Name: Simulation, Optimization, and Machine Learning for Finance, second edition (en Inglés)
Price: 133.62 USD
Availability: InStock
Author: Dessislava A. Pachamanova
ISBN: 9780262049801

portada Simulation, Optimization, and Machine Learning for Finance, second edition (en Inglés)

Simulation, Optimization, and Machine Learning for Finance, second edition (en Inglés)

Formato

Libro Físico

Editorial

MIT Press

Autor

Dessislava A. Pachamanova

Año

2025

Idioma

Inglés

N° páginas

672

Encuadernación

Tapa Dura

Dimensiones

26.162 x 20.828 x 3.048 cm

ISBN13

9780262049801

Simulation, Optimization, and Machine Learning for Finance, second edition (en Inglés)

Dessislava A. Pachamanova (Autor) · MIT Press · Tapa Dura

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Reseña del libro "Simulation, Optimization, and Machine Learning for Finance, second edition (en Inglés)"

A comprehensive guide to simulation, optimization, and machine learning for finance, covering theoretical foundations, practical applications, and data-driven decision-making.

Simulation, Optimization, and Machine Learning for Finance offers a comprehensive introduction to the quantitative tools essential for asset management and corporate finance. This extensively revised and expanded edition builds upon the foundation of the textbook Simulation and Optimization in Finance, integrating the latest advancements in quantitative tools. Designed for undergraduates, graduate students, and professionals seeking to enhance their analytical expertise in finance, the book bridges theory with practical application, making complex financial concepts more accessible.

Beginning with a review of foundational finance principles, the text progresses to advanced topics in simulation, optimization, and machine learning, demonstrating their relevance in financial decision-making. Readers gain hands-on experience developing financial risk models using these techniques, fostering conceptual understanding and practical implementation.

Provides a structured introduction to probability, inferential statistics, and data scienceExplores cutting-edge techniques in simulation modeling, optimization, and machine learningDemonstrates real-world asset allocation strategies, advanced portfolio risk measures, and fixed-income portfolio management using quantitative toolsCovers factor models and stochastic processes in asset pricingIntegrates capital budgeting and real options analysis, emphasizing the role of uncertainty and quantitative modeling in long-term financial decision-makingIs suitable for practitioners, students, and self-learners