Causality Network Analysis (CNA) is an advanced tool for modeling causal relationships between variables. In financial markets, CNA helps identify how market events influence each other, leading to better predictions.

Causal discovery infers relationships from data. For financial markets, it means pinpointing which factors, like economic indicators or market prices, affect others. The Fast Causal Inference (FCI) algorithm is often used for this purpose.

Network analysis represents relationships between financial instruments. This involves setting up a network structure to analyze these connections. Event prediction uses models like Vector Autoregression (VAR) for forecasting. The combination of CNA and VAR offers a comprehensive approach to market analysis.
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