Alternative Data

📊 Alternative data signals for company and market research

For finance researchers, equity analysts, data teams, and developers, Alternative Data turns a company or market-area choice into a structured signal row. Each row includes a 0–100 score, classification, confidence, source links, source timing, and the public indicators behind the score. Use it to study alternative data for investment decisions and build finance research datasets—not to get investment advice.

Use cases

• Review one company's score, news, hiring, filings, and source links with Company Analysis.
• Review a stock's company signal and news context with Stock Sentiment Analysis.
• Build a finance research row from public indicators with Alternative Data Finance.
• Use a scored row and its source links as context for Alternative Data For Investment Decisions, not as a trading recommendation.
• Build reusable public-data rows with Alternative Data Sets.
• Review sector return, relative strength, and disclosed congressional activity with Sector Analysis.
• Review a macro regime and domestic or global indicators with Macroeconomic Analysis.
• Review consumer stress, classification, and public indicators with Consumer Sentiment Analysis.

📈 Scores with evidence across six analysis lenses

Choose one target per run: target values are company, sector, macro, consumer, innovation, or cross_asset. Each saved row is for the selected target and includes its score, the signal components, public source URLs, source periods, and collection time. sourceIssues, stalenessWarnings, and history add context when the schema has it.

The score value is from 0 to 100, and confidence is from 0 to 1. A score is research context, not a price forecast, trade instruction, or investment recommendation.

▶️ Choose one lens and review its signal

Set the required target field to one analysis mode. Company analysis also uses companies, newsLookbackDays, and componentWeights; other targets ignore those company fields. Start with one company to review the output shape, then check the score rationale, source issues, freshness warnings, and source links before using a row.

⚙️ Input

The input form has one required field, target. Company analysis accepts one to 25 ticker symbols. The lookback and weight fields apply only to Company analysis.

Input fields

Field	Type	What it does
target	string, required	Selects company, sector, macro, consumer, innovation, or cross_asset analysis for the run.
companies	array of strings	For Company analysis, accepts one to 25 public-company ticker symbols, one per line. Other targets ignore it.
newsLookbackDays	integer	For Company analysis, sets how many recent days of company news to review. It must be at least 1. Other targets ignore it.
componentWeights	object	For Company analysis, sets the relative weights for news, hiring, and filing fundamentals. Values run from 0 to 100 and are scaled to a total of 100. Other targets ignore it.
componentWeights.news	number	Sets the relative weight of recent company news.
componentWeights.hiring	number	Sets the relative weight of the public company job board.
componentWeights.filingFundamentals	number	Sets the relative weight of filing-backed revenue and gross-margin changes.

Default input example

This is the public input from a successful current-beta default-input run:

{
  "target": "company",
  "companies": [
    "AAPL"
  ],
  "newsLookbackDays": 30,
  "componentWeights": {
    "news": 40,
    "hiring": 30,
    "filingFundamentals": 30
  }
}

🧾 Output

The run output links to the dataset. A dataset row contains the shared fields below and one matching analysis branch. Optional source-backed branches can be absent when a public source has no data for the subject. Arrays use [] in the field path to describe each member.

Run output link

Field	Type	What it does
dataset	URL string	Links to the signal rows from a successful run.

