Bigdata.com

Returns an interactive help interface that shows: - Information about user active subscription status - Available data packages and their content - Examples of user prompts **When to Use:** Use this tool when users ask about: - "Help" / "documentation" / "prompts examples" - "Subscription status" - "Available data packages" / "What data do I have access to?" / "What data can I use?"

bigdata_help

Returns a comprehensive ETF tearsheet in markdown covering fund facts, top holdings, price performance, historical returns, sector breakdown, and country allocation. **Prerequisite: Call find_securities first to get rp_entity_id (the "id" field from the response).** **Workflow for ETF tearsheet:** 1. Call find_securities → get "id" (use as rp_entity_id) and "type" (should be "ETF") 2. Call this tool with the rp_entity_id 3. Optionally call bigdata_search for supporting content **When to Use:** Use this tool when users ask about: - ETF overview, ETF snapshot, or ETF fund facts - ETF expense ratio, management fees, or total expense ratio (TER) - ETF assets under management (AUM) or fund size - ETF net asset value (NAV) - ETF holdings, top holdings, or portfolio composition - ETF sector breakdown, sector allocation, or sector exposure - ETF country allocation, geographic exposure, or country weighting - ETF price performance, returns, or historical performance - ETF risk metrics, volatility, max drawdown, or RSI - ETF premium or discount to NAV - ETF concentration, HHI, or top holdings weight - ETF provider, issuer, or fund company (e.g., SPDR, Vanguard, iShares) - ETF inception date, domicile, or ISIN - General information about a specific ETF (e.g., "tell me about SPY", "what is QQQ") **Data Returned:** The tearsheet is structured in seven sections, each as a markdown table: → **Fund Overview** (key fund facts from FMP): ISIN, Asset Class, Currency, Net Asset Value (NAV), Assets Under Management (AUM), Expense Ratio (TER), Holdings Count, Inception Date, Domicile, Provider, Average Volume, Listing Exchange → **Top 10 Holdings** (largest positions by weight from FMP): Rank, Asset Name, Shares, Market Value, Weight (%). Summary metrics: Top-10 Weight (%), HHI (Herfindahl-Hirschman Index for concentration) → **Price Performance** (real-time quote data from FMP): Currency, Last Price, Day Change (absolute + %), Market Cap, 52-Week High, 52-Week Low, 50-Day Moving Average, 200-Day Moving Average, Premium/Discount to NAV (%) → **Returns Overview** (computed from historical EOD prices from FMP): Period returns for 1D, 5D, 1M, 3M, 6M, YTD, 1Y, 3Y → **Risk & Technical** (risk metrics and technical indicators from FMP): Realized Volatility (20D), Realized Volatility (60D), Max Drawdown (1Y), RSI (14-period) for Current, 1D, 5D, 1M, 3M, 6M, 1Y → **Sector Breakdown** (sector weightings from FMP): Sector name and weight (%) for each sector the ETF holds → **Country Allocation** (country weightings from FMP): Country name and weight (%) for each country the ETF is exposed to **Data sources (LLM instruction):** When presenting ETF tearsheet results to the user, identify the data sources mentioned or implied in the tool response content and add a "Data sources" section at the bottom listing them.

bigdata_etf_tearsheet

This tool returns the document by its ID.

