ScholarGate
Assistent

Sammenlign metoder

Gennemgå dine valgte metoder side om side; rækker, der afviger, er fremhævet.

Betinget Value-at-Risk (Forventet Underskud)×ARIMA (Autoregressive Integrated Moving Average) Model×Kvantilregression×
FagområdeFinansieringØkonometriØkonometri
FamilieRegression modelRegression modelRegression model
Oprindelsesår200020151978
OphavspersonRockafellar & Uryasev (2000); Acerbi & Tasche (2002)Box & Jenkins (Box-Jenkins methodology)Koenker & Bassett
TypeCoherent tail-risk measureUnivariate time-series modelConditional quantile regression
Oprindelig kildeRockafellar, R. T. & Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, 2(3), 21-41. DOI ↗Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
AliasserCVaR, expected shortfall, average value-at-risk, tail VaRBox-Jenkins model, ARIMA(p,d,q), ARIMA Modeliconditional quantile regression, regression quantiles, Kantil Regresyon
Relaterede555
ResuméConditional 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.ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).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.
ScholarGateDatasæt
  1. v1
  2. 2 Kilder
  3. PUBLISHED
  1. v1
  2. 1 Kilder
  3. PUBLISHED
  1. v1
  2. 2 Kilder
  3. PUBLISHED

Gå til søgning Hent slides

ScholarGateSammenlign metoder: Conditional Value-at-Risk · ARIMA · Quantile Regression. Hentet 2026-06-18 fra https://scholargate.app/da/compare