Regime-aware markets
Calibrated volatility, fat tails, and return clustering. Sector dispersion with real winners and losers. Energy rallies in an oil shock, semis in an AI capex cycle.
Backed by Y Combinator
Synthetic financial market data for agents.
Historical and simulated market scenarios with prices, fundamentals, filings, news, events, and more. Backtest and train your AI agents, with no vendor licensing limits.
- 16,143
- Ticker aliases
- 720
- Scenario library
- 80
- Market themes
- 70+
- API endpoints
api.davidhf.com · /prices
$ curl https://api.davidhf.com/prices
?scenario_id=scn_8f3a&ticker=NVDA&interval=day
-H "X-API-KEY: ••••••••"
{
"ticker": "NVDA",
"interval": "day",
"prices": [
{ "date": "2026-01-02",
"open": 142.18, "high": 145.07,
"low": 141.55, "close": 144.92,
"volume": 41203885 },
{ "date": "2026-01-05",
"open": 145.10, "high": 149.33,
"low": 144.81, "close": 148.76,
"volume": 52994117 }
]
}200 OK · X-RateLimit-Remaining: 5,998 · scenario scn_8f3a
Daily & intraday OHLCVOptions & IV surfaceIncome statementsBalance sheetsCash flowsFinancial metricsEarnings & guidanceAnalyst estimatesSEC-style filingsMarket newsInsider transactions13F-like holdingsCorporate actionsMacro & ratesIndex fundsSegmented financialsEvent timelinesDaily & intraday OHLCVOptions & IV surfaceIncome statementsBalance sheetsCash flowsFinancial metricsEarnings & guidanceAnalyst estimatesSEC-style filingsMarket newsInsider transactions13F-like holdingsCorporate actionsMacro & ratesIndex fundsSegmented financialsEvent timelines
Platform
A market simulator that behaves like the real thing
Most synthetic data is a random walk with a ticker glued on. David Data generates scenario-conditioned market worlds with realistic dynamics, historical and forward branches, and the full public-company evidence surface.
Scenario-grounded worlds
Each scenario generates a full issuer narrative: fundamentals, events, price paths, filings, and news from the same market world, not a random walk with a ticker glued on.
Full evidence bundle
Daily and intraday prices, listed options, fundamentals, earnings, guidance, analyst revisions, news, SEC-style filings, ownership, insider trades, and corporate actions across the public-company surface.
Real ticker universe
16,143 exchange-style symbols with sector and industry metadata. Operating companies get full financials and filings; ETFs and benchmarks are modeled as the instruments they are.
Scenario themes & crises
80 market themes including war energy shocks, bank runs, AI IPO manias, Fed pivots, and semiconductor blockades, with event-aware macro tapes around each catalyst.
Python SDK + REST
Official Python SDK (pip install david-data) and a fully documented REST API with OpenAPI, API-key auth, and rate limits. Integrate in minutes.
Coverage
One API, the entire public-company surface
A complete endpoint surface covering discovery, statements, screeners, KPI views, options, ownership, and market snapshots, all from one REST API.
Market data
6 endpoints- /prices
- /prices/snapshot
- /prices/snapshot/market
- /index-funds
- /macro
- /macro/interest-rates
Fundamentals
6 endpoints- /financials/income-statements
- /financials/balance-sheets
- /financials/cash-flow-statements
- /financial-metrics
- /financials/as-reported
- /financials/segments
Earnings & estimates
6 endpoints- /earnings
- /kpi/guidance
- /kpi/metrics
- /kpi/non-gaap
- /analyst-estimates
- /financials/search/screener
Options & derivatives
5 endpoints- /options/tickers
- /options/expirations
- /options/chain
- /options/quotes
- /options/iv-surface
Disclosures & artifacts
6 endpoints- /news
- /filings
- /filings/items
- /institutional-holdings
- /company/facts
- /company/facts/tickers
Full reference in the interactive docs.
Use cases
Ground truth for teams that can't risk dirty data
01 · Quant research
Backtest without survivorship or look-ahead bias
Work across pre-built train/validation/test/holdout splits spanning 720 scenarios. Because the data is clean ground truth, there is no leakage, no restatement noise, and no vendor point-in-time licensing to negotiate.
- Mixed 30-year, business-cycle, and event-window horizons
- Theme-anchored historical and forward branches
- Pin a scenario for audit-ready, repeatable research
02 · AI agents
Train and evaluate financial agents safely
Give LLM agents a full market world to work in: filings, news, earnings, and prices from the same scenario. Because the data is generated, you know what actually happened and can check whether an agent got it right.
