论文标题
可行的推断布朗时代的随机波动率
Feasible Inference for Stochastic Volatility in Brownian Semistationary Processes
论文作者
论文摘要
本文研究了非半马丁纳尔环境中布朗分子过程的综合功率波动过程的许多估计量的有限样本行为。我们为集成挥发率建立了三个一致的可行估计量，两个源自参数方法，一个非参数。然后，我们使用仿真研究将估计器的收敛性相互比较，并将其与不可行的估计器的基准进行比较。我们进一步建立了不可行估计器的渐近方差的界限，并评估是否可以将适用于不可行的估计器的中心极限定理转化为可行的非参数估计仪的可行限制定理。
This article studies the finite sample behaviour of a number of estimators for the integrated power volatility process of a Brownian semistationary process in the non semi-martingale setting. We establish three consistent feasible estimators for the integrated volatility, two derived from parametric methods and one non-parametrically. We then use a simulation study to compare the convergence properties of the estimators to one another, and to a benchmark of an infeasible estimator. We further establish bounds for the asymptotic variance of the infeasible estimator and assess whether a central limit theorem which holds for the infeasible estimator can be translated into a feasible limit theorem for the non-parametric estimator.
