over six months","Trust Value insight over time",914,586,{"type":25,"tone":47,"imageSide":48,"reveal":49,"heading":50,"text":51,"image":52},"muted","left","fade","==Relevance== of Perception in Quant Research","**Empirical studies show that shifts in sentiment and media attention can predict future returns, volatility, and liquidity. Yet perception remains underused in quantitative research because traditional datasets are:**\n\n- **Sparse and lagging**: surveys are infrequent and narrow in scope.\n- **Noisy and shallow**: keyword sentiment misses context and narrative framing.\n- **Difficult to scale**: unstructured text resists clean integration with models.\n\nAs a result, many strategies overlook the informational layer where market expectations are formed. Perception is inherently forward-looking: trust builds before momentum, controversy emerges before drawdowns, and stakeholder sentiment shifts before leadership or policy changes drive repricing.\n\n**Atlastic captures this layer in structured form, making it possible to:**\n\n- Detect narrative build-up ahead of volatility events.\n- Quantify stakeholder trust momentum as a leading indicator.\n- Enhance multi-factor models with perception-driven inputs.\n- Identify early controversy signals that anticipate repricing.",{"src":53,"alt":54,"width":32,"height":33},"\u002Fuploads\u002F2023\u002F02\u002Frankings.png","Peer group rankings for Netflix: its global, country, sector and industry rank among US stocks",{"type":56,"spacing":57,"heading":58,"text":59,"aside":60,"glass":61,"background":62},"text","tall","The Data ==Difference== for Predictive Edge","Atlastic ingests 4M+ articles daily from a curated universe of 8M+ verified sources across 250+ jurisdictions – covering financial media, industry publications, NGO reports, regulatory filings, and local news. Each signal is transformed into structured, model-ready data through:\n\n1. Contextual Scoring – sentiment captured in full narrative context, not isolated keywords.\n2. Influence Weighting – sources ranked by credibility and market-shaping potential.\n3. Stakeholder Mapping – signals connected to companies, sectors, and decision-makers.\n4. Time Awareness – shifts timestamped for both short-term reactions and long-horizon modeling.\n5. Entity Linking – mapped to tickers, sectors, and geographies for cross-sectional analysis.","**Atlastic also provides 5+ years of point-in-time history, enabling robust backtesting and survivorship-bias-free research.**\n\nThis structured, machine-readable dataset enables:\n\n- Signal Discovery – correlation analysis and hypothesis testing across vast narrative data.\n- Factor Construction – build standalone perception factors or overlay them on value, momentum, and quality models.\n- Risk Diagnostics – track trust erosion, controversy build-up, and leadership sentiment as leading volatility drivers.\n- Event Anticipation – identify early signals of earnings surprises, regulatory actions, and reputational shocks.","aside",{"image":63,"size":64,"position":65,"overlay":66},"\u002Fuploads\u002F2021\u002F06\u002Fintegration-3-e1675864944346.jpg","50%","100% 44%","none",{"type":25,"tone":47,"imageSide":48,"reveal":49,"heading":68,"text":69,"image":70},"Precision Data ==Delivery== for Quant Research","**Atlastic delivers clean, scalable datasets purpose-built for systematic strategies and quant research workflows:**\n\n- API & Custom Feeds – standardized schema across entities, sectors, and regions.\n- Real-Time Streaming – configurable thresholds for monitoring and alerts.\n- Point-in-Time Archives – robust backtesting and factor validation without survivorship bias.\n- Seamless Integration – ready for Python, R, and cloud-based analytics environments.\n\nFrom targeted sector coverage and event-specific backfills to full-universe data, Atlastic provides structured perception signals designed for proprietary model engineering.",{"src":71,"alt":72,"width":44,"height":45},"\u002Fuploads\u002F2025\u002F08\u002Fcode-screen.png","Source code that loads Atlastic ESG data into a chart",{"type":56,"spacing":57,"heading":74,"text":75,"glass":56,"buttons":76,"background":78},"Explore how it works.","Request a demo to access sample data, explore perception mappings, and discuss how Atlastic fits into your existing quant research environment.",[77],{"label":19,"to":20,"variant":21},{"image":79,"position":80,"overlay":81},"\u002Fuploads\u002F2025\u002F08\u002Fpiepilipses-demo-bg.jpg","0% 50%","tint-strong",[],[84,85,86,87,88,89,90,91,92,93,94,95,4,96,97,98,99,100],"_home","about","asset-managers","contact","crypto","demo","hedge-funds","methodology","news-updates","perceived-esg","privacy-policy","private-capital","risk-management","terms-and-conditions","the-atlastic-philosophy","trading-signals","trust-value-tracking",null,1791457820397]