Applied quantitative finance
著者
書誌事項
Applied quantitative finance
(Statistics and computing)
Springer, c2017
3rd ed
大学図書館所蔵 全6件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Previous edition: 2008
Includes bibliographical references
内容説明・目次
内容説明
This volume provides practical solutions and introduces recent theoretical developments in risk management, pricing of credit derivatives, quantification of volatility and copula modeling. This third edition is devoted to modern risk analysis based on quantitative methods and textual analytics to meet the current challenges in banking and finance. It includes 14 new contributions and presents a comprehensive, state-of-the-art treatment of cutting-edge methods and topics, such as collateralized debt obligations, the high-frequency analysis of market liquidity, and realized volatility.
The book is divided into three parts: Part 1 revisits important market risk issues, while Part 2 introduces novel concepts in credit risk and its management along with updated quantitative methods. The third part discusses the dynamics of risk management and includes risk analysis of energy markets and for cryptocurrencies. Digital assets, such as blockchain-based currencies, have become popular b
ut are theoretically challenging when based on conventional methods. Among others, it introduces a modern text-mining method called dynamic topic modeling in detail and applies it to the message board of Bitcoins.
The unique synthesis of theory and practice supported by computational tools is reflected not only in the selection of topics, but also in the fine balance of scientific contributions on practical implementation and theoretical concepts. This link between theory and practice offers theoreticians insights into considerations of applicability and, vice versa, provides practitioners convenient access to new techniques in quantitative finance. Hence the book will appeal both to researchers, including master and PhD students, and practitioners, such as financial engineers. The results presented in the book are fully reproducible and all quantlets needed for calculations are provided on an accompanying website.
The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book.
目次
Part I Market Risk: VaR in High-Dimensional Systems.- Multivariate Volatility Models.- Portfolio Selection with Spectral Risk Measures.- Implementation of Local Stochastic Volatility Model.- Part II Credit Risk: Estimating DTD via Sequential Monte Carlo.- Risk Measurement with Spectral Capital Allocation.- Market Based Credit Rating and its Applications.- Using Public Information to Predict Corporate Default Risk.- Stress Testing in Credit Portfolio Models.- Penalized Independent Factor.- Term Structure of Loss Cascades in Portfolio Securitisation.- Credit Rating Score Analysis.- Part III Dynamics Risk Measurement: Copulae in High Dimensions - An Introduction.- Measuring and Modeling Risk Using High-Frequency Data.- Measuring Financial Risk in Energy Markets.- Risk Analysis of Cryptocurrency as an Alternative Asset Class.- Time Varying Quantile Lasso.- Dynamic Topic Modelling for Cryptocurrency Community Forums.
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