विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| ARCH मॉडल (ऑटोरिग्रेसिव कंडीशनल हेटेरोस्केडैस्टिसिटी)× | गार्छ मॉडल (अस्थिरता पूर्वानुमान)× | |
|---|---|---|
| क्षेत्र | अर्थमिति | अर्थमिति |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 1982 | 1986 |
| प्रवर्तक≠ | Robert F. Engle | Tim Bollerslev |
| प्रकार | Conditional volatility model | 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 | ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) |
| संबंधित≠ | 6 | 5 |
| सारांश≠ | The ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering. | 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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