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商品詳細
Financial Data Analytics: Theory and Application. 2022 ed.
・ISBN 978-3-030-83801-0 paper EUR 169.99
￥45,437.- (税込) ※（※）価格はご注文時の参考価格となります。
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お気に入り
★★★
| 著者・編者 | Derindere Koeseoglu, Sinem (ed.), |
|---|---|
| シリーズ | (Contributions to Finance and Accounting) |
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2023 |
| ページ数 | 384 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A02-79753＞ |
解説
?This book presents both theory of financial data analytics, as well as comprehensive insights into the application of financial data analytics techniques in real financial world situations. It offers solutions on how to logically analyze the enormous amount of structured and unstructured data generated every moment in the finance sector. This data can be used by companies, organizations, and investors to create strategies, as the finance sector rapidly moves towards data-driven optimization.
This book provides an efficient resource, addressing all applications of data analytics in the finance sector. International experts from around the globe cover the most important subjects in finance, including data processing, knowledge management, machine learning models, data modeling, visualization, optimization for financial problems, financial econometrics, financial time series analysis, project management, and decision making. The authors provide empirical evidence as examples of specific topics. By combining both applications and theory, the book offers a holistic approach.
Therefore, it is a must-read for researchers and scholars of financial economics and finance, as well as practitioners interested in a better understanding of financial data analytics.
This book provides an efficient resource, addressing all applications of data analytics in the finance sector. International experts from around the globe cover the most important subjects in finance, including data processing, knowledge management, machine learning models, data modeling, visualization, optimization for financial problems, financial econometrics, financial time series analysis, project management, and decision making. The authors provide empirical evidence as examples of specific topics. By combining both applications and theory, the book offers a holistic approach.
Therefore, it is a must-read for researchers and scholars of financial economics and finance, as well as practitioners interested in a better understanding of financial data analytics.