Shared row fields

Field	Type	What it does
target	string	Names the analysis target for the row.
subject	object	Identifies the company or market area covered by the row.
subject.name	string	Names the company or market area.
subject.symbol	string, optional	Gives the public ticker or source symbol for a company.
subject.scope	string, optional	Gives the market scope used for a non-company target.
score	object	Holds the bounded score and its explanation.
score.value	number	Gives the score from 0 to 100.
score.classification	string	Gives the plain label for the score direction.
score.confidence	number	Gives confidence from 0 to 1.
score.rationale	string	Explains the score in plain language.
score.components	array	Lists the signal parts used in the score.
score.components[].name	string	Names one signal part.
score.components[].score	number	Gives that part's score from 0 to 100.
score.components[].weight	number	Gives that part's weight from 0 to 100.
score.components[].rationale	string	Explains that part's score.
settings	object, optional	Echoes the settings used for the row.
settings.newsLookbackDays	integer	Gives the recent-news window used for company news.
settings.componentWeights	object	Holds the applied company weights.
settings.componentWeights.news	number	Gives the applied news weight.
settings.componentWeights.hiring	number	Gives the applied hiring weight.
settings.componentWeights.filingFundamentals	number	Gives the applied filing weight.
analysis	object	Holds the branch for the selected target.
sources	array	Lists public source links and the periods they cover.
sources[].source	string	Names the source kind.
sources[].url	URL string	Links to the public source used for the row.
sources[].period	object	Describes the source period or as-of date.
sources[].period.startDate	date string, optional	Gives the first date covered by the source.
sources[].period.endDate	date string, optional	Gives the last date covered by the source.
sources[].period.asOfDate	date string, optional	Gives the date described by a point-in-time source.
sources[].period.label	string	Names the source period.
sourceIssues	array, optional	Lists public sources that did not return data for the row.
sourceIssues[].source	string	Names the source with an issue.
sourceIssues[].message	string	Explains the source issue.
stalenessWarnings	array, optional	Warns about an old source period or delayed data.
stalenessWarnings[].source	string	Names the source with a freshness warning.
stalenessWarnings[].message	string	Explains the freshness warning.
stalenessWarnings[].periodEnd	date string	Gives the end date of the source period.
history	object, optional	Shows changes from a prior result for the same subject and target.
history.previousCollectedAt	date-time string	Gives the prior collection time.
history.scoreChange	number	Gives the current score minus the prior score.
history.classificationChanged	boolean	Says whether the classification changed.
history.componentChanges	array	Lists changes for signal parts found in both runs.
history.componentChanges[].name	string	Names the changed signal part.
history.componentChanges[].scoreChange	number	Gives the part's score change.
history.componentChanges[].summary	string	Explains the part's change.
collectedAt	date-time string	Gives the time when the row was collected.

Company analysis shape

The following fields are under analysis.company. The table includes company branches that can be absent when a public source does not provide data.

