混合GARCH模型下股票市场跳跃形态分析

在跳跃扩散模型下,假定跳跃强度服从门限自回归模型(self-threshold autoregressive model,SETAR)以反映跳跃强度的结构性突变,并使用GARCH模型描述收益率波动扩散形态.以受波动率影响的跳跃强度控制跳跃行为发生概率,并以受跳跃行为影响的GARCH模型控制正常扩散过程,构建了SETARGARCH模型.以上证房地产指数为例,实证研究发现,股指存在门限效应,GARCH效应明显,跳跃突变发生的概率为35.21%.资产收益率总体方差中有较大的部分是由跳跃行为异常所引起.历史波动率直接影响未来跳跃强度预期,历史跳跃行为干扰加剧了当期收益率波动扩散,波动率扩散和跳跃行为具有双向反馈机制.

Analysis of the Jump Dynamics of Stock Market Based on the Mixed GARCH Model

Based on the jump diffusion model， jump intensity is assumed to follow the self-threshold autoregressive model (SETAR) to reflect the structural break of jump density， and the GARCH model is used to describe the diffusion process of asset price volatility. The SETAR-GARCH model is constructed by making the jump density control probability of jump dynamics in which volatility affects jump density and by making the GARCH model control diffusion process in which jump dynamics influences volatility. Taking Shanghai real estate index for example， the empirical study finds that Shanghai real estate index exerts the threshold effect and significant GARCH effect， with 35. 21% jump mutation probability. The total variance of asset returns is largely caused by extreme jump dynamics. Investors’ evaluation of historical volatility directly affects jump intensity expectation， and the interference from historical jump dynamics has exacerbated the current volatility in the diffusion process， which illustrates that volatility diffusion processes and jump dynamics have a two-way feedback effect.