方法对比
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| 随机波动率模型 (Heston)× | GARCH 模型（波动率预测）× | |
|---|---|---|
| 领域≠ | 金融学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1993 | 1986 |
| 提出者≠ | Steven L. Heston | Tim Bollerslev |
| 类型≠ | Continuous-time stochastic volatility model | Conditional volatility model |
| 开创性文献≠ | Heston, S. L. (1993). A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options. Review of Financial Studies, 6(2), 327-343. DOI ↗ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗ |
| 别名 | Heston model, SV model, continuous-time stochastic volatility, Stokastik Volatilite Modeli (Heston, SV) | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) |
| 相关 | 5 | 5 |
| 摘要≠ | The stochastic volatility model is a continuous-time option-pricing and risk framework in which volatility follows its own random process rather than staying constant. The Heston model, introduced by Steven Heston in 1993, gives the variance a mean-reverting square-root (CIR) dynamic and yields a closed-form option price; it is the continuous-time counterpart of GARCH. | 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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