fetch

**Routing (hard rule):** Use **`find_securities`** for **ETFs**, **funds**, **securities**-oriented asks (including "find/list/search securities", fund tickers, ETF themes), and also for **any company or issuer lookup** (name, ticker, or domain) regardless of whether securities language is used. **Canonical example:** User asks **"Apple securities"** — **call `find_securities`**. User asks **"Apple"** or **"tell me about Apple"** — also **`find_securities`**, putting a single focused token in `query` (e.g. **"Apple"** or **"AAPL"** — follow the one-token rule). **Batch resolution:** When the user provides multiple tickers or names to look up (e.g. *"map AAPL, TSLA, NVDA to rp_ids"* or *"resolve these tickers: HYDR, PLUG, LIT"*), **fire all calls in parallel as a batch** — one `find_securities` call per ticker, all at the same time, not sequentially. Do not combine multiple tickers in a single `query`. Bare ticker symbols (e.g. `AAPL`, `SPY`, `HYDR`) always go here, never to **`get_securities`**. **Listed companies in results:** Matches can include **listed companies** and **ETFs**. **Returns REQUIRED data for downstream tools:** - **`id`:** entity identifier for follow-on tools that expect an entity id (e.g. `rp_entity_id` parameters) - Rows include **`security_type`** **COMPANY** vs **ETF** (and listing metadata for company-like rows where applicable) DO NOT run this tool again if: - The entity you need is already confirmed in this conversation thread - You already have the confirmed entity ID from a previous tool call Use this tool to: - Handle **"Apple securities"** and similar securities-explicit asks - Satisfy **"find securities"**, **"search for securities"**, **"list securities"**, **"which securities …"** (put the user's intent in `query`) - Resolve **ETF** or **fund** names and tickers (e.g. SPY, QQQ) to entity IDs - Resolve any **company** name, ticker, or domain to a RavenPack entity ID Use **`get_securities`** instead when the user provides exact security identifiers: **ISIN**, **CUSIP**, **SEDOL**, or **LISTING** (e.g. `XNAS:AAPL`). **Search scope:** By default, results can include **listed companies** and **ETFs**. Optional **`listing_type`**, **`countries`**, and **`sectors`** narrow the universe when the user specifies listing status, geography, or broad sector—use those structured fields rather than stuffing everything into **`query`** alone. For **`countries`**, pass **ISO 3166-1 alpha-2** codes (e.g. **US**, **ES**, **CA**, **GB**). Unknown or malformed entries are ignored (they do not apply a country filter). **Optional filters (use when the user narrows scope—do not bury everything in `query` only):** - **`countries`:** If they say **US**, **America**, **in Spain**, **UK-listed**, etc., set **`countries`** to the matching **alpha-2** list (e.g. `["US"]`, `["ES"]` — United Kingdom → **`GB`**, not `UK`). Never pass full country names in this argument. - **`sectors`:** If they mention **industry** or **sector** (e.g. finance, banks, tech, healthcare), map to one of these broad sector labels: **Basic Materials**, **Consumer Goods**, **Consumer Services**, **Energy**, **Financials**, **Health Care**, **Industrials**, **Real Estate**, **Technology**, **Telecommunications**, **Utilities**. Examples: "financial industry" / "banks" → **`["Financials"]`**. "tech" / "software" → **`["Technology"]`**. If you are not confident the label fits the user's intent, **omit `sectors`** and keep the industry wording in **`query`** only. - **`listing_type`:** When the user specifies **public** vs **private** listing, set **`PUBLIC`** or **`PRIVATE`** (not free text in **`query`**). - **`query` vs filters:** Put **one** issuer or securities-focused token in **`query`** (e.g. **Apple**, **Apple securities**, **AAPL** per rules). When **`listing_type`**, **`countries`**, and/or **`sectors`** are set, **avoid** repeating long listing, geography, or sector phrases inside **`query`**—let the filters carry that signal. **Composite example:** *"Apple in the US in the financial sector"* → **`find_securities`** with **`query`:** `"Apple"`, **`countries`:** `["US"]`, **`sectors`:** `["Financials"]`. Returns: A JSON **array** with a **single** element: an object with **`results`** (up to **5** matches) and **`metadata`**: `request_id` (UUID for correlating this tool call — not an end-user id) and `timestamp` (UTC ISO-8601). Each match in **`results`** includes `security_type`, `id`, identifiers, etc. If the top hit is wrong, inspect the remaining **`results`** before re-querying.

