Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street--applied mathematics and software code are increasingly driving finance and investment-decision tools.
Big Data Science in Finance examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry.
Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world.
Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Comprehensive in scope, this book offers in-depth instruction on how to separate signal from noise, how to deal with missing data values, and how to utilize Big Data techniques in decision-making.
Key topics include data clustering, data storage optimization, Big Data dynamics, Monte Carlo methods and their applications in Big Data analysis, and more.
This valuable book: Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samplesExplains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD)Covers vital topics in the field in a clear, straightforward mannerCompares, contrasts, and discusses Big Data and Small DataIncludes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides Big Data Science in Finance: Mathematics and Applications is an important, up-to-date resource for students in economics, econometrics, finance, applied mathematics, industrial engineering, and business courses, and for investment managers, quantitative traders, risk and portfolio managers, and other financial practitioners.
- Format: Hardback
- Pages: 400 pages
- Publisher: John Wiley & Sons Inc
- Publication Date: 02/02/2021
- Category: Finance & accounting
- ISBN: 9781119602989
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