Hawkes-driven stochastic volatility models: goodness-of-fit testing of alternative intensity specifications with S &P500 data
提出一种由霍克斯过程驱动的价格与波动率共同跳跃的随机波动率模型，并开发可行的极大似然估计方法。基于S&P500高频数据检验不同跳跃强度设定，发现强度与资产波动率呈线性关系的假设拟合最优，表明跳跃具有自激特性。
Abstract We introduce a novel stochastic volatility model with price and volatility co-jumps driven by Hawkes processes and develop a feasible maximum-likelihood procedure to estimate the parameters driving the jump intensity. Using S &P500 high-frequency prices over the period May 2007–August 2021, we then perform a goodness-of-fit test of alternative jump intensity specifications and find that the hypothesis of the intensity being linear in the asset volatility provides the relatively best fit, thereby suggesting that jumps have a self-exciting nature.