Market data¶

The abaquant.marketdata namespace provides lazy ticker and universe facades, provider interfaces, cached financial-statement workflows, option-chain analytics, and bridges into portfolio and credit analytics.

Ticker facade¶

from abaquant.marketdata import get_ticker

ticker = get_ticker("AAPL")

A ticker object groups related namespaces:

Ticker namespace	Typical methods
`ticker.spot()`	latest or configured spot quote.
`ticker.history`	price and return history.
`ticker.options`	listed option chains, pricing helpers, Greeks, option-chain analytics.
`ticker.financials`	statement snapshots, line-item helpers, credit-input construction.
`ticker.credit`	credit proxy assessment from supplied or cached financials.
`ticker.visualize()`	price-history and related charts.

Object construction is lazy. Provider retrieval occurs when you call a retrieval method.

Universe facade¶

from abaquant.marketdata import get_tickers

universe = get_tickers(["AAPL", "MSFT", "NVDA"])
prices = universe.history.prices(period="1mo")
returns = universe.history.returns(period="1mo")
summary = universe.statistics.summary(period="1mo")
portfolio = universe.portfolio.max_sharpe(period="1mo", risk_free_rate=0.02)

A universe object aligns multi-asset data and exposes portfolio-oriented helpers.

Option-chain analytics¶

chain_analytics = ticker.options.analytics("2027-01-15")
iv_smile = chain_analytics.iv_smile(option_type="call")
iv_surface = chain_analytics.iv_surface(option_type="call")
skew = chain_analytics.skew(option_type="call")
rich_cheap = chain_analytics.rich_cheap_table(risk_free_rate=0.04, option_type="call")

Analytics include implied-volatility smiles, surfaces, term structure, skew summaries, rich/cheap model comparisons, and open-interest heatmaps.

Financial statements¶

Financial statement workflows normalize provider facts into canonical statement tables and then build credit inputs.

snapshot = ticker.financials.snapshot()
inputs = ticker.financials.credit_inputs()
assessment = ticker.credit.assess_from_financials()

The financial statement stack includes:

Component	Role
Provider adapter	Supplies raw facts or tables.
Normalizer	Converts provider data into consistent DataFrames.
Line-item resolver	Maps provider-specific labels into canonical metrics.
Cache	Reuses raw and normalized statement snapshots.
Credit input builder	Converts statement data into `CreditAnalysisInputs`.

Providers¶

Provider area	Notes
Yahoo/yfinance	Optional market extra; useful for quotes, prices, options, and broad equity data when available.
SEC EDGAR/XBRL	Company Facts style provider for U.S. public company fundamentals. Use a real contact user agent for live requests.
Manual/deterministic fixtures	Used by examples and tests to keep workflows reproducible.

Caching¶

Use disk caching for repeated live-data sessions and reproducibility. Cache keys should be interpreted as implementation details; use public facade methods rather than depending on file names.

Provider risk¶

Market-data providers can produce:

stale data;
delayed data;
missing contracts or statements;
adjusted historical prices;
restated fundamentals;
survivorship-biased symbol sets;
incomplete option chains;
rate-limit or authorization failures.

Record provenance and avoid mixing provider snapshots without checking retrieval times and reporting periods.