Mattbusel/LLMTokenStreamQuantEngine

A low-latency, C++-based simulation engine that ingests token streams from an LLM in real-time, maps semantic token meaning to trade signals, and triggers micro-adjustments to a trading algorithm on a fractional-time (sub-second) scale.

23
/ 100
Experimental

This engine helps quantitative traders turn real-time natural language insights from large language models into immediate, precise trading actions. It ingests a stream of text tokens, translates their semantic meaning into directional trading signals, and then triggers micro-adjustments to a trading algorithm. The ideal user is a quant trader or firm focused on high-frequency, automated trading strategies based on rapid sentiment and market regime shifts.

Use this if you need to integrate LLM-derived market sentiment directly into a high-speed, automated trading system to make sub-second adjustments based on evolving market narratives.

Not ideal if your trading strategies are long-term, not sensitive to micro-second latency, or do not involve real-time natural language processing.

quantitative-trading algorithmic-trading financial-sentiment-analysis high-frequency-trading market-regime-detection
No License No Package No Dependents
Maintenance 13 / 25
Adoption 3 / 25
Maturity 7 / 25
Community 0 / 25

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Stars

4

Forks

Language

C++

License

Last pushed

Mar 18, 2026

Commits (30d)

0

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