Heavy-tailed distributions and robustness in economics and finance [electronic resource]

• 作者： Ibragimov, Marat.
• 其他作者：
  • Ibragimov, Rustam.
  • Walden, Johan.
  • SpringerLink (Online service)
• 其他題名：
  • Lecture notes in statistics
• 出版： Cham : Springer International Publishing :Imprint: Springer
• 叢書名： Lecture notes in statisticsv.214
• 主題： Distribution (Probability theory) , Statistics , Statistics for Business/Economics/Mathematical Finance/Insurance. , Statistical Theory and Methods. , Econometrics
• ISBN： 9783319168777 (electronic bk.) 、 9783319168760 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: Introduction -- Implications of Heavy-tailed ness -- Inference and Empirical Examples -- Conclusion.
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• 摘要註: This book focuses on general frameworks for modeling heavy-tailed distributions in economics, finance, econometrics, statistics, risk management and insurance. A central theme is that of (non-)robustness, i.e., the fact that the presence of heavy tails can either reinforce or reverse the implications of a number of models in these fields, depending on the degree of heavy-tailedness. These results motivate the development and applications of robust inference approaches under heavy tails, heterogeneity and dependence in observations. Several recently developed robust inference approaches are discussed and illustrated, together with applications.
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