| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w10579 |
| 来源ID | Working Paper 10579 |
| Maximum Likelihood Estimation of Stochastic Volatility Models | |
| Yacine Ait-Sahalia; Robert Kimmel | |
| 发表日期 | 2004-06-28 |
| 出版年 | 2004 |
| 语种 | 英语 |
| 摘要 | We develop and implement a new method for maximum likelihood estimation in closed-form of stochastic volatility models. Using Monte Carlo simulations, we compare a full likelihood procedure, where an option price is inverted into the unobservable volatility state, to an approximate likelihood procedure where the volatility state is replaced by the implied volatility of a short dated at-the-money option. We find that the approximation results in a negligible loss of accuracy. We apply this method to market prices of index options for several stochastic volatility models, and compare the characteristics of the estimated models. The evidence for a general CEV model, which nests both the affine model of Heston (1993) and a GARCH model, suggests that the elasticity of variance of volatility lies between that assumed by the two nested models. |
| 主题 | Financial Economics |
| URL | https://www.nber.org/papers/w10579 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/568208 |
| 推荐引用方式 GB/T 7714 | Yacine Ait-Sahalia,Robert Kimmel. Maximum Likelihood Estimation of Stochastic Volatility Models. 2004. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w10579.pdf（526KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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