Financial Stability & Systemic Risk Modeling with Python : Macroprudential Stress Testing, Contagion Networks, and Sovereign-Bank Feedback Loops

Hayden van der Post

ISBN 13: 9798244011364

Published by Independently Published Jan 2026, 2026

About this Item

Neuware.

Seller Inventory # 9798244011364

Bibliographic Details

• Title: Financial Stability & Systemic Risk Modeling with Python : Macroprudential Stress Testing, Contagion Networks, and Sovereign-Bank Feedback Loops
• Publisher: Independently Published Jan 2026
• Publication Date: 2026
• Language: English
• ISBN 13: 9798244011364
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 229W x 152H x 25D millimeters 229 millimeters width by 152 millimeters height by 25 millimeters depth
• Weight: 476 grams

About this title

Synopsis

Reactive Publishing

Financial systems are complex adaptive networks where shocks propagate through balance sheets, institutions, and sovereigns in non-linear ways. Understanding and modeling these dynamics is now a core requirement for central banks, regulators, macro-prudential analysts, and market participants operating in a post-GFC environment defined by volatility, leverage, and structural fragility.

Financial Stability & Systemic Risk Modeling with Python provides a comprehensive framework for modeling systemic risk using empirical data, network-based contagion mechanics, macro-prudential stress testing, and sovereign-bank feedback loops. Readers learn how to construct, simulate, and interpret systemic stress scenarios and translate them into operational insights for policy analysis, investment strategy, and risk management.

Topics include:
• Balance sheet-based contagion modeling and network spillovers
• Stress testing frameworks across banks, sovereigns, corporates, and funds
• Macro-prudential capital buffers, procyclicality, and regulatory triggers
• Sovereign-bank doom loops and fiscal-financial feedback channels
• Cross-border contagion and currency-denominated liabilities
• Funding markets, collateral chains, and liquidity crunch dynamics
• Agent-based systemic simulations for non-linear shock propagation
• Market microstructure stress factors (volatility, basis spreads, fragmentation)
• Early warning indicators for financial instability
• Python implementations of core systemic models and simulation pipelines

Designed for practitioners, researchers, and advanced students in finance, economics, and risk management, the book integrates real-world datasets, empirical calibration, and executable Python models. By bridging academic rigor with applied modeling, it equips readers to evaluate systemic vulnerabilities, stress test financial architecture, and foresee how shocks can cascade through an interconnected global economy.

This is not a theoretical textbook. It is a modeling playbook for understanding financial stability under uncertainty, where the cost of misjudging contagion is measured in crises.