- Filing items and news linked to source events
- Scenario ground truth for scoring agent outputs
- No real-data licensing or redistribution risk
03 · Product & demos
Build and demo without touching licensed feeds
Stand up dashboards, screeners, and analytics on a realistic dataset you can ship in demos, sandboxes, and CI. Swap in the synthetic endpoint anywhere your client expects a financial data feed.
- Drop-in REST surface with API-key auth
- Stable fixtures for CI and integration tests
- Shareable demo environments, zero leakage
Developer experience
Query a complete market world in two calls
Official Python SDK, REST API, JSON responses, and rate-limit headers on every request. If you've used a financial data API before, you already know this one.
X-API-KEY required
pip install david-data
from david_data import DavidData
dd = DavidData() # uses DAVID_DATA_API_KEY
scenario = dd.scenarios.list(limit=1)[0]
sid = scenario["id"]
bars = dd.prices.get("AAPL", scenario_id=sid, limit=10)
income = dd.financials.income_statements(
"AAPL", scenario_id=sid, period="quarterly", limit=8,
)
news = dd.news.list(ticker="AAPL", scenario_id=sid, limit=5)Pricing
Start free, scale when you need to
Begin on the free tier with no card required. Every paid plan adds scale, more scenarios, and support. Never paywalled features.
Free
Kick the tires and prototype against real data shapes.
$0forever
- 1 API key · 60 req/min
- Core endpoint surface
- 3 sample library scenarios
- Real ticker universe
- Community support
Credits
1,000 prepaid API requests. No subscription, never expire.
$20one-time
- 1,000 API requests, use anytime
- 1 API key · 300 req/min
- Full endpoint surface
- 10 library scenarios
- Buy again whenever you run low
Most popular
Build
For quant teams and AI labs running real workloads.
$200/mo
- 100,000 API requests / month
- 5 API keys · 6,000 req/min
- 250 library scenarios
- Python SDK
- Train/validation/test/holdout splits
- Priority email support
Enterprise
For institutions needing scale, SLAs, and custom worlds.
Custom
- Unmetered requests & dedicated capacity
- Full 720-scenario library
- Custom themes & calibration
- On-prem / VPC deployment
- SLA + named support engineer
FAQ
Questions, answered
No. Every price, fundamental, filing, news item, and event is synthetically generated with market-like dynamics and no licensed redistribution restrictions. You get realistic, calibrated scenarios without point-in-time licensing headaches.
Pin a scenario ID and you get the same world every time. That makes backtests auditable and agent evals repeatable.
A random walk gives you a price series with nothing behind it. David Data builds scenario-grounded worlds: accounting identities hold, OHLC invariants are valid, earnings tie to guidance, headlines trace to structured events, and filings carry catalyst lineage. Validation and dataset-quality audits check the result.
Yes. Use the official Python SDK or hit the REST API directly. API-key auth, JSON responses, and a documented OpenAPI surface cover discovery, as-reported and segmented statements, screeners, KPI/non-GAAP views, index funds, interest rates, and market snapshots. Most clients only need to change the base URL and key.
Generation is calibrated against empirical reference panels for volatility, kurtosis, return clustering, drawdowns, and tail behavior. Calibration is a research workbench result, not an institutional sellability claim. For institutional use we offer custom calibration against licensed vendor panels.
Yes. Listed options come as discovery, expirations, full chains, per-contract quotes with greeks, and implied-volatility surface nodes — all point-in-time via as_of, so a query never sees contracts or prices that weren't public yet. Chains are generated from each scenario's spot path, volatility state, dividend policy, and event calendar, with options-quote invariants validated (arbitrage-free bid/ask, no negative prices, coherent surfaces). Liquid ETF options like SPY and QQQ are modeled too.
Every scenario ships daily OHLCV, plus regular-hours intraday bars at 1-, 5-, and 15-minute resolution. Pass interval=1m|5m|15m to /prices with a date window; intraday history is window-capped per interval (14 days at 1m, 60 at 5m, 180 at 15m) and calibrated against real intraday reference panels.
Yes. The library ships with 80 market themes including crisis archetypes. On Enterprise, our team designs custom scenarios and themes, runs custom calibration, and delivers fully materialized institutional panels with on-prem or VPC deployment.
Stop fighting your data. Start owning it.
Get an API key and start querying scenario-grounded market worlds in minutes. License-free ground truth for backtests and AI agents.
Questions? Email us at founders@davidhf.com