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farfromexact/README.md
Far From Exact - research systems for uncertain worlds

Market research systems built for evidence, review, and judgment.

Research systems  ·  All repositories

I build auditable research systems for China equities, index options, commodities, and cross-asset portfolio review. The work starts with reliable source data and ends with a conclusion that can be rechecked: source date, transformations, caveats, and result stay connected.

Operating areas

Data foundations

Point-in-time A-share, CFFEX options, and commodity futures datasets with provenance, coverage checks, and usable daily releases.
Market research

Cross-asset reports, regime views, and derivative positioning that separate evidence from interpretation.
Portfolio & capital

Review workflows, solvency scenarios, and capital tools that turn operating questions into traceable analysis.

Selected systems

Global Cross-Asset Radar
An evolving report archive that brings macro, futures, commodities, FX, volatility, and options context into one research surface.

Python · Reports · Cross-asset research
China Stock Engine
A point-in-time A-share market and reference-data foundation with source-date checks, coverage controls, and auditable daily outputs.

Python · PIT data · Quality gates
China Options Engine
An engine that turns CFFEX futures and option-chain data into implied volatility, Greeks, gamma exposure, and daily state.

Python · CFFEX · IV and Greeks
China Commodities Engine
An EOD China commodity futures foundation with explicit provenance, quality gates, and research-ready market surfaces.

Python · Commodity futures · EOD
Portfolio Review
A monthly portfolio-review workflow from Excel snapshots to traceable Parquet releases, analytics, and asset-level evidence.

Python · Parquet · Portfolio analytics
Solvency
An insurance solvency and asset-allocation workbench for historical review, scenario shocks, target solving, and capital attribution.

Python · Streamlit · Scenario analysis

Working principles

Evidence before signal. Keep source dates, transformations, assumptions, and data gaps visible. Build the smallest useful system that can still be challenged and rechecked; keep sensitive data local where appropriate.

Research and educational software. No repository here is an order-generation system or investment advice.

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