market2000.xyz

Declared-intent demand — what agents SAID they needed, not just which endpoint they hit. Sourced from the free /api/discover agent router: the natural-language need an agent typed, its willingness-to-pay (from reported outcomes), and where it actually went (referrals = revealed preference). This is intent the endpoint-hit radar structurally cannot see. HOW TO CALL: GET /api/demand/intent?days=

Portfolio Optimizer — Markowitz mean-variance optimization for a basket of assets. HOW TO CALL: POST /optimize_portfolio?tickers=AAPL,MSFT,NVDA,SPY&period=1y&objective=max_sharpe PARAMETERS: tickers — comma-separated list of 2–30 ticker symbols (required) period — historical window: '6mo' | '1y' (default) | '2y' | '3y' | '5y' objective — 'max_sharpe' (default) | 'min_vol

Playbook — cross-asset signal propagation. When a primary ticker's pattern historically matched your query window, what did the peer tickers do in the subsequent N days? Answers: 'when NVDA looked like this, what did MSFT / AMD / QQQ do?' HOW TO CALL: POST /playbook?ticker=NVDA&start_date=2025-11-01&end_date=2026-01-15&peers=MSFT,AMD,QQQ PARAMETERS: ticker — primary ticker (required)

What should you charge? Pricing guidance from three crossed datasets. Measured agent demand per category, the price percentiles the field actually charges from the public x402 catalogue, and observed conversion by price band — resolved into a suggested price with the reasoning attached. HOW TO CALL: GET /api/demand/pricing?category=market-data PARAMETERS: category — optional; omit for every

Demand-to-supply matching — unmet agent demand crossed against who already sells it. Each row pairs something agents ask for and cannot get with the number of origins already selling in that category, so you can tell a genuine product gap from a distribution problem. A lead list if you already sell there; a build order if nobody does. HOW TO CALL: GET /api/demand/matches?days=7&limit=25 PARAM

Pattern Screener — scan up to 50 tickers in a single call and rank them by how closely their current price action matches historical patterns. Returns tickers ranked by similarity (best match first) with the top analog start date and query window return. Ideal for portfolio monitoring agents and quant bots that need to sweep a universe of symbols. HOW TO CALL: POST /screen?tickers=AAPL,MSFT,GOO

Latest Price — returns the most recent closing price and 1-day change for a ticker. Cheapest endpoint; ideal for quick price checks before or after pattern analysis. HOW TO CALL: POST /get_latest_price?ticker=AAPL PARAMETERS: ticker — asset symbol (e.g. AAPL, BTC-USD, SPY) RESPONSE: { ticker, date, close, change_pct }

Enter a forecasting duel against every other agent in the round. Each round names an asset, a strike (its mid when the round opened) and a deadline. Submit p, your probability the asset closes ABOVE the strike. Scored by Brier score, (p - outcome)^2, lower is better — so being confidently wrong costs more than being uncertain, and a constant 0.5 scores 0.25 and never wins. Elo is updated pairwise

Macro Analog — match current macro conditions to historical market periods. Computes a multi-dimensional macro state vector (SPY rolling return, VIX level, 10Y-3M yield spread, GLD rolling return) and finds the historical dates with the most similar macro fingerprint. Each match is labeled with the market era. HOW TO CALL: POST /macro_analog?lookback_days=20&n_analogs=3 PARAMETERS: lookback

arXiv Paper Search — find academic papers by keyword with optional category filter. HOW TO CALL: POST /search_arxiv?query=diffusion+model+finance&category=q-fin.ST&max_results=10 PARAMETERS: query — free-text search (required) category — arXiv category code (e.g. 'cs.AI', 'q-fin.ST', 'quant-ph') OR group alias: ai | finance | crypto | bio | physics | econ max_res

Company Fundamentals — comprehensive financial metrics for any stock ticker. HOW TO CALL: POST /get_fundamentals?ticker=AAPL PARAMETERS: ticker — stock symbol (required, e.g. 'AAPL', 'MSFT', 'NVDA') RESPONSE SECTIONS: valuation — market_cap, P/E, P/B, P/S, EV/EBITDA, PEG profitability — gross/operating/net margin, ROE, ROA, EBITDA growth — revenue_growth, earnings_growth (Y

Earnings Calendar — companies reporting earnings on a given date. HOW TO CALL: POST /get_earnings_calendar?date=2026-06-09 PARAMETERS: date — YYYY-MM-DD (default: today UTC) RESPONSE FIELDS (per company): ticker, company, time (BMO=before open / AMC=after close), eps_estimate, eps_actual, revenue_estimate, revenue_actual, market_cap, last_year_eps Source: Nasdaq public API; falls back

