Fourier volatility forecasting with high-frequency data and microstructure noise

被引：2

作者：

Barucci, Emilio ^{[1
]}

Magno, Davide ^{[1
]}

Mancino, Maria Elvira ^{[2
]}

机构：

[1] Politecn Milan, Dept Math, I-20133 Milan, Italy

[2] Univ Florence, Dept Math & Decis, I-50124 Florence, Italy

来源：

QUANTITATIVE FINANCE | 2012年 / 12卷 / 02期

关键词：

Monte Carlo methods; Wavelets in finance; Mathematical finance; GARCH models; Derivatives pricing; Financial engineering; Numerical methods for option pricing; INTEGRATED VOLATILITY; MARKET; MODELS;

D O I：

10.1080/14697680903413589

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

We study the forecasting performance of the Fourier volatility estimator in the presence of microstructure noise. Analytical comparison and simulation studies indicate that the Fourier estimator significantly outperforms realized volatility-type estimators, particularly for high-frequency data and when the noise component is relevant. We show that the Fourier estimator generally exhibits better performance, even compared with methods specifically designed to handle market microstructure contamination.

引用

页码：281 / 293

页数：13

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