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Big Data Science in Finance
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 Big Data Science in 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.
- GenresFinance
336 pages, Hardcover
Published January 27, 2021
7 people are currently reading
53 people want to read
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Displaying 1 - 2 of 2 reviews
April 13, 2024
"Big Data Science in Finance" by Irene Aldridge and Marco Avellaneda is a comprehensive guide that explores the application of big data techniques in the financial industry.
There are a few regression methods that perhaps you and I never heard of, such as KNN. They use this method to recreate the picture of mouth and jaw, just by the input of forehead and eyes. The result from different methods gives funny images, seems like AI still has a long way to go.
The book covers the mathematics, theory, and practical use of these techniques, which are transforming the industry. It is not designed to be accessible to readers with a limited or no IT background, making it an advanced resource for professionals in finance.
The authors, who are experts in quantitative finance and quantitative methodology, provide insights into how big data can be harnessed to improve financial decision-making and risk management.
The book has a rather engaging writing style, as well as its deep knowledge of the subject matter, one will need a good understanding of mathematics to fully grab the details in this book.
There are a few regression methods that perhaps you and I never heard of, such as KNN. They use this method to recreate the picture of mouth and jaw, just by the input of forehead and eyes. The result from different methods gives funny images, seems like AI still has a long way to go.
The book covers the mathematics, theory, and practical use of these techniques, which are transforming the industry. It is not designed to be accessible to readers with a limited or no IT background, making it an advanced resource for professionals in finance.
The authors, who are experts in quantitative finance and quantitative methodology, provide insights into how big data can be harnessed to improve financial decision-making and risk management.
The book has a rather engaging writing style, as well as its deep knowledge of the subject matter, one will need a good understanding of mathematics to fully grab the details in this book.
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March 20, 2021كتاب ثري وممتع.. ننصح بقرائته.
Displaying 1 - 2 of 2 reviews