AgenticWaves: Agentic AI-Powered Wavelet Financial Network Analysis

A revolutionary framework combining Agent-Based Modeling (ABM) with Wavelet Quantile Transfer Entropy (WaveQTE) analysis for comprehensive financial network analysis. Features autonomous AI agents, dynamic spillover detection, multi-asset analysis, and publication-quality visualizations.

Main Functions

Core Analysis Functions:

create_autonomous_agent - Create AI analysis agent
create_enhanced_agent_population - Generate agent population
simulate_enhanced_market_dynamics - Run market simulation
calculate_dynamic_spillover_networks - Spillover analysis
generate_publication_dashboard - Create visualizations

Interactive Applications:

launch_agentic_waves - Launch main application
run_agentic_waves_app - Run Shiny dashboard

Network Visualization:

plot_enhanced_network - Advanced network plots
plot_agent_type_network - Agent network visualization

Package Features

Multi-Asset Analysis:

Equities (Global indices, individual stocks)
Commodities (Energy, metals, agriculture)
Cryptocurrencies (Bitcoin, altcoins, DeFi)
Fixed Income (Government and corporate bonds)
Real Estate (REITs and property indices)

Autonomous AI Capabilities:

Self-optimizing parameter selection
Intelligent pattern recognition
Adaptive model configuration
Continuous learning and improvement

Agent-Based Modeling:

6 heterogeneous agent types
Realistic behavioral patterns
Multi-layer network interactions
Crisis-dependent behavior adaptation

Dynamic Network Analysis:

Real-time spillover detection
Multi-scale temporal decomposition
Contagion episode identification
Regime-switching dynamics

Getting Started

# Launch the main application
launch_agentic_waves()

# Or run a quick analysis
library(AgenticWaves)
data <- get_sample_data("global_markets")
agent <- create_autonomous_agent()
results <- agent$analyze_autonomously(data)

References

Baruník, J., & Křehlík, T. (2018). Measuring the frequency dynamics of financial connectedness and systemic risk. Journal of Financial Econometrics, 16(2), 271-296.

Axtell, R. L., & Farmer, J. D. (2025). Agent-based modeling in economics and finance: Past, present, and future. Journal of Economic Literature.

Author