Field	Type	What it does
analysis.company	object	Holds company news, hiring, filing, market, insider, and related signals.
analysis.company.marketProfile	object	Holds basic public company profile details.
analysis.company.marketProfile.sector	string	Names the company's main sector.
analysis.company.marketProfile.industry	string	Names the company's main industry.
analysis.company.marketProfile.exchange	string	Names the exchange where the company is listed.
analysis.company.marketProfile.country	string	Gives the country linked to the company.
analysis.company.marketProfile.marketCap	number	Gives the market value at quote time.
analysis.company.marketProfile.marketCapCurrency	string	Gives the market-cap currency.
analysis.company.quote	object	Holds the latest public quote found for the company.
analysis.company.quote.price	number	Gives the quoted price.
analysis.company.quote.currency	string	Gives the quote currency.
analysis.company.quote.changePercent	number	Gives the quote-period price change in percent.
analysis.company.quote.asOf	date-time string	Gives the quote time.
analysis.company.news	object	Holds recent news coverage, sentiment, and speed.
analysis.company.news.articleCount	integer	Counts the news articles found.
analysis.company.news.publishers	array of strings	Lists publishers found in the news set.
analysis.company.news.sentiment	string	Labels the overall news sentiment.
analysis.company.news.sentimentScore	number	Gives the news sentiment score from -1 to 1.
analysis.company.news.velocity	object	Shows how fast news appeared in the review period.
analysis.company.news.velocity.articlesPerDay	number	Gives the average articles per day.
analysis.company.news.velocity.recentArticleCount	integer	Counts articles in the recent part of the period.
analysis.company.news.velocity.priorArticleCount	integer	Counts articles in the prior comparison period.
analysis.company.news.period	object	Gives the dates covered by the news review.
analysis.company.news.period.startDate	date string	Gives the first news date.
analysis.company.news.period.endDate	date string	Gives the last news date.
analysis.company.hiring	object	Holds current job openings and the hiring mix.
analysis.company.hiring.openingCount	integer	Counts current open jobs.
analysis.company.hiring.mix	array	Groups open jobs by job function.
analysis.company.hiring.mix[].function	string	Names a job function.
analysis.company.hiring.mix[].openingCount	integer	Counts open jobs in that function.
analysis.company.hiring.change	object	Shows changes since a prior company run.
analysis.company.hiring.change.newOpenings	integer	Counts jobs found now but not in the prior snapshot.
analysis.company.hiring.change.removedOpenings	integer	Counts prior jobs not found now.
analysis.company.hiring.change.netChange	integer	Gives new openings minus removed openings.
analysis.company.hiring.change.comparedAt	date-time string	Gives the prior comparison time.
analysis.company.filingFundamentals	object	Holds annual revenue and gross-margin changes from a filing.
analysis.company.filingFundamentals.periodEnd	date string	Gives the end of the annual filing period.
analysis.company.filingFundamentals.annualRevenue	object	Holds reported annual revenue.
analysis.company.filingFundamentals.annualRevenue.amount	number	Gives the annual revenue amount.
analysis.company.filingFundamentals.annualRevenue.currency	string	Gives the annual revenue currency.
analysis.company.filingFundamentals.revenueChangePercent	number	Gives year-over-year revenue change in percent.
analysis.company.filingFundamentals.grossMarginPercent	number	Gives gross margin in percent.
analysis.company.filingFundamentals.grossMarginChangePoints	number	Gives year-over-year gross-margin change in percentage points.
analysis.company.institutional	object	Holds institutional convergence from quarterly 13F holdings.
analysis.company.institutional.periodEnd	date string	Gives the end of the holdings period.
analysis.company.institutional.convergenceScore	number	Gives the institutional convergence score from 0 to 100.
analysis.company.institutional.institutionCount	integer	Counts institutions in the holdings data.
analysis.company.institutional.direction	string	Labels the direction of institutional convergence.
analysis.company.insider	object	Holds directional public Form 4 insider activity.
analysis.company.insider.transactionCount	integer	Counts insider transactions found.
analysis.company.insider.buyCount	integer	Counts insider buys.
analysis.company.insider.sellCount	integer	Counts insider sells.
analysis.company.insider.netValue	number	Gives the net reported value of insider activity.
analysis.company.insider.currency	string	Gives the net-value currency.
analysis.company.insider.sentiment	string	Labels the direction of insider activity.
analysis.company.insider.period	object	Gives the dates covered by insider data.
analysis.company.insider.period.startDate	date string	Gives the first insider-activity date.
analysis.company.insider.period.endDate	date string	Gives the last insider-activity date.
analysis.company.filingContext	object	Holds material filing events and risk factors.
analysis.company.filingContext.materialEvents	array	Lists material events found in public filings.
analysis.company.filingContext.materialEvents[].type	string	Names the filing-event type.
analysis.company.filingContext.materialEvents[].filedAt	date string	Gives the filing date.
analysis.company.filingContext.materialEvents[].summary	string	Summarizes the filing event.
analysis.company.filingContext.riskFactors	array	Lists risk factors named in public filings.
analysis.company.filingContext.riskFactors[].title	string	Names a risk factor.
analysis.company.filingContext.riskFactors[].summary	string	Summarizes the risk factor.
analysis.company.innovationContext	object	Holds company patent and research-and-development hiring context.
analysis.company.innovationContext.patentActivity	object	Holds recent public patent activity.
analysis.company.innovationContext.patentActivity.patentCount	integer	Counts patents in the review period.
analysis.company.innovationContext.patentActivity.periodEnd	date string	Gives the end of the patent period.
analysis.company.innovationContext.researchAndDevelopmentHiring	object	Holds research-and-development job openings.
analysis.company.innovationContext.researchAndDevelopmentHiring.openingCount	integer	Counts research-and-development openings.
analysis.company.innovationContext.researchAndDevelopmentHiring.periodEnd	date string	Gives the end of the hiring period.
analysis.company.innovationContext.momentumScore	number	Gives the innovation momentum score from 0 to 100.

Company row example

This shortened genuine row is from the successful current-beta company run. The string value "..." marks omitted fields from the same real row.

{
  "target": "company",
  "subject": {
    "name": "Apple Inc.",
    "symbol": "AAPL",
    "scope": "company"
  },
  "score": {
    "value": 83,
    "classification": "strong_positive",
    "confidence": 0.7100000000000001,
    "rationale": "news: 100 articles with mixed sentiment and 3.333 articles/day. filing_fundamentals: Revenue changed 81.54% and gross margin changed 8.44 points. insider: 0 buys and 5 sells in current Form 4 rows. market_profile: Quote change over the Yahoo window is 2.5%.",
    "components": [
      {
        "name": "news",
        "score": 70,
        "weight": 40,
        "rationale": "100 articles with mixed sentiment and 3.333 articles/day."
      },
      "..."
    ]
  },
  "settings": "...",
  "analysis": {
    "company": {
      "marketProfile": {
        "sector": "Electronic Computers",
        "industry": "Electronic Computers",
        "exchange": "NasdaqGS",
        "country": "US"
      },
      "quote": {
        "price": 311,
        "currency": "USD",
        "asOf": "2026-08-05T13:30:00.000Z",
        "changePercent": 2.5
      },
      "news": {
        "articleCount": 100,
        "publishers": "...",
        "sentiment": "mixed",
        "sentimentScore": 0.07,
        "velocity": {
          "articlesPerDay": 3.333,
          "recentArticleCount": 100,
          "priorArticleCount": 0
        },
        "period": {
          "startDate": "2026-07-07",
          "endDate": "2026-08-06"
        }
      },
      "filingFundamentals": "...",
      "insider": "...",
      "filingContext": "...",
      "innovationContext": "..."
    }
  },
  "sources": [
    {
      "source": "company_news",
      "url": "https://news.google.com/rss/search?q=(AAPL%20OR%20%22Apple%20Inc.%22)%20when%3A30d&hl=en-US&gl=US&ceid=US:en",
      "period": {
        "label": "30-day Google News window",
        "startDate": "2026-07-07",
        "endDate": "2026-08-06"
      }
    },
    "..."
  ],
  "sourceIssues": [
    {
      "source": "company_jobs",
      "message": "No supported public source mapping is available for this target."
    },
    {
      "source": "institutional_holdings",
      "message": "No supported public source mapping is available for this target."
    },
    {
      "source": "patent_records",
      "message": "The public source could not be reached after safe retries."
    }
  ],
  "stalenessWarnings": [
    {
      "source": "insider_filings",
      "message": "This insider filings source period is 51 days old.",
      "periodEnd": "2026-06-16"
    }
  ],
  "collectedAt": "2026-08-06T02:28:33.597Z",
  "history": "..."
}

