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Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Thibitisho la Thamani ya Hatari (Matarajio ya Upungufu)×Regression ya Kiasi (Quantile Regression)×
NyanjaFedhaEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili20001978
MwanzilishiRockafellar & Uryasev (2000); Acerbi & Tasche (2002)Koenker & Bassett
AinaCoherent tail-risk measureConditional quantile regression
Chanzo asiliaRockafellar, R. T. & Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, 2(3), 21-41. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Majina mbadalaCVaR, expected shortfall, average value-at-risk, tail VaRconditional quantile regression, regression quantiles, Kantil Regresyon
Zinazohusiana55
MuhtasariConditional Value-at-Risk (CVaR), also called Expected Shortfall, is a coherent tail-risk measure that quantifies the conditional expectation of losses beyond the Value-at-Risk threshold. It was introduced for optimization by Rockafellar and Uryasev (2000) and shown to be coherent by Acerbi and Tasche (2002), and it has replaced VaR as the regulatory standard under Basel III/IV.Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
ScholarGateSeti ya data
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  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: Conditional Value-at-Risk · Quantile Regression. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare