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Quantitative Corporate Finance. Third Edition 2022
・ISBN 978-3-030-87271-7 paper EUR 59.99
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| 著者・編者 | Guerard Jr., John B. / Saxena, Anureet / Gueltekin, Mustafa N., |
|---|---|
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2023 |
| ページ数 | 657 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A01-97891＞ |
解説
This textbook presents a comprehensive treatment of the legal arrangement of the corporation, the instruments and institutions through which capital can be raised, the management of the flow of funds through the individual firm, and the methods of dividing the risks and returns among the various contributors of funds.
Now in its third edition, the book covers a wide range of topics in corporate finance, from time series modeling and regression analysis to multi-factor risk models and the Capital Asset Pricing Model. Guerard, Gultekin and Saxena build significantly on the first edition of the text, but retain the core chapters on cornerstone topics such as mergers and acquisitions, regulatory environments, bankruptcy and various other foundational concepts of corporate finance.
New to the third edition are examinations of APT portfolio selection and time series modeling and forecasting through SAS, SCA and OxMetrics programming, FactSet fundamental data templates. This is intended to be a graduate-level textbook, and could be used as a primary text in upper level MBA and Financial Engineering courses, as well as a supplementary text for graduate courses in financial data analysis and financial investments.
Now in its third edition, the book covers a wide range of topics in corporate finance, from time series modeling and regression analysis to multi-factor risk models and the Capital Asset Pricing Model. Guerard, Gultekin and Saxena build significantly on the first edition of the text, but retain the core chapters on cornerstone topics such as mergers and acquisitions, regulatory environments, bankruptcy and various other foundational concepts of corporate finance.
New to the third edition are examinations of APT portfolio selection and time series modeling and forecasting through SAS, SCA and OxMetrics programming, FactSet fundamental data templates. This is intended to be a graduate-level textbook, and could be used as a primary text in upper level MBA and Financial Engineering courses, as well as a supplementary text for graduate courses in financial data analysis and financial investments.