Beschreibung
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.
Autorenporträt
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.
Herstellerkennzeichnung:
Springer Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE
E-Mail: juergen.hartmann@springer.com
