ScholarGate
सहायक

विधियों की तुलना करें

चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।

सामान्यीकृत ऑटोरेग्रेसिव कंडीशनल हेटेरोस्केडैस्टिसिटी (GARCH)×जीजेआर-गार्च (असममित गार्च)×
क्षेत्रअर्थमितिअर्थमिति
परिवारRegression modelRegression model
उद्भव वर्ष19861993
प्रवर्तकTim BollerslevGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
प्रकारConditional volatility modelAsymmetric conditional volatility model
मौलिक स्रोतBollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. DOI ↗
उपनामGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeliasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
संबंधित55
सारांशGARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994).
ScholarGateडेटासेट
  1. v1
  2. 1 स्रोत
  3. PUBLISHED
  1. v1
  2. 2 स्रोत
  3. PUBLISHED

खोज पर जाएँ स्लाइड डाउनलोड करें

ScholarGateविधियों की तुलना करें: GARCH · GJR-GARCH. 2026-06-19 को यहाँ से प्राप्त https://scholargate.app/hi/compare