Fractal Risk Dynamics: Chaos, Self-Similarity, and Scaling Laws in Modern Markets: A Quantitative Exploration of Nonline, (Paperback)

★★★★★ 5.0 33 reviews

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Management number 238794168 Release Date 2026/07/11 List Price US$14.00 Model Number 238794168
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<b>Reactive Publishing</b><p><i>Fractal Risk Dynamics: Chaos, Self-Similarity, and Scaling Laws in Modern Markets</i> unveils the hidden geometry that underpins financial volatility. Where traditional models assume order and equilibrium, real markets reveal fractal complexity-structures that repeat, scale, and evolve across every time horizon.</p><p>In this groundbreaking guide, Hayden Van Der Post bridges mathematics, physics, and finance to expose the nonlinear foundations of modern risk. You'll explore how fractal volatility emerges from self-organized market behavior, why scaling laws reveal universal constants across asset classes, and how chaos theory redefines the limits of prediction.</p><p>Through advanced yet accessible explanations, this book teaches you how to quantify uncertainty using multifractal analysis, design volatility surfaces informed by scaling exponents, and apply complexity modeling to portfolio optimization and risk forecasting.</p><p>Whether you're a quantitative analyst, trader, or researcher, <i>Fractal Risk Dynamics</i> will transform the way you perceive financial systems-from random noise to living, self-similar organisms driven by feedback, memory, and evolution.</p><p><b>Key Topics Include: </b></p><ul><li><p>Fractal and multifractal modeling of volatility and price movements</p></li><li><p>Scaling laws, power distributions, and turbulence analogies in finance</p></li><li><p>Chaos, attractors, and sensitivity in market systems</p></li><li><p>Nonlinear feedback loops and emergent risk patterns</p></li><li><p>Practical Python implementations for fractal risk metrics and simulations</p></li></ul><p><i>Step beyond conventional risk models and discover the fractal architecture of modern finance.</i></p>

  • Fractal Risk Dynamics: Chaos, Self-Similarity, and Scaling Laws in Modern Markets: A Quantitative Exploration of Nonline, (Paperback)
  • Author: Independently Published
  • ISBN: 9798273050822
  • Format: Paperback
  • Publication Date: 2025-11-05
  • Page Count: 478
Book format Paperback
Fiction/nonfiction Non-Fiction
Genre Business & Investing
Publication date November, 2025
Pages 478
Subgenre Finance
Series title No Series
Number in series 0
Edition 1
Publisher Amazon Digital Services LLC - Kdp
Original languages English
Language English
Edu focus Mathematics
Is collectible N
Editor Danny Munrow
Recording time 0 min
Retail packaging Single Piece
Assembled product dimensions (l x w x h) 6.00 x 0.96 x 9.00 in
Assembled product weight 1.4 lb
Bisac subject heading Business & Economics

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