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20122022
most citedModeling high-frequency financial data by pure jump processes

59 citations · 118 across the 8 of their papers we have counts for

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6 papers · 1 filter

math.ST2020

Large Deviation principles of Realized Laplace Transform of Volatility

Xinwei Feng, Lidan He, Zhi Liu

Under scenario of high frequency data, consistent estimator of realized Laplace transform of volatility is proposed by \citet{TT2012a} and related central limit theorem has been we…

math.ST2020

Edgeworth corrections for spot volatility estimator

Lidan He, Qiang Liu, Zhi Liu

We develop Edgeworth expansion theory for spot volatility estimator under general assumptions on the log-price process that allow for drift and leverage effect. The result is based…

math.ST2018★ 4 cited

High-dimensional covariance matrices in elliptical distributions with application to spherical test

Jiang Hu, Weiming Li, Zhi Liu +1

This paper discusses fluctuations of linear spectral statistics of high-dimensional sample covariance matrices when the underlying population follows an elliptical distribution. Su…

math.ST2016★ 2 cited

Asymptotic properties of the realized skewness and related statistics

Yuta Koike, Zhi Liu

The recent empirical work of Amaya et al. (2015) has pointed out that the realized skewness, which is the sample skewness of intraday high-frequency returns of a financial asset, s…

math.ST2015★ 52 cited

Testing for pure-jump processes for high-frequency data

Xin-Bing Kong, Zhi Liu, Bing-Yi Jing

Pure-jump processes have been increasingly popular in modeling high-frequency financial data, partially due to their versatility and flexibility. In the meantime, several statistic…

math.ST2012★ 59 cited

Modeling high-frequency financial data by pure jump processes

Bing-Yi Jing, Xin-Bing Kong, Zhi Liu

It is generally accepted that the asset price processes contain jumps. In fact, pure jump models have been widely used to model asset prices and/or stochastic volatilities. The que…