About Wickra Genome

Wickra Genome is a vector database of the whole market: every asset as a live feature vector over the streaming indicators, with similarity search, clustering and anomaly detection over its microstructure DNA. A query is a JSON command — data, not code — so it runs in every one of ten languages and returns byte-for-byte identical results.

What makes it different

• Every asset is a vector. Each asset has a shape — the momentum, volatility, flow and microstructure signature of how it is trading right now. Genome turns that shape into a feature vector, one coordinate per Wickra indicator.
• Find assets behaving alike. Similarity search finds every asset behaving like X right now, ranked by cosine or Euclidean distance in the normalized space.
• Cluster and flag. Seeded k-means clustering groups the market into regimes, and anomaly scoring flags the assets whose DNA has gone strange.
• One coordinate per indicator. Vectors are built from the same 514 indicators of the Wickra core the rest of the ecosystem uses — the same numbers a backtest or a live chart sees, turned into geometry.

Why it exists

Market screening is usually per-symbol and rule-based; it can't ask "what else is behaving like this?" Genome makes the whole market a vector space, built once in Rust, and exposes it as a JSON-over-C-ABI data API to Rust, Python, Node.js, WASM and — over a C ABI — C, C++, C#, Go, Java and R. The same query runs anywhere.

Open source

Released under the MIT OR Apache-2.0 license — permissive, OSI-approved, free for any use including commercial. Source, issues and releases on GitHub.

Disclaimer

Wickra Genome is a software library, not a trading system, and is provided as-is with no warranty. It surfaces geometric relationships over market data; it does not give financial advice. Use it at your own risk.