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Financial Data and Artificial Intelligence, Volume I: An Introduction to Computational Statistics, Networks, Algorithms, Multivariate Probability Systems, and Bayesian and Kalman-Filtering Analysis

Autor Charles S. Tapiero, Oren J. Tapiero
en Limba Engleză Hardback – 8 aug 2024
The growth of financial complexity, technology, and big data is transforming and integrating computational statistics and data science; in their wake, it’s also changing financial engineering. This first volume introduces elements of computational statistics and data algorithms and considers conventional financial models using statistical models. Such a method provides a more transparent approach to data-science methods when applied to financial data.

This book focuses on financial data including time series, default models, and their increasing complexity in a technological and global financial world. It outlines elements of computational statistics and features applications, including problems and models of credit risks and time series applied to various financial problems. Based on multiple sources, academic research, and applications drawn from various domains and adapted to financial data, this book will be of interest to financial engineering researchers, students, and practitioners.
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Specificații

ISBN-13: 9783030750428
ISBN-10: 3030750426
Pagini: 364
Ilustrații: XXIII, 421 p. 76 illus., 64 illus. in color.
Dimensiuni: 148 x 210 mm
Ediția:2024
Editura: Springer International Publishing
Colecția Palgrave Macmillan
Locul publicării:Cham, Switzerland

Cuprins

Chapter 1. Finance and Data.- Chapter 2. Data Everywhere.- Chapter 3. Data and Statistical Models.- Chapter 4. Computational Statistics and Regressions.- Chapter 5. Algorithms, Glm and Data Reduction.- Chapter 6. Statistical and Data Reduction.- Chapter 7. Multivariate Statistical Distributions.- Chapter 8. Data Information and Entropy.- Chapter 9. Graphs and Networks.- Chapter 10. Modeling Memory and Learning.- Chapter 11. Bayesian Learning.- Chapter 12: Bayesian Networks.- Chapter 13. Bayesian Models and Kalman’s Filter.


Notă biografică

Charles S. Tapiero is the Topfer Chair Distinguished Professor of Financial Engineering and Technology Management at the New York University Tandon School of Engineering, USA. He founded the Department of Finance and Risk Engineering in 2006 and was department head until 2016. Tapiero was co-founder and co-editor-in-chief of Risk and Decision Analysis. His fields of interests span financial engineering, fractional, multi-agents and global finance, and computational and actuarial science.

Oren J. Tapiero is the Chief Science Officer at Cuma Financial, Tel-Aviv, with a PhD in Finance from Bar-Ilan University, Israel, and formerly a post-doctoral student at Université de Paris – La Sorbonne, France. He is also the finance program coordinator at Netanya Academic College, Israel.

Textul de pe ultima copertă

The growth of financial complexity, technology, and big data is transforming and integrating computational statistics and data science; in their wake, it’s also changing financial engineering. This first volume introduces elements of computational statistics and data algorithms and considers conventional financial models using statistical models. Such a method provides a more transparent approach to data-science methods when applied to financial data.

This book focuses on financial data including time series, default models, and their increasing complexity in a technological and global financial world. It outlines elements of computational statistics and features applications, including problems and models of credit risks and time series applied to various financial problems. Based on multiple sources, academic research, and applications drawn from various domains and adapted to financial data, this book will be of interest to financial engineering researchers, students,and practitioners.
Charles S. Tapiero is the Topfer Chair Distinguished Professor of Financial Engineering and Technology Management at the New York University Tandon School of Engineering, USA. He founded the Department of Finance and Risk Engineering in 2006 and was department head until 2016. Tapiero was co-founder and co-editor in chief of Risk and Decision Analysis. His fields of interests span financial engineering, fractional, multi-agents and global finance, and computational and actuarial science.
Oren J. Tapiero is the Chief Science Officer at Cuma Financial, Tel-Aviv, with a PhD in Finance from Bar-Ilan University, Israel, and formerly a post-doctoral student at Université de Paris – La Sorbonne, France. He is also the finance program coordinator at Netanya Academic College, Israel.

Caracteristici

Covers elements of computational as well as data mining, statistical estimation, and probability moments with examples Introduces credit risk, scoring and granting as well as credit derivatives (CDOs) applications Provides a statistical and calculus approach to digitalized data, in both their deterministic and random manifestations