ScholarGate
Asszisztens

Módszerek összehasonlítása

Tekintse át a kiválasztott módszereket egymás mellett; az eltérő sorok kiemelve jelennek meg.

ARIMA (Autoregressive Integrated Moving Average) modell×Kondicionális Érték a Kockázatnál (Elvárt Hanyad)×Exponenciális GARCH (EGARCH)×
TudományterületÖkonometriaPénzügyÖkonometria
MódszercsaládRegression modelRegression modelRegression model
Keletkezés éve201520001991
MegalkotóBox & Jenkins (Box-Jenkins methodology)Rockafellar & Uryasev (2000); Acerbi & Tasche (2002)Nelson
TípusUnivariate time-series modelCoherent tail-risk measureConditional volatility model (asymmetric GARCH variant)
AlapműBox, 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 ↗
Alternatív nevekBox-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
Kapcsolódó554
ÖsszefoglalóARIMA 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.
ScholarGateAdatkészlet
  1. v1
  2. 1 Források
  3. PUBLISHED
  1. v1
  2. 2 Források
  3. PUBLISHED
  1. v1
  2. 2 Források
  3. PUBLISHED

Ugrás a kereséshez Diák letöltése

ScholarGateMódszerek összehasonlítása: ARIMA · Conditional Value-at-Risk · EGARCH. Letöltve 2026-06-19, forrás: https://scholargate.app/hu/compare