Sector analysis shape

The following fields are under analysis.sector.

Field	Type	What it does
analysis.sector	object	Holds descriptive sector rotation and market activity signals.
analysis.sector.rotation	object	Holds the direction and score of sector rotation.
analysis.sector.rotation.signal	string	Labels the descriptive sector flow signal.
analysis.sector.rotation.score	number	Gives the rotation score from 0 to 100.
analysis.sector.rotation.rationale	string	Explains the rotation signal.
analysis.sector.sectorReturnPercent	number	Gives the sector return for the review period.
analysis.sector.relativeStrengthPercent	number	Gives the sector return compared with its reference market.
analysis.sector.congressionalActivity	object	Holds disclosed congressional trading linked to the sector.
analysis.sector.congressionalActivity.buyCount	integer	Counts disclosed buys.
analysis.sector.congressionalActivity.sellCount	integer	Counts disclosed sells.
analysis.sector.congressionalActivity.netValue	number	Gives the net disclosed trade value.
analysis.sector.congressionalActivity.currency	string	Gives the net-value currency.
analysis.sector.congressionalActivity.periodEnd	date string	Gives the end of the trade period.

Sector row example

This complete row is from the successful current-beta sector run:

{
  "target": "sector",
  "subject": {
    "name": "Technology sector",
    "scope": "sector"
  },
  "score": {
    "value": 70,
    "classification": "positive",
    "confidence": 0.63,
    "rationale": "sector: XLK returned 5.79% versus 3.79% for SPY. congressional: 0 congressional buys and 1 sells.",
    "components": [
      {
        "name": "sector",
        "score": 70,
        "weight": 100,
        "rationale": "XLK returned 5.79% versus 3.79% for SPY."
      },
      {
        "name": "congressional",
        "score": 40,
        "weight": 0,
        "rationale": "0 congressional buys and 1 sells."
      }
    ]
  },
  "settings": {
    "newsLookbackDays": 30,
    "componentWeights": {
      "news": 40,
      "hiring": 30,
      "filingFundamentals": 30
    }
  },
  "analysis": {
    "sector": {
      "rotation": {
        "signal": "inflow",
        "score": 70,
        "rationale": "XLK returned 5.79% versus 3.79% for SPY."
      },
      "sectorReturnPercent": 5.79,
      "relativeStrengthPercent": 2,
      "congressionalActivity": {
        "buyCount": 0,
        "sellCount": 1,
        "netValue": 0,
        "currency": "USD",
        "periodEnd": "2026-08-06"
      }
    }
  },
  "sources": [
    {
      "source": "macro_indicators",
      "url": "https://query1.finance.yahoo.com/v8/finance/chart/XLK?range=5d&interval=1d",
      "period": {
        "label": "Yahoo sector ETF comparison",
        "asOfDate": "2026-08-06"
      }
    },
    {
      "source": "congressional_trades",
      "url": "https://disclosures-clerk.house.gov/public_disc/ptr-pdfs/2025/20032062.pdf",
      "period": {
        "label": "House periodic disclosure 20032062",
        "endDate": "2026-08-06"
      }
    }
  ],
  "sourceIssues": [],
  "stalenessWarnings": [],
  "collectedAt": "2026-08-06T02:29:42.374Z",
  "history": {
    "previousCollectedAt": "2026-08-06T01:29:51.568Z",
    "scoreChange": 0,
    "classificationChanged": false,
    "componentChanges": [
      {
        "name": "sector",
        "scoreChange": 0,
        "summary": "Current 70; previous 70."
      },
      {
        "name": "congressional",
        "scoreChange": 0,
        "summary": "Current 40; previous 40."
      }
    ]
  }
}

Macro analysis shape

The following fields are under analysis.macro.

