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    Topology & Geometry in Quantitative Finance: A Mathematical Framework for Market Structure, Risk

    Posted By: Free butterfly
    Topology & Geometry in Quantitative Finance: A Mathematical Framework for Market Structure, Risk

    Topology & Geometry in Quantitative Finance: A Mathematical Framework for Market Structure, Risk, and Portfolio Optimization: A Comprehensive Guide for … by Hayden Van Der Post, Reactive Publishing, Alice Schwartz
    English | March 1, 2025 | ASIN: B0DYZB32HH | 303 pages | EPUB | 1.56 Mb

    Reactive Publishing
    Modern financial systems are complex, high-dimensional spaces where traditional methods often fail to capture deep structural relationships. Topology and geometry provide a powerful mathematical framework for understanding market behavior, risk propagation, and portfolio dynamics in ways that conventional statistical methods cannot.
    This book bridges the gap between abstract mathematics and practical finance, offering insights into manifold structures, persistent homology, and differential geometry for quantitative trading, risk management, and portfolio optimization.What You’ll Learn:
    Differential Geometry in Finance – Understand manifolds, curvature, and geodesics in financial modeling
    Topological Data Analysis (TDA) – Discover market structure and clustering using persistent homology
    Geometric Portfolio Theory – Optimize asset allocation using Riemannian metrics and distance functions
    Trading Strategies with Manifold Learning – Use topological features to detect market regime shifts
    Systemic Risk & Network Topology – Model contagion and financial crises using graph & topological techniques
    Stochastic Differential Geometry – Apply Brownian motion on manifolds to option pricing and risk modeling
    Python Implementations & Real-World Case Studies – Hands-on coding with scikit-tda, NumPy, and TensorFlowWho This Book is For:
    Quantitative Traders & Hedge Funds – Apply geometric insights to trading algorithms and market structure analysis
    Risk Managers & Financial Engineers – Improve systemic risk models using topological data analysis
    AI & Machine Learning Researchers – Integrate geometric deep learning and manifold-based feature extraction
    Students & Academics in Quant Finance & Math – Build a strong foundation in topology and differential geometry for finance
    With clear explanations, hands-on Python examples, and practical case studies, this book transforms abstract mathematical concepts into actionable tools for financial decision-making.
    Redefine the way you see financial markets—get your copy today!

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