Financial Data and Artificial Intelligence, Volume I
An Introduction to Computational Statistics, Networks, Algorithms, Multivariate Probability Systems, and Bayesian and Kalman-Filtering Analysis
Published on 8. August 2024
Online / Databases
XXIII, 421 pages
978-3-030-75043-5 (ISBN)
Description
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.
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.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
XXIII, 421 p. 76 illus., 64 illus. in color.
ISBN-13
978-3-030-75043-5 (9783030750435)
DOI
10.1007/978-3-030-75043-5
Schweitzer Classification
Other editions
Additional editions
Charles S. Tapiero | Oren J. Tapiero
Financial Data and Artificial Intelligence, Volume I
An Introduction to Computational Statistics, Networks, Algorithms, Multivariate Probability Systems, and Bayesian and Kalman-Filtering Analysis
Book
08/2024
1st Edition
Palgrave Macmillan
€106.99
The article will not be published
Persons
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.
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.
Content
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.