Field	Type	What it does
analysis.macro	object	Holds a macro regime and the public indicators behind it.
analysis.macro.regime	string	Labels the current macro regime.
analysis.macro.indicators	array	Lists domestic and global indicators used for the regime.
analysis.macro.indicators[].name	string	Names the indicator.
analysis.macro.indicators[].region	string	Names the region covered.
analysis.macro.indicators[].value	number	Gives the reported indicator value.
analysis.macro.indicators[].unit	string	Gives the indicator unit.
analysis.macro.indicators[].direction	string	Describes the direction signaled by the indicator.
analysis.macro.indicators[].periodEnd	date string	Gives the end of the indicator period.

Macro row example

This complete row is from the successful current-beta macro run:

{
  "target": "macro",
  "subject": {
    "name": "US and global macro",
    "scope": "macro"
  },
  "score": {
    "value": 70,
    "classification": "positive",
    "confidence": 0.5900000000000001,
    "rationale": "macro: Macro regime is expansion.",
    "components": [
      {
        "name": "macro",
        "score": 70,
        "weight": 100,
        "rationale": "Macro regime is expansion."
      }
    ]
  },
  "settings": {
    "newsLookbackDays": 30,
    "componentWeights": {
      "news": 40,
      "hiring": 30,
      "filingFundamentals": 30
    }
  },
  "analysis": {
    "macro": {
      "regime": "expansion",
      "indicators": [
        {
          "name": "US unemployment rate",
          "region": "domestic",
          "value": 4.2,
          "unit": "percent",
          "direction": "improving",
          "periodEnd": "2026-06-01"
        },
        {
          "name": "US CPI index",
          "region": "domestic",
          "value": 332.568,
          "unit": "index",
          "direction": "stable",
          "periodEnd": "2026-06-01"
        },
        {
          "name": "World GDP growth",
          "region": "global",
          "value": 2.92127318539153,
          "unit": "percent",
          "direction": "improving",
          "periodEnd": "2025-12-31"
        }
      ]
    }
  },
  "sources": [
    {
      "source": "macro_indicators",
      "url": "https://fred.stlouisfed.org/graph/fredgraph.csv?id=UNRATE&cosd=2025-01-01&coed=2026-08-06",
      "period": {
        "label": "FRED unemployment",
        "endDate": "2026-06-01"
      }
    },
    {
      "source": "macro_indicators",
      "url": "https://fred.stlouisfed.org/graph/fredgraph.csv?id=CPIAUCSL&cosd=2025-01-01&coed=2026-08-06",
      "period": {
        "label": "FRED CPI",
        "endDate": "2026-06-01"
      }
    },
    {
      "source": "macro_indicators",
      "url": "https://api.worldbank.org/v2/country/WLD/indicator/NY.GDP.MKTP.KD.ZG?format=json&per_page=5",
      "period": {
        "label": "World Bank global GDP",
        "endDate": "2025-12-31"
      }
    }
  ],
  "sourceIssues": [],
  "stalenessWarnings": [
    {
      "source": "macro_indicators",
      "message": "This macro indicators source period is 218 days old.",
      "periodEnd": "2025-12-31"
    }
  ],
  "collectedAt": "2026-08-06T02:29:31.983Z",
  "history": {
    "previousCollectedAt": "2026-08-06T00:52:51.895Z",
    "scoreChange": 0,
    "classificationChanged": false,
    "componentChanges": [
      {
        "name": "macro",
        "scoreChange": 0,
        "summary": "Current 70; previous 70."
      }
    ]
  }
}

Consumer analysis shape

The following fields are under analysis.consumer.

Field	Type	What it does
analysis.consumer	object	Holds consumer financial stress and its public indicators.
analysis.consumer.stressScore	number	Gives the consumer stress score from 0 to 100.
analysis.consumer.classification	string	Labels the level of consumer stress.
analysis.consumer.indicators	array	Lists public indicators used for the stress score.
analysis.consumer.indicators[].name	string	Names the consumer indicator.
analysis.consumer.indicators[].value	number	Gives the reported indicator value.
analysis.consumer.indicators[].unit	string	Gives the indicator unit.
analysis.consumer.indicators[].direction	string	Describes the direction signaled by the indicator.
analysis.consumer.indicators[].periodEnd	date string	Gives the end of the indicator period.

