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advanced-math-tradinginformation-causal
by keith-mvs
An advanced AI-driven quantitative trading ecosystem featuring multi-source market data aggregation, high-fidelity paper trading simulation, and machine learning-powered signal generation.
⭐ 1🍴 0📅 Dec 28, 2025
Run in ManusSKILL.md
name: advanced-math-trading/information-causal description: Information theory (entropy/MI/TE) and causal inference for trading signals.
What this covers
- MI/transfer entropy features, causal validation, Bayesian conditioning.
Navigation (load on demand)
- docs/knowledge-base/domains/foundations/advanced-mathematics/information-theory.md
- docs/knowledge-base/domains/foundations/advanced-mathematics/causal-inference.md
- docs/knowledge-base/domains/foundations/advanced-mathematics/conditional-probability-and-bayes-theorem.md
Quick workflows
- Feature relevance → MI/TE from information-theory.
- Causal checks (Granger/DAGs/potential outcomes) → causal-inference.
- Bayesian updates → conditional-probability-and-bayes-theorem.
Notes
- Keep context to the specific technique needed.
Score
Total Score
75/100
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