方法对比
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| 贝叶斯自回归条件异方差模型× | 自回归条件异方差 (ARCH) 模型× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1982 (ARCH); 1989 (Bayesian estimation) | 1982 |
| 提出者≠ | Robert F. Engle (ARCH, 1982); Bayesian treatment: John Geweke (1989) | Robert F. Engle |
| 类型≠ | Volatility model with Bayesian inference | Conditional volatility model |
| 开创性文献 | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ |
| 别名 | Bayesian ARCH, ARCH with Bayesian estimation, Bayesian conditional heteroskedasticity model, B-ARCH | ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model |
| 相关 | 6 | 6 |
| 摘要≠ | The Bayesian ARCH model estimates Engle's Autoregressive Conditional Heteroskedasticity specification within a Bayesian framework. Instead of maximising a likelihood, it combines a prior distribution over the volatility parameters with the data likelihood to obtain a full posterior distribution, providing richer uncertainty quantification than classical maximum-likelihood ARCH. | 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. |
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