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Graph Theory & Network Models for Quantitative Finance Graph Topology, Network Flows, and Market Microstructure [#1017725]

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Graph Theory & Network Models for Quantitative Finance: Graph Topology, Network Flows, and Market Microstructure by Hayden Van Der Post, James Preston, Konrad R. Falkner
English | January 12, 2026 | ISBN: N/A | ASIN: B0GGF7FRGD | 600 pages | EPUB | 0.81 Mb
Reactive Publishing


Graph theory has quietly become one of the most powerful lenses for understanding modern markets. Behind every price series lies a hidden network: agents exchanging liquidity, information propagating through clusters, volatility pooling in hubs, and systemic shocks cascading across links that investors never see on a chart. This book brings that architecture into focus and shows how to model it with rigor.
Graph Theory & Network Models for Quantitative Finance introduces a structured framework for using graph topology, network analytics, and flow models to analyze pricing, trading, contagion, and systemic risk. Instead of treating markets as isolated time series, the book treats them as dynamic interconnected graphs-revealing insights traditional quant techniques routinely miss.
Readers will learn how to represent markets as graphs, measure network centrality, compute flows, model liquidity stresses, evaluate cluster formation, and simulate the spread of shocks across financial systems. Case studies on network-based volatility regimes, limit-order book topology, liquidity networks, counterparty webs, and systemic risk dynamics connect the mathematics directly to real-world trading and portfolio management.
Core topics include:
* Graph representation of financial markets, assets, and agents
* Network topology, centralities, clustering, and connectivity
* Flow-based models for liquidity, information, and contagion
* Order book microstructure modeled as dynamic graphs
* Counterparty and clearing networks in derivatives markets
* Systemic risk propagation and network fragility
* Graph metrics for portfolio construction and risk decomposition
* Graph-based factor extraction and signal generation
* Cross-asset connectivity and hidden market structure
* Network simulation for stress testing and scenario design
By unifying graph theory, network science, and quantitative finance, the book equips traders, quants, and risk professionals with tools for the coming era of network-aware markets. If price charts describe what happened, graphs explain why, and what comes next.
For practitioners who suspect that the deepest truths in finance lie in the relationships between things, not the things themselves, this book is a definitive guide to modeling market networks with precision, insight, and edge.


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