Consumer row example

This complete row is from the successful current-beta consumer run:

{
  "target": "consumer",
  "subject": {
    "name": "Consumer conditions",
    "scope": "consumer"
  },
  "score": {
    "value": 0,
    "classification": "strong_negative",
    "confidence": 0.5900000000000001,
    "rationale": "consumer: Consumer stress score is 100.",
    "components": [
      {
        "name": "consumer",
        "score": 0,
        "weight": 100,
        "rationale": "Consumer stress score is 100."
      }
    ]
  },
  "settings": {
    "newsLookbackDays": 30,
    "componentWeights": {
      "news": 40,
      "hiring": 30,
      "filingFundamentals": 30
    }
  },
  "analysis": {
    "consumer": {
      "stressScore": 100,
      "classification": "high",
      "indicators": [
        {
          "name": "CFPB complaints",
          "value": 16906013,
          "unit": "complaints",
          "direction": "higher_stress",
          "periodEnd": "2026-08-05"
        },
        {
          "name": "US unemployment rate",
          "value": 4.2,
          "unit": "percent",
          "direction": "stable",
          "periodEnd": "2026-06-01"
        },
        {
          "name": "University of Michigan sentiment",
          "value": 49.5,
          "unit": "index",
          "direction": "higher_stress",
          "periodEnd": "2026-06-01"
        }
      ]
    }
  },
  "sources": [
    {
      "source": "consumer_indicators",
      "url": "https://www.consumerfinance.gov/data-research/consumer-complaints/search/api/v1/?size=1&from=0&sort=created_date_desc",
      "period": {
        "label": "latest CFPB complaint",
        "asOfDate": "2026-08-05"
      }
    },
    {
      "source": "consumer_indicators",
      "url": "https://fred.stlouisfed.org/graph/fredgraph.csv?id=UNRATE&cosd=2025-01-01&coed=2026-08-06",
      "period": {
        "label": "FRED unemployment",
        "endDate": "2026-06-01"
      }
    },
    {
      "source": "consumer_indicators",
      "url": "https://fred.stlouisfed.org/graph/fredgraph.csv?id=UMCSENT&cosd=2025-01-01&coed=2026-08-06",
      "period": {
        "label": "FRED sentiment",
        "endDate": "2026-06-01"
      }
    }
  ],
  "sourceIssues": [],
  "stalenessWarnings": [],
  "collectedAt": "2026-08-06T02:29:32.922Z",
  "history": {
    "previousCollectedAt": "2026-08-06T00:52:42.872Z",
    "scoreChange": 0,
    "classificationChanged": false,
    "componentChanges": [
      {
        "name": "consumer",
        "scoreChange": 0,
        "summary": "Current 0; previous 0."
      }
    ]
  }
}

Innovation analysis shape

The following fields are under analysis.innovation.

Field	Type	What it does
analysis.innovation	object	Holds patent activity and research-and-development hiring signals.
analysis.innovation.momentumScore	number	Gives the innovation momentum score from 0 to 100.
analysis.innovation.classification	string	Labels innovation momentum.
analysis.innovation.patentActivity	object	Holds recent public patent activity.
analysis.innovation.patentActivity.patentCount	integer	Counts patents in the review period.
analysis.innovation.patentActivity.periodEnd	date string	Gives the end of the patent period.
analysis.innovation.researchAndDevelopmentHiring	object	Holds research-and-development job openings.
analysis.innovation.researchAndDevelopmentHiring.openingCount	integer	Counts research-and-development openings.
analysis.innovation.researchAndDevelopmentHiring.periodEnd	date string	Gives the end of the hiring period.

Innovation row example

This complete row is from the successful current-beta innovation run:

