Heavy-Tailed Distributions and Robustness in Economics and Finance
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 implication...
| Main Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2015, 2015
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| Edition: | 1st ed. 2015 |
| Series: | Lecture Notes in Statistics
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
| Summary: | 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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| Physical Description: | XIV, 119 p. 9 illus online resource |
| ISBN: | 9783319168777 |