{"product_id":"simulation-optimization-and-machine-learning-for-finance-second-edition-9780262049801","title":"Simulation, Optimization, and Machine Learning for Finance, Second Edition","description":"\u003cp\u003e • Author(s): Dessislava A. Pachamanova\u003cbr\u003e • Publisher: MIT Press\u003cbr\u003e • Publisher Imprint: MIT Text Books\u003cbr\u003e • BISAC: Finance - Financial Risk Management\u003c\/p\u003e\u003cp\u003e\u003cb\u003eA comprehensive guide to simulation, optimization, and machine learning for finance, covering theoretical foundations, practical applications, and data-driven decision-making.\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003ci\u003eSimulation, Optimization, and Machine Learning for Finance\u003c\/i\u003e 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 \u003ci\u003eSimulation and Optimization in Finance\u003c\/i\u003e, 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. \u003cp\u003e\u003c\/p\u003eBeginning 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. \u003cp\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eProvides a structured introduction to probability, inferential statistics, and data science\u003c\/li\u003e\n\u003cli\u003eExplores cutting-edge techniques in simulation modeling, optimization, and machine learning\u003c\/li\u003e\n\u003cli\u003eDemonstrates real-world asset allocation strategies, advanced portfolio risk measures, and fixed-income portfolio management using quantitative tools\u003c\/li\u003e\n\u003cli\u003eCovers factor models and stochastic processes in asset pricing\u003c\/li\u003e\n\u003cli\u003eIntegrates capital budgeting and real options analysis, emphasizing the role of uncertainty and quantitative modeling in long-term financial decision-making\u003c\/li\u003e\n\u003cli\u003eIs suitable for practitioners, students, and self-learners\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"MIT Press","offers":[{"title":"Hardcover","offer_id":46296553324695,"sku":"9780262049801","price":8580.0,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9780262049801.webp?v=1769304996","url":"https:\/\/atlanticbooks.com\/products\/simulation-optimization-and-machine-learning-for-finance-second-edition-9780262049801","provider":"Atlantic Books","version":"1.0","type":"link"}