{
  "target": "innovation",
  "subject": {
    "name": "Cloudflare, Inc.",
    "symbol": "NET",
    "scope": "innovation"
  },
  "score": {
    "value": 100,
    "classification": "strong_positive",
    "confidence": 0.5900000000000001,
    "rationale": "innovation: 124810 public patent search results and 293 R&D openings.",
    "components": [
      {
        "name": "innovation",
        "score": 100,
        "weight": 100,
        "rationale": "124810 public patent search results and 293 R&D openings."
      }
    ]
  },
  "settings": {
    "newsLookbackDays": 30,
    "componentWeights": {
      "news": 40,
      "hiring": 30,
      "filingFundamentals": 30
    }
  },
  "analysis": {
    "innovation": {
      "momentumScore": 100,
      "classification": "strong_positive",
      "patentActivity": {
        "patentCount": 124810,
        "periodEnd": "2026-08-06"
      },
      "researchAndDevelopmentHiring": {
        "openingCount": 293,
        "periodEnd": "2026-08-06"
      }
    }
  },
  "sources": [
    {
      "source": "patent_records",
      "url": "https://patents.google.com/xhr/query?url=q%3DCloudflare%2C%20Inc.&exp=",
      "period": {
        "label": "Google Patents public search result",
        "asOfDate": "2026-08-06"
      }
    },
    {
      "source": "company_jobs",
      "url": "https://boards-api.greenhouse.io/v1/boards/cloudflare/jobs?content=false",
      "period": {
        "label": "current public Greenhouse openings",
        "asOfDate": "2026-08-06"
      }
    }
  ],
  "sourceIssues": [],
  "stalenessWarnings": [],
  "collectedAt": "2026-08-06T02:29:37.548Z",
  "history": {
    "previousCollectedAt": "2026-08-06T00:52:56.231Z",
    "scoreChange": 0,
    "classificationChanged": false,
    "componentChanges": [
      {
        "name": "innovation",
        "scoreChange": 0,
        "summary": "Current 100; previous 100."
      }
    ]
  }
}

Cross-asset analysis shape

The following fields are under analysis.crossAsset.

Field	Type	What it does
analysis.crossAsset	object	Holds observational risk context across major asset groups.
analysis.crossAsset.riskRegime	string	Labels the current cross-asset risk regime.
analysis.crossAsset.assets	array	Lists quote and change context for each asset group.
analysis.crossAsset.assets[].assetClass	string	Names the asset group.
analysis.crossAsset.assets[].symbol	string	Gives the public symbol used for the quote.
analysis.crossAsset.assets[].value	number	Gives the latest value for the asset group.
analysis.crossAsset.assets[].changePercent	number	Gives the value change in percent for the quote period.
analysis.crossAsset.assets[].currency	string	Gives the value currency.
analysis.crossAsset.assets[].asOf	date-time string	Gives the quote time.
analysis.crossAsset.rationale	string	Explains the cross-asset risk label.

Cross-asset row example

This complete row is from the successful current-beta cross_asset run:

{
  "target": "cross_asset",
  "subject": {
    "name": "Cross-asset risk context",
    "scope": "cross_asset"
  },
  "score": {
    "value": 50,
    "classification": "mixed",
    "confidence": 0.5900000000000001,
    "rationale": "cross_asset: Cross-asset risk regime is normal.",
    "components": [
      {
        "name": "cross_asset",
        "score": 50,
        "weight": 100,
        "rationale": "Cross-asset risk regime is normal."
      }
    ]
  },
  "settings": {
    "newsLookbackDays": 30,
    "componentWeights": {
      "news": 40,
      "hiring": 30,
      "filingFundamentals": 30
    }
  },
  "analysis": {
    "crossAsset": {
      "riskRegime": "normal",
      "assets": [
        {
          "assetClass": "equities",
          "symbol": "SPY",
          "value": 769.7899780273438,
          "changePercent": 3.79,
          "currency": "USD",
          "asOf": "2026-08-05T13:30:00.000Z"
        },
        {
          "assetClass": "cryptoassets",
          "symbol": "BTC",
          "value": 64491,
          "changePercent": 0,
          "currency": "USD",
          "asOf": "2026-08-06T02:29:24.260Z"
        },
        {
          "assetClass": "foreign_exchange",
          "symbol": "EURUSD=X",
          "value": 1.1559356451034546,
          "changePercent": 0.31,
          "currency": "USD",
          "asOf": "2026-08-06T02:28:56.000Z"
        },
        {
          "assetClass": "volatility",
          "symbol": "^VIX",
          "value": 15.8100004196167,
          "changePercent": -7.49,
          "currency": "USD",
          "asOf": "2026-08-05T07:00:00.000Z"
        },
        {
          "assetClass": "rates",
          "symbol": "^TNX",
          "value": 4.616999626159668,
          "changePercent": -0.99,
          "currency": "USD",
          "asOf": "2026-08-05T12:20:00.000Z"
        }
      ],
      "rationale": "Volatility was 15.8100004196167; the observed risk regime is normal."
    }
  },
  "sources": [
    {
      "source": "cross_asset_quotes",
      "url": "https://query1.finance.yahoo.com/v8/finance/chart/SPY?range=5d&interval=1d",
      "period": {
        "label": "Yahoo equity quote window",
        "asOfDate": "2026-08-06"
      }
    },
    {
      "source": "cross_asset_quotes",
      "url": "https://api.coingecko.com/api/v3/simple/price?ids=bitcoin&vs_currencies=usd",
      "period": {
        "label": "CoinGecko spot quote",
        "asOfDate": "2026-08-06"
      }
    },
    {
      "source": "cross_asset_quotes",
      "url": "https://query1.finance.yahoo.com/v8/finance/chart/EURUSD%3DX?range=5d&interval=1d",
      "period": {
        "label": "Yahoo FX quote window",
        "asOfDate": "2026-08-06"
      }
    },
    {
      "source": "cross_asset_quotes",
      "url": "https://query1.finance.yahoo.com/v8/finance/chart/%5EVIX?range=5d&interval=1d",
      "period": {
        "label": "Yahoo volatility quote window",
        "asOfDate": "2026-08-06"
      }
    },
    {
      "source": "cross_asset_quotes",
      "url": "https://query1.finance.yahoo.com/v8/finance/chart/%5ETNX?range=5d&interval=1d",
      "period": {
        "label": "Yahoo rates quote window",
        "asOfDate": "2026-08-06"
      }
    }
  ],
  "sourceIssues": [],
  "stalenessWarnings": [],
  "collectedAt": "2026-08-06T02:29:24.261Z",
  "history": {
    "previousCollectedAt": "2026-08-06T00:52:49.686Z",
    "scoreChange": 0,
    "classificationChanged": false,
    "componentChanges": [
      {
        "name": "cross_asset",
        "scoreChange": 0,
        "summary": "Current 50; previous 50."
      }
    ]
  }
}