find_securities

Returns a comprehensive company tearsheet with financial data, market intelligence, and analyst coverage. **⚠️ PREREQUISITE: Call find_securities first to get rp_entity_id and listing_type.** **Tearsheet routing by security_type (from find_securities):** - security_type "COMPANY" → call this tool (bigdata_company_tearsheet) - security_type "ETF" → call bigdata_etf_tearsheet instead - security_type "BOND" → no tearsheet available **Workflow for company tearsheet:** 1. Call find_securities → check security_type. Only proceed here if security_type is "COMPANY". 2. Read "listing_type" from the result ("PUBLIC" → "Public", "PRIVATE" → "Private") — this is company_type. 3. Call this tool with rp_entity_id and company_type. 4. Optionally call bigdata_search for supporting content. **⚠️ CRITICAL — Never infer company_type from training knowledge:** The listing classification comes from RavenPack's Point-in-Time (PiT) entity database — it is the authoritative source and will always be present for company entities. It may differ from your training knowledge (e.g. a company you believe is private may be listed, or may have financial data from a previous listing period). Always use the value from find_securities. Never guess. **When to Use:** Company financials, earnings, revenue, valuation, balance sheet, cash flow, analyst ratings, price targets, ESG data, risk assessment, real time sentiment and media attention, or any financial analysis. **Data Returned by Company Type:** → PUBLIC companies (from financial data APIs): • Company profile & real-time quote (price, market cap, volume) • C-level leadership: the people leading the company, including the executive directory, board composition, and management stats • Price performance (52-week range, moving averages, price changes over time) • Competitors comparison (symbol, price, market cap) • Financial statements (income, balance sheet, cash flow) • Key metrics & ratios (P/E, ROE, ROA, debt ratios, margins) • Analyst ratings & recommendations (Strong Buy/Buy/Hold/Sell/Strong Sell) • Analyst price targets (consensus, median, high, low) • Analyst estimates (forward revenue & EPS projections for next 8 quarters) • Latest earnings release (actual vs estimated, surprise %) • Earnings calendar & upcoming earnings dates • Dividend history (dates, amounts, yields, frequency) • Revenue segmentation by product and geography • Sentiment data (last 24h real-time, company-specific news) • Fund trends & institutional holdings (top buyers/sellers, position changes, options activity) • ESG performance scores (Environmental, Social, Governance scores & classifications) • ESG historical trends (yearly ESG scores, performance buckets, sector comparisons) • Workforce signals & employee trend metrics: modeled employee counts and net in/out workforce changes with time-series comparisons (MoM, YoY, trailing-12-month), enabling company growth and contraction analysis regarding job market trends. → PRIVATE companies: • Company overview (legal name, status, founded date, headcount, tags, founders, description) • Contact details (phone, email) & headquarters location (region, country, categories) • Web & social links (website, LinkedIn, Twitter/X, Facebook) • Crunchbase rank with trend changes (7/30/90-day) • Sentiment data (last 24h real-time, company-specific news) • Leadership team (executives, board members, advisors with roles and start dates) • Funding rounds (valuation, total raised, round details with investors and lead investors) • Investments made & acquisitions (target companies, amounts, status) • Founder profiles (investment activity, portfolio, exits) • Workforce signals & employee trend metrics: modeled employee counts and net in/out workforce changes with time-series comparisons (MoM, YoY, trailing-12-month), enabling company growth and contraction analysis regarding job market trends. **Filtering:** The `sections` parameter exists for cases where the user EXPLICITLY references specific sections by name or concept. Do NOT use it for general tearsheet requests — omit it to return the complete tearsheet. **Data sources (LLM instruction):** When presenting the tearsheet results to the user, identify the data sources mentioned or implied in the tool response content and add a "Data sources" section at the bottom listing them.

bigdata_company_tearsheet

**PREFERRED TOOL for any explicit sentiment request.** Use this tool whenever the user asks for sentiment, news tone, media perception, or how the media views a company (e.g. "get the sentiment for Apple", "what is the sentiment on Tesla", "show Apple's media sentiment"). Returns a real-time media sentiment analysis for a company as a markdown report. More complete and detailed than the sentiment summary included in the company tearsheet. The report includes: - Sentiment score and direction (bullish / bearish / neutral) - Media attention level over recent periods - An AI-generated narrative summarising the main sentiment drivers - Cited source articles supporting the narrative **You must call find_securities first** to obtain the rp_entity_id before calling this tool. Works for both public and private companies that have recent media coverage. **IMPORTANT:** Present the tool output exactly as returned — do not reformat, summarise, or omit any part of the markdown report.

