Jump Variation Estimation with Noisy High Frequency Financial Data via Wavelets

Jump Variation Estimation with Noisy High Frequency Financial Data via Wavelets

This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatility in finance for portfolio allocation, derivativ...

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Bibliographic Details
Main Authors: Xin Zhang, Donggyu Kim, Yazhen Wang
Format: Article
Language:English
Published: MDPI AG 2016-08-01
Series:Econometrics
Subjects:
high frequency financial data
jump variation
realized volatility
integrated volatility
microstructure noise
wavelet methods
nonparametric methods
Online Access:http://www.mdpi.com/2225-1146/4/3/34

Internet

http://www.mdpi.com/2225-1146/4/3/34

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