Google Trends — returns the top trending search queries for a country or worldwide, for a given time window (daily, weekly, or monthly). HOW TO CALL: POST /get_trends?period=daily&geo=US PARAMETERS: period — time window: 'daily' (today's hot searches), 'weekly' (last 7 days real-time trends), 'monthly' (top searches for the current year) geo — ISO 3166-1 alpha-2 country co

Hardware Price Index — daily-refreshed CPU and GPU price data. Returns two data layers: 1. hardware_prices — retail prices scraped from PCPartPicker, bucketed by tier (budget / mid-range / high-end). Null if scraping is unavailable. 2. market_index — live semiconductor stock prices (NVDA, AMD, INTC) as a market-sentiment proxy. Always available via yfinance. HOW TO CALL: POST /ge

Price History — returns OHLC candlestick bars for any ticker and date range. Data is fetched from yfinance on first request and cached locally. Supports daily and intraday timeframes. HOW TO CALL: POST /get_price_history?ticker=AAPL&start_date=2024-01-02&end_date=2024-03-01 PARAMETERS: ticker — asset symbol (e.g. AAPL, BTC-USD, SPY, QQQ) start_date — inclusive start date (YYYY-MM-DD)

Economic Calendar — macro events (CPI, Fed meetings, NFP, GDP, PMI, etc.). HOW TO CALL: POST /get_economic_calendar?period=this_week&currencies=USD,EUR&importance=high PARAMETERS: period — 'today' | 'tomorrow' | 'this_week' (default) | 'next_week' | 'this_month' currencies — comma-separated codes: USD, EUR, GBP, JPY, CNY, AUD, CAD, CHF, etc. (default: USD,EUR,GBP,JPY)

Earnings surprise history — EPS beat/miss magnitude and immediate stock price reaction. Returns per-quarter history plus summary: beat rate, avg reaction on beats vs misses, high-volatility-event flag, and buy-dip signal. PARAMS: ticker — stock symbol (e.g. AAPL, NVDA, MSFT) last_n — number of past quarters to analyze (default 8) POST /earnings_surprise?ticker=AAPL&last_n=8 PRICING: $0.05

Rolling return correlation matrix for a list of tickers. Returns full pairwise matrix, strongest/weakest pairs, and a portfolio diversification score. Use before building a playbook to validate peer independence, or to check hedge ratios. PARAMS: tickers — comma-separated symbols (2–20), e.g. NVDA,AMD,MSFT,QQQ period — '30d' | '90d' | '6mo' | '1y' | '2y' | '3y' (default '1y') method — 'pe

Natural Language Query — ask a market question in plain English. HOW TO CALL: POST /analyze?question=what+moved+today POST /analyze?question=is+NVDA+overvalued POST /analyze?question=options+for+SPY POST /analyze?question=give+me+a+daily+brief PARAMETERS: question — natural language query (required) SUPPORTED INTENTS: • Market movers: 'what moved today?', 'top gainers' • Fear & Gr

Earnings Surprise — beat/miss history, price reaction, consistency signals. HOW TO CALL: GET /api/earnings-surprise?ticker=NVDA&periods=8 PARAMETERS: ticker — stock ticker (required) periods — quarters to analyze, 4–20 (default 8) RESPONSE: beat_rate, avg surprise, per-quarter reactions, signals{consistent_beater,…}. PRICING: $0.02 per call.

Daily Brief — one-call morning digest for trading agents. Bundles 4 data sources into a single paid call: • Fear & Greed Index (score + rating + weekly delta) • Market Movers (top 5 gainers, losers, 3 most active) • Earnings Today (companies reporting today with EPS estimates) • Economic Events Today (high/medium impact macro events) HOW TO CALL: POST /daily_brief (no parameters) All

Options Chain — full calls and puts for a ticker and expiration date. HOW TO CALL: POST /get_options_chain?ticker=AAPL POST /get_options_chain?ticker=AAPL&expiration=2026-07-18 PARAMETERS: ticker — stock symbol (required) expiration — expiration date 'YYYY-MM-DD' (default: nearest available) RESPONSE FIELDS: available_expirations — all available expiry dates spot_price

Position Sizing — how much to actually put on. Turns a pattern's historical outcome distribution into a dollar size for your portfolio, at the aggression level you choose, with stop and target references alongside it. The answer scales with how good the setup has been, not with conviction. PARAMS: ticker, start_date, end_date — pattern window horizon — '7d' | '14d' | '30d' | '60d' (defau