bigdata_sentiment_tearsheet

Returns a professionally formatted markdown calendar of corporate events including earnings announcements, conferences and IPO listings. **Output Format:** The tool returns a markdown document with the following structure: 1. **Header Section:** - Title: "# Events Calendar" - Metadata recap: timestamp, date range (From/To), applied filters (countries, exchanges) 2. **Earnings Section (📊):** Markdown table with columns: TICKER | COMPANY NAME | RELEASE DATE | EARNINGS CALL TIME | PERIOD - Shows company ticker symbols and full company names - Earnings call times displayed in UTC timezone - Fiscal period (Q1, Q2, Q3, Q4, H1, H2) - Events organized chronologically by date 3. **Conferences Section (🎤):** Markdown table with columns: TICKER | COMPANY NAME | DATE | TIME | NAME - Includes investor days, analyst meetings, conference presentations - Event names (e.g., "Investor Day 2026", "AGM 2026") - Times displayed in UTC timezone 4. **IPOs Section (🔔):** present when the results include IPO listings Markdown table with columns: TICKER | COMPANY NAME | LISTING DATE | NAME - Upcoming and recently priced US initial public offerings - NO time column: an IPO is dated to the day, so report the listing date only - The offering status is the title prefix ("Priced:", "Expected:", "Withdrawn:") - A company that has not started trading yet may have no entity record. Those offerings are grouped under the single rp_entity_id "NO_MAP", and their ticker and company name come from the offering itself. Treat them as valid results, not errors, and never pass "NO_MAP" back as an rp_entity_id — it is a bucket of several companies, not one entity. **Unknown values in any table:** a TICKER or COMPANY NAME cell reading "–" (en dash) means no ticker is available for that company, or the company is not covered. The row itself is a real event: present it with whatever identifier it does carry, rather than reporting an error. **Default Behavior:** - If NO parameters provided: Returns next 7 days of events from today - Categories default to all of them, so an unfiltered calendar includes earnings calls, conference calls and IPO listings - Automatic mode selection: • **Calendar Mode** (chronological): Used for discovery queries (multiple companies, country filters) • **Company Mode** (per-company grouping): Used for single company queries **Workflow & Prerequisites for events calendar:** For SPECIFIC companies: 1. FIRST: Call find_securities tool to get RavenPack Entity IDs 2. THEN: Pass entity IDs to rp_entity_ids parameter For MARKET-WIDE screening: - Omit rp_entity_ids and use filters (countries and exchanges) **When to Use This Tool:** - "What are Apple's upcoming earnings?" → Get entity ID first, then call with rp_entity_ids - "Show me US earnings this week" → Use countries: ["US"] - "NYSE earnings calendar for next 7 days" → Use exchanges: ["XNYS"] - "Japanese market events in January" → Use countries: ["JP"], start_date/end_date for January - "What IPOs are coming up this month?" → Use categories: ["ipos-calendar"] with start_date/end_date **Key Features:** - Company enrichment: Ticker symbols and full names added automatically where available - Timezone handling: All times displayed in UTC for consistency - Smart filtering: Combine multiple filters (countries, exchanges, date ranges) - Category filtering: Separate or combine earnings-call, conference-call and ipos-calendar events - Professional formatting: Tables, headers, and visual indicators (📊 🎤) **Data sources (LLM instruction):** When presenting the calendar results to the user, identify the data sources mentioned or implied in the tool response content and add a "Data sources" section at the bottom listing them.

