quantitative_data_analysis_rs

Quantitative market analysis toolkit written in Rust. It ingests historical stock data plus fundamentals from J-Quants and Yahoo Finance to produce chart-ready signals, summaries, and SVG/JSON artifacts for reporting.

Features

• Hexagonal-style architecture (domain, use_case, controller, presenter, infrastructure, shared) keeps market logic testable and interchangeable.
• Trend analysis engine detects crossover patterns, MACO signals, candlestick patterns (marubozu, doji), and aggregates them into summaries.
• Financial indicator analyzer correlates statements with the latest available prices to generate JSON-friendly metrics.
• CSV/TSV ingestion utilities plus ready-made assets under assets/ accelerate local experiments.
• Async-first data access via J-Quants REST API and Yahoo Finance scrapers, including helper tooling for token rotation.

Installation

1. Install the Rust toolchain specified in rust-toolchain (Rust 1.90.0). rustup automatically picks it up when you enter the repo.
2. Install build essentials for your OS (LLVM/Clang on macOS, build-essential on Linux).
3. Clone the repository and fetch dependencies:

cargo fetch

This repository intentionally tracks Cargo.lock to keep CI and J-Quants connectivity checks reproducible.

Usage

• Financial indicators:

  cargo run --example financial_indicator

• Trend analysis (SVG + JSON outputs):

  cargo run --example trend_analysis

• Company master TSV generator:

  cargo run --example make_companies

Generated artifacts are written to examples/ (SVG charts) and compared against the golden files in assets/ for regression safety.

Configuration

• Provide J-Quants API key via environment variable before executing any example or binary:

  export JQUANTS_API_KEY="your-jquants-api-key"

• Optional inputs (dates, markets, crossover filters) are passed directly when calling controllers or editing the example binaries.

Contribution

• Read RUST_GUIDELINES.md and the referenced Microsoft Pragmatic Rust Guidelines before sending PRs.
• Adhere to the layered architecture; new logic should live in domain/use_case, while adapters go under infrastructure/presenter.
• Include documentation/comments for non-obvious algorithms and add/adjust tests in tests/ or under the relevant module.

Testing

Run formatting and the full test suite locally:

cargo fmt --all
cargo clippy --all-targets --all-features
cargo test

Examples double as integration tests; compare their outputs with the JSON/SVG fixtures in assets/ when modifying presenters.

License

The project has not declared an explicit license yet. Please ask the maintainers before using it in production or redistributing.

Acknowledgements

• J-Quants for providing authenticated access to fundamental and price data.
• Yahoo Finance for historical CSV feeds used in examples.
• The Rust community and the authors of the crates listed in Cargo.toml for the ecosystem support.