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Computational Finance Mathematical Finance and Financial Computing with Real-World Applications [#1043403]

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Computational Finance: Mathematical Finance and Financial Computing with Real-World Applications
English | 2026 | ISBN: 3112228170 | 535 pages | True PDF,EPUB | 57.81 MB
Mathematical finance and computing are parts of nearly all aspects of everyday life. The discipline has underpinned beneficial modern capabilities, financial modelling, predictive analysis and optimization including search algorithms, financial data visualisation, financial computing, numerical analysis for predictions, and quantitative risk management. Mathematics and computer science are constantly evolving and contributing to most areas of science, engineering and finance; therefore, future generations of mathematical scientists should reassess the increasingly cross-disciplinary nature of the mathematical sciences. Mathematical Finance and Financial Computing with Real-World Applications presents current scientific and technological innovations from leading academics, researchers, and experts across the globe in mathematical sciences and computing.


The volume will discuss new technical ideas and features that can be incorporated into day-to-day life for the benefit of society. A diversified spectrum of scientific advancements is discussed, including applications of stochastics differential equation, numerical analysis, financial computation, computation dynamics, nonlinear optimization, machine learning, and artificial intelligence. Readers will explore diverse ideas and innovations in the field of financial computation and its growing connections to various fields of mathematics and statistics.
This book will benefit young and middle level researchers in quantitative finance, financial computing and quantitative risk management. Professors, students, and researchers working in research areas such as mathematical finance, financial modelling, asset pricing, volatility modelling, risk analysis, predictive modelling, portfolio optimization, statistical finance, financial computing, financial engineering, financial data analysis and data science can use this book to improve their results.

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