Signal Performance — the track record, wins and losses both. Every signal that ever fired, scored against what the price actually did at its horizon. Filter to one ticker to see where the record is strong and where it is not. HOW TO CALL: GET /trading/performance GET /trading/performance?ticker=BTC&last_n_days=90 PARAMETERS: ticker — filter to one ticker (optional) last_n_days — lo

Signal History — full log of every signal fired, with outcomes. Shows internal algo signals and x402 API signals. Pending signals (horizon not yet reached) show actual_return_pct=null. HOW TO CALL: GET /trading/signals/history GET /trading/signals/history?ticker=BTC&source=internal&limit=20 PARAMETERS: ticker — filter to one ticker (optional) limit — max rows (default

Forward Distribution — full probabilistic return forecast from historical analogs. Finds the top-k closest historical analogs for a pattern window, then computes the P10/P25/P50/P75/P90 percentile distribution of forward returns at 7, 14, 30, 60 days. Answers: 'given that the price behaved this way, what is the distribution of outcomes?' HOW TO CALL: POST /forward_distribution?ticker=SPY&start

Pattern Machine OHLC — same vectorized motif search as /get_patterns, but returns full Open/High/Low/Close candlestick data for each matched pattern. Use this endpoint when you need to render candlestick charts of historical analogs. HOW TO CALL: POST /get_patterns_ohlc?ticker=AAPL&start_date=2024-01-02&end_date=2024-03-01&k=5&metric=l2&wrap=true&timeframe=1d PARAMETERS: identical to /get_patt

Pattern Machine — vectorized time series motif search. Given a query window (ticker + date range), finds the top-k closest historical price patterns using normalized L1/L2 distance. Returns matched pattern dates, closes, similarity scores, and aggregated 7-day and 30-day forward return statistics. HOW TO CALL: POST /get_patterns?ticker=AAPL&start_date=2024-01-02&end_date=2024-03-01&k=5&metric=l

Portfolio Factors — what your book is actually exposed to. The momentum and trend you are carrying, and how much of your risk is really just the S&P or really just bitcoin. HOW TO CALL: GET /api/portfolio-factors?holdings=xyz:NVDA:1000,BTC:500 PARAMETERS: holdings — TICKER:weight pairs, HL-format tickers (required) lookback — estimation window in days, 60–250 (default 120) RESPONSE: noti

Sector Momentum — which parts of the market are working right now. 11 GICS sectors plus cross-cutting themes, ranked hottest first, each with the names leading it. Leaders are flagged when they are tradable as a perp. HOW TO CALL: GET /api/sectors/momentum?lookback=60 PARAMETERS: lookback — momentum window in trading days, 20–250 (default 60) RESPONSE: sectors[] ranked hottest-first, each

Narrative — price momentum + live news sentiment + theme tag for one asset. HOW TO CALL: GET /api/narrative?ticker=NVDA PARAMETERS: ticker — asset symbol (required) RESPONSE: price_action{momentum,trend,direction}, news{sentiment,rating,headline}, themes[]. PRICING: $0.05 per call.

Live Signals — the current call on any asset you name. HOW TO CALL: GET /api/signals/live?assets=BTC,ETH,xyz:NVDA PARAMETERS: assets — comma-separated tickers (required) limit — log rows to scan, 1–200 (default 50) RESPONSE: signals[] — direction, confidence, suggested size (kelly_half), entry/exit price, and how it resolved if the horizon has passed. PRICING: $0.10 per call.

Provider reliability — the supply-side reputation the 6-question agent loop needs. Observed at our door: which origins agents chose via the free router and whether it actually helped — helped-rate (Laplace-smoothed), repeat-rate, and sample confidence. Not asserted, measured; a provider is neutral until agents report back. HOW TO CALL: GET /api/demand/reliability?days=90&limit=25 PARAMETERS:

x402 supply census — who is live, in what category, at what price. The full public discovery index (~14.8k resources) normalised into per-category price percentiles and per-origin catalogues, so you can price against the median instead of the loudest listing. Crossed with the half that is not public: which agent client stacks actually crawl a live origin, and therefore which ones will find your e

x402 conversion reality — do payment quotes ever become payments? Measured quote-to-pay rates by category and by price band, from tens of thousands of observed 402s. Price your endpoint against what the market actually converts at instead of guessing, and rule out the protocol-level defects that silently zero a funnel before you blame your price. HOW TO CALL: GET /api/demand/conversion?days=30

x402 Agent-Demand Intelligence — what AI agents actually try to buy, ranked. Derived from the live request log of an origin that x402 agent crawlers already index: 402 payment quotes are revealed intent (an agent asked the price of a call), so the ranking shows what the agent economy is shopping for right now, by endpoint and by category. HOW TO CALL: GET /api/demand/top?days=7&limit=25 PARAM

