Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Modeli Bayesian GARCH× | Modeli GARCH (Parashikimi i Volatilitetit)× | |
|---|---|---|
| Fusha | Ekonometri | Ekonometri |
| Familja | Regression model | Regression model |
| Viti i origjinës≠ | 1989–2000 | 1986 |
| Krijuesi≠ | Geweke (1989); further developed by Nakatsuma (2000) and Bauwens & Lubrano (1998) | Tim Bollerslev |
| Lloji≠ | Bayesian volatility model | Conditional volatility model |
| Burimi themelues≠ | Geweke, J. (1989). Exact predictive densities for linear models with ARCH disturbances. Journal of Econometrics, 40(1), 63–86. DOI ↗ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗ |
| Emërtime të tjera | Bayesian GARCH, BGARCH, GARCH with Bayesian inference, Bayesian volatility model | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) |
| Të lidhura≠ | 4 | 5 |
| Përmbledhja≠ | The Bayesian GARCH model combines the GARCH framework for time-varying volatility with Bayesian posterior inference. Instead of maximising a likelihood, it specifies prior distributions for the GARCH parameters and draws from the resulting posterior — typically via Markov chain Monte Carlo (MCMC) — to quantify both point estimates and full uncertainty about volatility dynamics. | 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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