ESTIMATING TIME-CHANGES IN NOISY LEVY MODELS

被引：6
|
作者：
Bull, Adam D. [1 ]
机构：
[1] Univ Cambridge, Stat Lab, Cambridge CB3 0WB, England
来源：
ANNALS OF STATISTICS | 2014年 / 42卷 / 05期
基金：
英国工程与自然科学研究理事会;
关键词：
Ito semimartingale; Levy process; microstructure noise; volatility; time-change; HIGH-FREQUENCY DATA; NONPARAMETRIC-ESTIMATION; INTEGRATED VOLATILITY; MICROSTRUCTURE NOISE; DIFFUSION-COEFFICIENT; EFFICIENT ESTIMATION; JUMPS; INFERENCE;
D O I：
10.1214/14-AOS1250
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In quantitative finance, we often model asset prices as a noisy Ito semimartingale. As this model is not identifiable, approximating by a time-changed Levy process can be useful for generative modelling. We give a new estimate of the normalised volatility or time change in this model, which obtains minimax convergence rates, and is unaffected by infinite-variation jumps. In the semimartingale model, our estimate remains accurate for the normalised volatility, obtaining convergence rates as good as any previously implied in the literature.
引用
收藏
页码：2026 / 2057
页数：32
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