# OIPD

## Docs

- [Connect AI coding tools](https://docs.open-lemma.com/ai-coding-tools.md): Connect the hosted OIPD docs MCP server to Claude Code, OpenAI Codex, Cursor, or VS Code so AI agents can use the docs while writing OIPD code.
- [Market inputs](https://docs.open-lemma.com/concepts/market-inputs.md): What OIPD needs to know about rates, dates, and prices before fitting option data.
- [Mental model](https://docs.open-lemma.com/concepts/mental-model.md): A short guide to OIPD's four main objects and the fit-then-query workflow.
- [Probability layer](https://docs.open-lemma.com/concepts/probability-layer.md): How OIPD turns fitted volatility into market-implied probability distributions.
- [Volatility layer](https://docs.open-lemma.com/concepts/volatility-layer.md): How OIPD fits implied volatility curves and surfaces before deriving probabilities.
- [Data sources](https://docs.open-lemma.com/guides/data-sources.md): Fetch live options chains via yfinance, normalize a CSV file, or pass an existing DataFrame — all using the OIPD sources module.
- [Probability curve](https://docs.open-lemma.com/guides/probability-single-expiry.md): Step-by-step guide to fitting a risk-neutral probability distribution on a single option expiry date and querying prices, quantiles, and moments.
- [Probability surface](https://docs.open-lemma.com/guides/probability-surface.md): Fit a risk-neutral probability surface over multiple expiries, query densities within the fitted range, and export a long-format results DataFrame.
- [Volatility smile](https://docs.open-lemma.com/guides/volatility-smile.md): Configure and calibrate a single-expiry implied volatility smile, evaluate IVs, price options, compute Greeks, and export results with VolCurve.
- [Volatility surface](https://docs.open-lemma.com/guides/volatility-surface.md): Calibrate an implied volatility surface across many expiries, slice it within the fitted range, export long-format IV results, and convert to ProbSurface.
- [Warnings](https://docs.open-lemma.com/guides/warnings-diagnostics.md): Understand OIPD's structured warning system, inspect per-event diagnostics on fitted objects, and configure strict CDF violation policies.
- [Installation](https://docs.open-lemma.com/installation.md): Install oipd from PyPI with pip and pick the standard or minimal dependency set.
- [Introduction](https://docs.open-lemma.com/introduction.md): Learn what OIPD is and how its four core objects work together to extract market-implied probability distributions from options chains.
- [Quickstart](https://docs.open-lemma.com/quickstart.md): Fetch a live options chain, fit a ProbCurve, and query market-implied tail probabilities, quantiles, and distributional moments in five steps.
- [Errors](https://docs.open-lemma.com/reference/exceptions.md): Understand the OIPD exception hierarchy, when each error is raised, and how to write robust try/except blocks for calibration and data-loading workflows.
- [MarketInputs](https://docs.open-lemma.com/reference/market-inputs.md): Provide risk-free rates, valuation dates, and underlying prices to OIPD calibration methods using the MarketInputs dataclass and VendorSnapshot.
- [ProbCurve](https://docs.open-lemma.com/reference/prob-curve.md): Build and query a risk-neutral probability distribution for one option expiry — querying tail probabilities, quantiles, moments, and plots.
- [ProbSurface](https://docs.open-lemma.com/reference/prob-surface.md): Query risk-neutral probability distributions across multiple expiries from a volatility surface or a multi-expiry option chain using OIPD.
- [Sources](https://docs.open-lemma.com/reference/sources.md): Fetch live option chains, list available expiry dates, and normalize chain data from CSV files or DataFrames using the oipd.sources module.
- [VolCurve](https://docs.open-lemma.com/reference/vol-curve.md): Fit an SVI implied volatility smile for one expiry, query IVs, compute Greeks, and derive a risk-neutral probability distribution with OIPD.
- [VolSurface](https://docs.open-lemma.com/reference/vol-surface.md): Calibrate an implied volatility surface across multiple expiries, interpolate between pillars, and export IV results or derive probability distributions.
- [Pipeline details](https://docs.open-lemma.com/theory/pipeline-details.md): Advanced theory notes on how OIPD fits volatility and converts it into market-implied probability distributions.