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基于 OU-Gamma 时间变换的随机波动率模型：理论与估计AI 解读

We consider stochastic volatility models that are defined by an Ornstein–Uhlenbeck (OU)-Gamma time change. These models are most suitable for modeling financial time series and follow the general framework of the popular non-Gaussian OU models of Barndorff-Nielsen and Shephard. One current problem of these otherwise attractive nontrivial models is, in general, the unavailability of a tractable likelihood-based statistical analysis for the returns of financial assets, which…

价格跳跃与波动率跳跃不相关性的检验AI 解读

We consider a log-price process Xt, which is observed at discrete times 0,Δn, 2Δn,…, and the process has a stochastic squared volatility σt2. Assuming that the price process as well as the volatility process have common jumps, we suggest tests for non-correlation between log-price and squared volatility jumps, or functions of such jumps. Our tests have a prescribed asymptotic level, as the mesh Δn tends to 0 and the observation time Tn tends to ∞. The finite sample…