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Модель ARIMA (авторегрессионная интегрированная скользящая средняя)×Условный риск (Expected Shortfall)×Экспоненциальный GARCH (EGARCH)×
ОбластьЭконометрикаФинансыЭконометрика
СемействоRegression modelRegression modelRegression model
Год появления201520001991
Автор методаBox & Jenkins (Box-Jenkins methodology)Rockafellar & Uryasev (2000); Acerbi & Tasche (2002)Nelson
ТипUnivariate time-series modelCoherent tail-risk measureConditional volatility model (asymmetric GARCH variant)
Основополагающий источникBox, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Rockafellar, R. T. & Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, 2(3), 21-41. DOI ↗Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗
Другие названияBox-Jenkins model, ARIMA(p,d,q), ARIMA ModeliCVaR, expected shortfall, average value-at-risk, tail VaRexponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH
Связанные554
СводкаARIMA 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).Conditional 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.EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance.
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ScholarGateСравнение методов: ARIMA · Conditional Value-at-Risk · EGARCH. Получено 2026-06-19 из https://scholargate.app/ru/compare