💳 Pricing

This Actor uses pay-per-event pricing. The current buyer-facing company signal charge applies when one evidence-linked company signal is saved for a submitted public company. Empty, setup, and diagnostic work are not described here as a company-signal charge. Check the pricing panel for the current tier rate.

🔌 Integrations

Use the dataset link in the run output to read the saved JSON rows in Apify or export them for a spreadsheet, notebook, or review workflow. Source URLs remain in each row so you can inspect the public data behind a signal.

Video guide

❓ FAQ

What is alternative data here?

Here, alternative data means public company and market indicators used with a score, rationale, and source links. The Actor does not promise private, paywalled, or proprietary datasets.

Can one run combine company, sector, and macro analysis?

No. Choose one target for each run. Use separate runs for separate analysis targets.

What happens to company fields for another target?

The companies, newsLookbackDays, and componentWeights fields apply to Company analysis. Other targets ignore them.

Can I change how much news, hiring, and filings affect a company score?

Yes. Set the three component weights from 0 to 100. The Actor scales the relative values so their total is 100.

Will every company have hiring data?

No. Company hiring fields depend on a supported public Greenhouse job board. The Actor does not guess an employer-board mapping; check sourceIssues when hiring data is not present.

What does confidence mean?

score.confidence is the schema's confidence value from 0 to 1. Read it with the score rationale, source periods, and source links. It is not a promise of accuracy or an investment recommendation.

What do source periods and freshness warnings tell me?

Each source can include the period it covers, while collectedAt shows when the row was saved. stalenessWarnings calls out an old source period or delayed data so you can judge how fresh the signal is.

Why can a source issue appear in a successful row?

sourceIssues lists a public source that did not return data for that row. Review the available analysis fields and the source links before using the signal.

Can I compare repeated company runs?

Yes. A later row can include history for the same subject and target, including score and component changes. The Actor does not provide historical backtesting or a guaranteed long-term history.

What does a cross-asset row mean?

It is observational context for equities, cryptoassets, foreign exchange, volatility, and rates. It is not a mathematical correlation measure, price forecast, or trading signal.

Does this Actor give investment advice?

No. It provides public-data research context and source links. It does not tell you what to buy, sell, or hold.

📝 Changelog

0.0: Initial release

🆘 Support

For issues, questions, or feature requests, file a ticket and I'll fix or implement it in less than 24h 🫡

🔗 Related Actors

• OpenInsider — Review public SEC Form 4 trades when a company signal needs insider-activity detail.
• SEC 13F Manager Quarterly Report Scraper — Add one manager's quarterly 13F holdings for institutional portfolio context.
• MarketWatch Scraper — Collect article-level financial news when a signal needs source text and ticker context.
• Barchart — Pull financial news or options snapshots for symbol and market context.
• Crypto Fear and Greed Index Scraper — Add daily crypto market sentiment rows to a cross-asset review.

Made with ❤️ by Maxime Dupré