Financial Data and Artificial Intelligence, Volume I

An Introduction to Computational Statistics, Networks, Algorithms, Multivariate Probability Systems, and Bayesian and Kalman-Filtering Analysis
1. Auflage 2024
ISBN: 978-3-030-75042-8
Verlag: Palgrave Macmillan

Buch, Englisch, 421 Seiten, Format (B × H): 148 mm x 210 mm

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.

Zielgruppe

Research

Autoren/Hrsg.

Tapiero, Charles S.

Tapiero, Oren J.

Fachgebiete

• Mathematik | Informatik Mathematik Mathematik Interdisziplinär Finanz- und Versicherungsmathematik
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Finanzsektor & Finanzdienstleistungen: Allgemeines
• Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Anlagen & Wertpapiere

Inhaltsverzeichnis

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.

Über Autor(innen)

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.