學術產出-專書/專書篇章
文章檢視/開啟
書目匯出
-
題名 Performance-measure approaches for selecting optimum portfolios 作者 陳鴻毅
Cheng-Few Lee;Hong-Yi Chen;Jessica Shin-Ying Mai貢獻者 財管系 日期 2010-05 上傳時間 13-十一月-2014 18:04:58 (UTC+8) 摘要 Quantitative finance is a combination of economics, accounting, statistics, econometrics, mathematics, stochastic process, and computer science and technology. Increasingly, the tools of financial analysis are being applied to assess, monitor, and mitigate risk, especially in the context of globalization, market volatility, and economic crisis. This three-volume handbook, comprised of over 100 chapters, is the most comprehensive resource in the field to date, integrating the most current theory, methodology, policy, and practical applications. Showcasing contributions from an international array of experts, the Handbook of Quantitative Finance and Risk Management is unparalleled in the breadth and depth of its coverage. Volume 1 presents an overview of quantitative finance and risk management research, covering the essential theories, policies, and empirical methodologies used in the field. Chapters provide in-depth discussion of portfolio theory and investment analysis. Volume 2 covers options and option pricing theory and risk management. Volume 3 presents a wide variety of models and analytical tools. Throughout, the handbook offers illustrative case examples, worked equations, and extensive references; additional features include chapter abstracts, keywords, and author and subject indices. From "arbitrage" to "yield spreads," the Handbook of Quantitative Finance and Risk Management will serve as an essential resource for academics, educators, students, policymakers, and practitioners. 關聯 Handbook of Quantitative Finance and Risk Management, Springer, pp.125-136
ISBN 978-0-387-77117-5資料類型 book/chapter dc.contributor 財管系 en_US dc.creator (作者) 陳鴻毅 zh_TW dc.creator (作者) Cheng-Few Lee;Hong-Yi Chen;Jessica Shin-Ying Mai en_US dc.date (日期) 2010-05 en_US dc.date.accessioned 13-十一月-2014 18:04:58 (UTC+8) - dc.date.available 13-十一月-2014 18:04:58 (UTC+8) - dc.date.issued (上傳時間) 13-十一月-2014 18:04:58 (UTC+8) - dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/71428 - dc.description.abstract (摘要) Quantitative finance is a combination of economics, accounting, statistics, econometrics, mathematics, stochastic process, and computer science and technology. Increasingly, the tools of financial analysis are being applied to assess, monitor, and mitigate risk, especially in the context of globalization, market volatility, and economic crisis. This three-volume handbook, comprised of over 100 chapters, is the most comprehensive resource in the field to date, integrating the most current theory, methodology, policy, and practical applications. Showcasing contributions from an international array of experts, the Handbook of Quantitative Finance and Risk Management is unparalleled in the breadth and depth of its coverage. Volume 1 presents an overview of quantitative finance and risk management research, covering the essential theories, policies, and empirical methodologies used in the field. Chapters provide in-depth discussion of portfolio theory and investment analysis. Volume 2 covers options and option pricing theory and risk management. Volume 3 presents a wide variety of models and analytical tools. Throughout, the handbook offers illustrative case examples, worked equations, and extensive references; additional features include chapter abstracts, keywords, and author and subject indices. From "arbitrage" to "yield spreads," the Handbook of Quantitative Finance and Risk Management will serve as an essential resource for academics, educators, students, policymakers, and practitioners. en_US dc.format.extent 142 bytes - dc.format.mimetype text/html - dc.language.iso en_US - dc.relation (關聯) Handbook of Quantitative Finance and Risk Management, Springer, pp.125-136 en_US dc.relation (關聯) ISBN 978-0-387-77117-5 en_US dc.title (題名) Performance-measure approaches for selecting optimum portfolios en_US dc.type (資料類型) book/chapter en
