विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| टाइम-वेरिंग पैरामीटर एआरसीएच मॉडल (TVP-ARCH)× | गार्छ मॉडल (अस्थिरता पूर्वानुमान)× | |
|---|---|---|
| क्षेत्र | अर्थमिति | अर्थमिति |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 1980s–1990s | 1986 |
| प्रवर्तक≠ | Extension of Engle (1982) ARCH; TVP-ARCH formalization credited to Nicholls & Quinn and subsequent state-space literature | Tim Bollerslev |
| प्रकार≠ | Conditional heteroscedasticity model with time-varying coefficients | Conditional volatility model |
| मौलिक स्रोत≠ | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗ |
| उपनाम | TVP-ARCH, time-varying ARCH, adaptive ARCH, state-space ARCH | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) |
| संबंधित | 5 | 5 |
| सारांश≠ | The Time-Varying Parameter ARCH (TVP-ARCH) model extends the classic ARCH framework by allowing both the conditional mean coefficients and the ARCH variance parameters to drift over time according to a random-walk or state-space process. This makes it possible to capture structural shifts in volatility dynamics without imposing a fixed parameter regime. | The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series. |
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