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Bibliografie

Conference Paper (international conference)

Estimation of Conditional Value-at-Risk in Linear Model

Jurečková Jana, Picek J., Kalina Jan

: Combining, Modelling and Analyzing Imprecision, Randomness and Dependence, p. 200-207

: International Conference on Soft Methods in Probability and Statistics 2024 - SMPS 2024 /11./, (Salzburg, AT, 20240903)

: GA22-03636S, GA ČR, GA24-11146S, GA ČR

: conditional-value-at-risk, averaged regression quantile, two-step regression quantile

: 10.1007/978-3-031-65993-5_24

: https://library.utia.cas.cz/separaty/2024/SI/jureckova-0598425.pdf

(eng): The conditional value-at-risk (CVaR) represents a popular risk measure often exploited e.g. within portfolio optimization. The situation with a nuisance linear regression is considered here; in other words, we do not observe directly the loss Z of interest, but only Y=\beta _0+X\beta+Z, where the covariates are not under our control. We propose a novel estimator of CVaR(Z) based on the averaged two-step regression quantile combined with an R-estimate of regression parameters.

: BB

: 10103