Финансовые рынки: Нейронные сети, хаос и нелинейная динамика

В настоящей книге рассмотрены методы построения и обучения нейронных сетей; описаны наиболее распространенные виды сетей, применяющихся в задачах классификации и анализа временных рядов. Рассмотрено применение сетей к таким расчетам на финансовом рынке, как расчет цен опционов европейского типа, оценка индексов акций и управление международным портфелем. Показаны фрактальные свойства временных рядов, изложены динамические модели детерминированного хаоса. Для снижения неопределенности продемонстрировано применение алгоритмов оптимальной фильтрации и решение задачи параметрической идентификации при построении уравнений модели хаоса. Описаны возможности нейронных сетей для прогнозирования детерминированного хаоса. В приложении приведен комплект учебных материалов по курсу «Финансовые рынки и нейронные сети». Пособие предназначено для студентов специальностей «Прикладная математика и информатика», «Прикладная математика», «Прикладная информатика», «Математические методы в экономике», экономических и финансовых специальностей вузов. Оно будет также полезно широкому кругу специалистов финансовых институтов, применяющих финансовые вычисления в своей работе.

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Financial Markets: Neural Networks, Chaos, and Nonlinear Dynamics

Explore the cutting-edge intersection of finance and artificial intelligence with "Financial Markets: Neural Networks, Chaos, and Nonlinear Dynamics." This comprehensive guide delves into the application of neural networks for financial modeling, time series analysis, and risk management, offering practical insights for students and professionals alike.

Book Overview and Main Themes

This book provides a thorough examination of neural network construction and training, focusing on network types commonly used for classification and time series analysis. It explores the application of these networks to critical financial market calculations, including European option pricing, stock index valuation, and international portfolio management. The book also investigates the fractal properties of time series and presents dynamic models of deterministic chaos. To mitigate uncertainty, it demonstrates the use of optimal filtering algorithms and parametric identification for building chaos model equations. Finally, it highlights the potential of neural networks for predicting deterministic chaos.

Target Audience and Reading Level

This book is ideal for:

• Students in applied mathematics and computer science, applied mathematics, applied informatics, mathematical methods in economics, and economics/finance programs.
• Financial professionals seeking to leverage neural networks for advanced financial computations.
• Anyone interested in the application of AI and machine learning to financial markets.

The book assumes a basic understanding of financial markets and mathematical concepts. A background in programming is helpful but not required.

Key Features and Benefits

• Practical Applications: Learn how to apply neural networks to real-world financial problems.
• Comprehensive Coverage: Gain a deep understanding of neural network architectures and training methods.
• Advanced Techniques: Explore fractal analysis, deterministic chaos models, and optimal filtering algorithms.
• Educational Resources: Access a complete set of educational materials for a "Financial Markets and Neural Networks" course in the appendix.

Why Readers Should Choose This Book

In today's rapidly evolving financial landscape, understanding advanced analytical techniques is crucial for success. "Financial Markets: Neural Networks, Chaos, and Nonlinear Dynamics" provides a unique and practical guide to leveraging the power of neural networks for financial modeling and prediction. Whether you're a student looking to expand your knowledge or a professional seeking to enhance your skills, this book offers the insights and tools you need to stay ahead of the curve. Unlock the potential of AI in finance and gain a competitive edge with this essential resource.