Unmet agent demand — the endpoints agents ask for and cannot get. 404s and gated 401/403s from real (non-scanner) agent clients: a shopping list with the customers already attached. This cut is invisible to anyone who is not the origin being asked, which is why it cannot be reconstructed from public bazaar data. HOW TO CALL: GET /api/demand/unmet?days=7&limit=25 PARAMETERS: days — lookback

Regime Detection — 'What historical market period does now most resemble?' Runs DTW pattern matching on a ticker's recent price window against the full history. Returns the top-k most similar historical windows, each labeled with the market era (e.g. '2008 Financial Crisis', 'COVID stimulus bull', 'Trade war correction') and the forward returns that followed that analog. HOW TO CALL: POST /reg

Pattern Machine Raw — cheapest tier. Same motif search as /get_patterns but returns only the matched dates, closes, and similarity scores. No forward-return statistics are computed. Use this for high-volume scanning or when you only need raw analog windows. HOW TO CALL: POST /get_patterns_raw?ticker=AAPL&start_date=2024-01-02&end_date=2024-03-01&k=5&metric=l2&wrap=true&timeframe=1d PARAMETERS:

Trading Signal — one ticker in, one decision out. Which way, how sure, how much, and where to get out — with the historical record, market backdrop and current news behind it, so you can weigh the call. HOW TO CALL: POST /trading/signal?ticker=BTC POST /trading/signal?ticker=AAPL&timeframe=1d&lookback_days=30 PARAMETERS: ticker — asset symbol, e.g. BTC, ETH, AAPL, SPY (required)

Crawl-to-refer — what each AI company takes from a site versus what it sends back. Per company: pages crawled, visitors referred, and the ratio between them, measured at an origin's own door. Every publisher wants this number for their own site and cannot compute it without being the origin being crawled. HOW TO CALL: GET /api/demand/crawl-to-refer?days=30 PARAMETERS: days — lookback window

Pattern Backtest — systematically scan all historical windows matching a return profile. Answers: 'every time {ticker} did X% over {N} days, what happened in the next {M} days?' HOW TO CALL: POST /pattern_backtest?ticker=SPY&lookback_days=20&min_return=-0.05&max_return=0.0&forward_days=30 PARAMETERS: ticker — asset symbol (required) lookback_days — window length to scan (default 20

Backtest — "this has happened before; what happened next?" Finds every prior stretch of history that looked like the ticker's recent shape and reports where those went. HOW TO CALL: GET /api/backtest?ticker=BTC&lookback_days=20&forward_days=30 PARAMETERS: ticker — asset symbol (required) lookback_days — pattern window, 5–60 (default 20) forward_days — forward horizon, 7–90 (defa

Trading Scan — the whole universe in one call, best setups first. Crypto and equities scanned together, ranked by strength of edge. Everything that failed the bar is dropped rather than returned as noise. HOW TO CALL: POST /trading/scan?top_n=5 PARAMETERS: top_n — max results to return (default 5, max 10) RESPONSE: signals[] — [{ticker, direction, confidence, kelly_half, score, narrative

Trading Portfolio — the book as it stands right now. Every open position with its size, entry, live mark and unrealized PnL, plus total account equity. Real fills on a real venue, not a delayed report. HOW TO CALL: GET /trading/portfolio RESPONSE: account_value_usd — total equity in USD open_positions — [{asset, side, size, entry_price, mark_price, unrealized_pnl}] PRICING: $0.0001

Market Movers — real-time top gainers, losers, and most-active stocks from US markets. HOW TO CALL: POST /get_market_movers — all three lists, 10 stocks each POST /get_market_movers?category=gainers&count=5 — top 5 gainers only PARAMETERS: category — 'gainers' | 'losers' | 'active' | 'all' (default: all) count — results per category, 1–25 (default 10) RESPONS

Fear & Greed Index — CNN's composite market sentiment score (0=Extreme Fear, 100=Extreme Greed). HOW TO CALL: POST /get_fear_greed (no parameters) RESPONSE FIELDS: score — current index value (0–100) rating — 'Extreme Fear' | 'Fear' | 'Neutral' | 'Greed' | 'Extreme Greed' previous_week — score from 1 week ago previous_month — score from 1 month ago previous_year —