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Bootstrapping Nonparametric Prediction Intervals for Conditional Value-at-Risk with Heteroscedasticity
Joint Authors
Torsen, Emmanuel
Seknewna, Lema Logamou
Source
Journal of Probability and Statistics
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-05-07
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Using bootstrap method, we have constructed nonparametric prediction intervals for Conditional Value-at-Risk for returns that admit a heteroscedastic location-scale model where the location and scale functions are smooth, and the function of the error term is unknown and is assumed to be uncorrelated to the independent variable.
The prediction interval performs well for large sample sizes and is relatively small, which is consistent with what is obtainable in the literature.
American Psychological Association (APA)
Torsen, Emmanuel& Seknewna, Lema Logamou. 2019. Bootstrapping Nonparametric Prediction Intervals for Conditional Value-at-Risk with Heteroscedasticity. Journal of Probability and Statistics،Vol. 2019, no. 2019, pp.1-6.
https://search.emarefa.net/detail/BIM-1186866
Modern Language Association (MLA)
Torsen, Emmanuel& Seknewna, Lema Logamou. Bootstrapping Nonparametric Prediction Intervals for Conditional Value-at-Risk with Heteroscedasticity. Journal of Probability and Statistics No. 2019 (2019), pp.1-6.
https://search.emarefa.net/detail/BIM-1186866
American Medical Association (AMA)
Torsen, Emmanuel& Seknewna, Lema Logamou. Bootstrapping Nonparametric Prediction Intervals for Conditional Value-at-Risk with Heteroscedasticity. Journal of Probability and Statistics. 2019. Vol. 2019, no. 2019, pp.1-6.
https://search.emarefa.net/detail/BIM-1186866
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186866