Big Data Science in Finance - by Irene Aldridge & Marco Avellaneda (Hardcover)

Book Synopsis

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 samples
• Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD)
• Covers vital topics in the field in a clear, straightforward manner
• Compares, contrasts, and discusses Big Data and Small Data
• Includes 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.

From the Back Cover

Big Data Science in Finance delivers the mathematics, theories, and applications of Big Data techniques in finance. Distinguished authors and professionals Irene Aldridge and Marco Avellaneda offer readers brand-new, updated material on the latest world-class research taught in the top Financial Mathematics and Engineering programs in the world. The book's materials have been tested in prestigious classrooms within the Cornell University Financial Engineering program and have proven highly engaging and instructive.

In Big Data Science in Finance, Aldridge and Avellaneda walk readers through the foundational and advanced topics necessary to comprehensively understand the intersection of the worlds of Big Data and finance. Readers will learn about how Big Data differs from Small Data, in-depth techniques in supervised, semi-supervised, and unsupervised learning, the techniques for separating signal from noise, how to effectively deal with missing data values, data clustering, and much more, all in the context of profitable applications of Big Data to finance.

Big Data Science in Finance and its supplementary web resources include lesson plans, end-of-chapter questions, and teaching slides that will aid readers in remembering and retaining the complex material within. Readers will obtain a complete and fulsome understanding of the Big Data techniques currently revolutionizing the finance and investment industries. From fundamental concepts to advanced subjects like supervised and unsupervised machine learning, the book walks readers through every subject they'll need to navigate the intersection of the worlds of Big Data and finance.

Perfect for undergraduate and graduate students in economics and econometrics, finance, applied mathematics, industrial engineering, and business, the book also belongs on the shelves of investment managers, quantitative traders, risk managers, and portfolio managers who aim to improve their ability to find success in the financial markets.

About the Author

IRENE ALDRIDGE is President and Managing Director, Research of AbleMarkets, a company that provides Big Data services to capital markets. She is also a visiting professor at Cornell University.

More information at irenealdridge.com

MARCO AVELLANEDA, PHD, is associated with Finance Concepts, a consulting firm he founded in 2003 and is a faculty member at New York University-Courant. He is regularly published in scientific journals like Quantitative Finance, Risk Magazine, and the International Journal of Theoretical and Applied Finance.

More information at marco-avellaneda.com