bigdata_events_calendar

Returns a comprehensive country economic tearsheet with a sectoral macroeconomic overview, economic calendar data, G7 peer comparison, market indices, currency information, and US Treasury yields. **When to Use:** Use this tool when users ask about: - Upcoming economic events or recent economic releases - Economic calendar events, upcoming economic releases, or economic indicators - Country economic data, GDP, CPI, unemployment rates, interest rates - Economic comparisons between countries (G7 peer comparison) - Sector-specific economic data (housing, manufacturing, retail, trade, energy, etc.) - Central bank decisions, interest rates, or monetary policy - Fiscal policy, government budget, or debt data - Government securities auctions or bond auction results - Stock market indices, market performance, or equity market data for a country - Comparisons between a country's primary index and regional markets - Currency data, forex rates, or exchange rates for a country's base currency - Currency performance, trends, and cross-currency positioning - US Treasury yields, yield curve data, or bond market information (US ONLY) - Yield curve analysis, spread analysis, or interest rate trends for US Treasuries **Data Returned:** - Upcoming Events: Economic calendar events - Macroeconomic Overview: Sectoral breakdown of recent economic indicators, organized into: • GDP & Growth • Labor Market • Inflation & Prices • Consumer & Business Sentiment • Manufacturing & Services • Housing Market • Retail & Consumer Spending • Trade & International • Inventories & Supply Chain • Credit & Monetary • Central Bank & Monetary Policy • Regional Economic Indicators • Energy & Commodities • Government Securities Auctions • Fiscal Policy Each section shows the latest releases with actual vs. consensus values, surprise %, frequency, and impact level. - Country Comparison: G7 peer comparison table with key economic indicators: • GDP Growth (QoQ, YoY, Annualized) • CPI (YoY) • Unemployment Rate • Interest Rate - Market Indices: Real-time stock market index data including: • Primary Index: Country's main stock market index (e.g., S&P 500 for US, DAX for Germany) • Regional Comparisons: Related regional indices for context • Metrics: Current price, daily change, % change, 52-week high/low, 50-day and 200-day moving averages - Currencies: Real-time forex market data including: • Spot Overview: Reference pair, current spot price, previous close, 24h % change, direction • Trend & Momentum: 50-day MA, 200-day MA, MA spread, distance to 52-week high/low • Performance Snapshot: Returns over multiple horizons (1D, 5D, 1M, 3M, YTD, 1Y) with trend classification • Cross-Currency Positioning: Multiple currency pairs with rates, previous close, 24h % change, and strength indicators relative to the country's base currency - Yields (US ONLY): Real-time US Treasury yield curve data including: • Yield Curve Overview: Multiple maturities (1M, 3M, 6M, 1Y, 2Y, 3Y, 5Y, 7Y, 10Y, 20Y, 30Y) • Current Rates: Latest yield rates for each maturity • Daily Changes: Basis point changes and percentage changes from previous close • Yield Curve Analysis: Spread analysis (10Y-2Y, 30Y-2Y) and curve shape indicators • Historical Context: Comparison to recent highs/lows and trend indicators **IMPORTANT - Country Parameter:** - This tool accepts ONLY ONE country at a time - If the user mentions a specific country (e.g., "US", "UK", "Germany", "France"), use that country code in the `country` parameter - If the user mentions multiple countries, use only the first/primary country mentioned - Use the exact 2-letter country codes listed below (e.g., "US" for United States, "DE" for Germany, "EMU" for Eurozone) **Data sources (LLM instruction):** When presenting the country tearsheet results to the user, identify the data sources mentioned or implied in the tool response content and add a "Data sources" section at the bottom listing them.

bigdata_country_tearsheet

Resolves one or more **security identifiers** to **issuer** company records from the knowledge graph (not for fuzzy name search — use **`find_securities`** for company or ETF names, tickers, and themes). **When to use** - User provides exact structured identifiers: **CUSIP** `037833100`, **ISIN** `US0378331005`, **SEDOL** `2046251`, **LISTING** `XNAS:AAPL` (exchange MIC + ":" + symbol). - You already have exact identifiers and need rp_company_id, company profile, and cross-refs. **Do NOT use for bare ticker symbols** (e.g. `AAPL`, `SPY`, `QQQ`, `HYDR`, `PLUG`). A LISTING identifier requires the full `EXCHANGE:TICKER` format with a colon (e.g. `XNAS:AAPL`). Plain tickers, company names, or ETF symbols → use **`find_securities`** instead. The API infers the type per id: length 12 → ISIN, 9 → CUSIP, 7 → SEDOL, or ":" → LISTING. Mixed shapes in one request are supported (batched by type). Returns **`results`** (map of each requested identifier → a typed object or ``null`` if unknown or if the id failed shape validation), plus **`metadata`**: `request_id` is the unique id for this MCP HTTP request (UUID), not the end-user id — plus `timestamp` (UTC ISO-8601). If some ids are malformed, **`message`** explains which were skipped. Well-formed ids are still resolved. If **all** ids are malformed, **`results`** is empty and data-tools is not called. Each resolved entry includes **`security_type`** ``COMPANY``, ``ETF``, or ``BOND``. ``ETF`` vs ``COMPANY`` follows knowledge-graph ``company_etf_type`` (``ETF`` or ``BUSINESS``). ``BOND`` applies when the row has ``security_class`` ``FIXED_INCOME`` or the inferred id type is ``BISIN`` / ``BCUSIP``. Bonds nest the issuer under ``details.company``. Identifier cross-reference lists are on flat ``COMPANY`` / ``ETF`` rows only. **Data sources (LLM instruction):** When presenting results, identify data sources implied in the payload and add a "Data sources" section.

