We propose novel nonparametric estimators for stochastic volatility and the volatility of volatility. In doing so, we relax the assumption of a constant volatility of volatility and therefore, we allow the volatility of volatility to vary over time. Our methods are exceedingly simple and far simpler than the existing ones. Using intraday prices for the Standard & Poor's 500 equity index, the estimates revealed strong evidence that both volatility and the volatility of volatility are stochastic. We also proceeded in a Monte Carlo simulation analysis and found that the estimates were reasonably accurate. Such evidence implies that the stochastic volatility models proposed in the literature with constant volatility of volatility may fail to approximate the discrete-time short rate dynamics.
机构:
Sichuan Univ, Dept Math, Chengdu 610064, Sichuan, Peoples R ChinaSichuan Univ, Dept Math, Chengdu 610064, Sichuan, Peoples R China
Yang, Ben-Zhang
Yue, Jia
论文数: 0引用数: 0
h-index: 0
机构:
South Western Univ Finance & Econ, Dept Econ Math, Chengdu 610074, Sichuan, Peoples R ChinaSichuan Univ, Dept Math, Chengdu 610064, Sichuan, Peoples R China
Yue, Jia
Wang, Ming-Hui
论文数: 0引用数: 0
h-index: 0
机构:
Sichuan Univ, Dept Math, Chengdu 610064, Sichuan, Peoples R ChinaSichuan Univ, Dept Math, Chengdu 610064, Sichuan, Peoples R China
Wang, Ming-Hui
Huang, Nan-Jing
论文数: 0引用数: 0
h-index: 0
机构:
Sichuan Univ, Dept Math, Chengdu 610064, Sichuan, Peoples R ChinaSichuan Univ, Dept Math, Chengdu 610064, Sichuan, Peoples R China