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Simulation, optimization, and machine learning for finance
Hardback
€174.00
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- Book Synopsis
- 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 science Explores cutting-edge techniques in simulation modeling, optimization, and machine learning Demonstrates real-world asset allocation strategies, advanced portfolio risk measures, and fixed-income portfolio management using quantitative tools Covers factor models and stochastic processes in asset pricing Integrates capital budgeting and real options analysis, emphasizing the role of uncertainty and quantitative modeling in long-term financial decision-making Is suitable for practitioners, students, and self-learners
- About The Author
- Frank J. Fabozzi is Professor of Practice at Johns Hopkins Carey Business School. He has held positions at EDHEC Business School, Yale, Princeton, MIT, NYU, and Carnegie Mellon. He is the author of Entrepreneurial Finance and Accounting for High-Tech Companies and Introduction to Fixed-Income Analysis and Portfolio Management, and coauthor of Bond Markets, Analysis, and Strategies, Tenth Edition and Foundations of Global Financial Markets and Institutions, all published by the MIT Press. His forthcoming coauthored books to be published by MIT Press are The Economics of FinTech and Simulation, Optimization, and Machine Learning for Finance. Francesco A. Fabozzi is Managing Editor of the Journal of Financial Data Science, coauthor of two books on asset management, and a doctoral student in data science at Stevens Institute of Technology.
- Product Details
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- ISBN
- 9780262049801
- Format
- Hardback
- Publisher
- The MIT Press, (09 September 2025)
- Number of Pages
- 720
- Language
- English
- Dimensions
- 254 x 203 mm
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