get_securities

Returns a comprehensive market snapshot in markdown covering eight asset classes: global equity ETFs, equity sectors, major stock market indexes, commodities, fixed income bond ETFs, US Treasury yields, equity factors, and currencies (fiat + crypto). For each instrument the tearsheet shows current price and percentage changes over 1D, 5D, 1M, 3M, 6M, YTD, and 1Y. Note: equity data in Global Markets reflects ETF prices (e.g. SPY for US, EWG for Germany, EWJ for Japan), not the underlying index levels directly (S&P 500, DAX, Nikkei). ETF prices closely track their benchmark indexes and are a reliable proxy for country equity performance. Major Indexes shows the actual index levels. **When to Use:** Use this tool when users ask about: - "Market tearsheet", "market snapshot", "market screenshot", or "global markets" - How country or regional stock markets are performing (e.g. US market, European markets, Asian markets, Emerging Markets) - Global equity market performance, country stock market returns, or regional market comparisons - Which countries or regions are outperforming or underperforming (daily or over multiple periods) - A broad overview of worldwide market conditions - Major stock market index levels or performance — S&P 500, Dow Jones, NASDAQ, DAX, FTSE 100, Nikkei, etc. - Commodity prices or performance — oil, gas, gold, silver, copper, wheat, corn, coffee, etc. - Currency performance — major fiat pairs (EUR/USD, GBP/USD, USD/JPY, USD/CNY, etc.) or emerging market currencies - Crypto prices or performance — Bitcoin, Ethereum, Solana, XRP, BNB, etc. - Equity sector performance — Technology, Health Care, Financials, Energy, etc. - Fixed income / bond market performance — Treasury ETFs, corporate bonds, municipal bonds, TIPS, MBS, emerging market debt - US Treasury yield curve — current rates and changes for 1M, 3M, 6M, 1Y, 2Y, 5Y, 10Y, 20Y, 30Y maturities - Interest rate movements, yield curve shape, or rate changes over time - Equity factor performance — growth vs value, momentum, small-cap, quality, buybacks, etc. - Multi-period performance comparisons (5D, 1M, 3M, 6M, YTD, 1Y) across any of the above **Data Returned:** The tearsheet is structured in eight sections, each as a markdown table. Every row includes: name, ticker, current price, and percentage changes for 1D, 5D, 1M, 3M, 6M, YTD, and 1Y. → **Global Markets** (38 country/region equity ETFs, grouped by region): Americas: United States (SPY), Canada, Mexico, Brazil, Chile, Colombia, Argentina Europe: United Kingdom, Germany, France, Italy, Spain, Netherlands, Switzerland, Sweden, Poland Asia-Pacific: Japan, China, Hong Kong, South Korea, Taiwan, Australia, India, Singapore, Malaysia, Thailand, Indonesia, Philippines, New Zealand Mideast-Africa: South Africa, Israel, Turkey, Saudi Arabia, Qatar Other: Emerging Markets (EEM), Emerging Markets Vanguard (VWO), EAFE Developed ex-US (EFA), All World ex-US (VEU) → **Major Indexes** (38 stock market indexes, grouped by region): North America (11): S&P 500, Dow Jones Industrial Avg, NASDAQ Composite, NASDAQ 100, Russell 2000, Russell 1000, Wilshire 5000, NYSE Composite, CBOE Volatility Index (VIX), S&P/TSX Composite, S&P BMV IPC Europe (13): FTSE 100, DAX 40, CAC 40, Euro Stoxx 50, STOXX Europe 600, IBEX 35, FTSE MIB, AEX, SMI, OMX Stockholm 30, BEL 20, ATX, MOEX Russia Asia-Pacific (12): Nikkei 225, Hang Seng, S&P/ASX 200, KOSPI, TWSE (TAIEX), NIFTY 50, BSE SENSEX, STI Index, NZX 50, SET Index, Jakarta Composite, KLCI Other (5): Bovespa, Merval, JSE Top 40, EGX 30, Tadawul All Share → **Commodities** (30 instruments, grouped by sector): Energy (5): Crude Oil WTI, Brent Crude, Natural Gas, Gasoline RBOB, Heating Oil Metals (8): Gold, Silver, Platinum, Palladium, Micro Gold, Micro Silver, Copper, Aluminum Agricultural (17): Corn, Wheat, Soybeans, Soybean Oil, Soybean Meal, Oats, Rough Rice, Sugar, Coffee, Cocoa, Cotton, Orange Juice, Live Cattle, Feeder Cattle, Lean Hogs, Lumber, Class III Milk → **Currencies** (49 pairs, grouped by type): Fiat Currencies (34 pairs): Major pairs (EUR/USD, GBP/USD, USD/JPY, USD/CHF, AUD/USD, USD/CAD, NZD/USD), cross pairs (EUR/GBP, EUR/JPY, GBP/JPY, EUR/CHF, AUD/JPY, EUR/AUD, GBP/CHF, AUD/NZD, EUR/CAD, GBP/AUD, CAD/JPY), and emerging market pairs (USD/CNY, USD/CNH, USD/INR, USD/MXN, USD/BRL, USD/ZAR, USD/TRY, USD/KRW, USD/TWD, USD/SGD, USD/THB, USD/RUB, USD/PLN, USD/CLP, USD/IDR, USD/PHP) Cryptocurrencies (15): BTC/USD, ETH/USD, USDT, BNB/USD, SOL/USD, USDC, XRP/USD, ADA/USD, DOGE/USD, AVAX/USD, DOT/USD, LINK/USD, TRX/USD, MATIC/USD, LTC/USD → **Equity Sectors** (11 US sector ETFs): United States: Technology (XLK), Health Care (XLV), Financials (XLF), Consumer Discretionary (XLY), Communication Services (XLC), Industrials (XLI), Consumer Staples (XLP), Energy (XLE), Utilities (XLU), Real Estate (XLRE), Materials (XLB) → **Fixed Income** (26 bond ETFs, grouped by category): US Treasury Duration (7): 0-1Y Tsy (SHV), 1-3Y Tsy (SHY), 3-7Y Tsy (IEI), 7-10Y Tsy (IEF), 10-20Y Tsy (TLH), 20Y+ Tsy (TLT), Laddered Tsy (GOVI) US Government Agencies (7): US Tsy (GOVT), US TIPS (TIP), US Agencies (AGZ), Mortgage-Backed MBS (MBB), Ginnie Mae GNMA (GNMA), Municipals (MUB), Municipal Short-Term (SUB) US Corporate Credit (8): USD Aggregate Bond (AGG), Senior Loans (BKLN), High Grade Corp (LQD), High Yield Corp (HYG), Convertibles (CWB), Preferred Stock (PFF), HG Floating Corp (FLOT), HG Short-Term Corp (MINT) International Credit (4): Intl Treasuries (IGOV), Intl Aggregate Bond (BNDX), USD Emerging Markets (EMB), Local Emerging Markets (EMLC) → **Yields** (12 US Treasury maturities): Shows current yield and percentage-point changes for 1D, 5D, 1M, 3M, 6M, YTD, 1Y. Maturities: 1 Month, 2 Month, 3 Month, 6 Month, 1 Year, 2 Year, 3 Year, 5 Year, 7 Year, 10 Year, 20 Year, 30 Year → **Equity Factors** (20 factor ETFs, grouped by style, relative to S&P 500): Style (6): Growth (IWF), Value (IWD), Momentum (MTUM), Small-Cap (IJR), Low Volatility (USMV), High Dividend Yield (VYM) Qualitative (6): Buybacks (PKW), Spin-offs (CSD), Hedge Funds (GURU), IPOs (IPO), Quality (QUAL), Private Equity (PSP) Size & Style (8): Large-Cap Value (IVE), Large-Cap Growth (IVW), Mid-Cap Value (IJJ), Mid-Cap Core (IJH), Mid-Cap Growth (IJK), Small-Cap Value (IWN), Small-Cap Core (IWM), Small-Cap Growth (IWO) **Complement to bigdata_market_tearsheet:** For macro/economic context (GDP, CPI, interest rates, economic calendar) use bigdata_country_tearsheet instead. **Data sources (LLM instruction):** When presenting market tearsheet results to the user, identify the data sources mentioned or implied in the tool response content and add a "Data sources" section at the bottom listing them.

bigdata_market_tearsheet