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Combining dimensionality reduction methods with neural networks for realized volatility forecasting Journal article
Andrea Bucci, HE Lidan, Liu Z(劉志). Combining dimensionality reduction methods with neural networks for realized volatility forecasting[J]. Annals of Operations Research, 2023.
Authors:  Andrea Bucci;  HE Lidan;  Liu Z(劉志)
Favorite | TC[WOS]:7 TC[Scopus]:5  IF:4.4/4.4 | Submit date：2023/08/15
Realized Volatility  Artificial Neural Network  Machine-learning  Pca Method  Bayesian Model Averaging  
Forecasting realized volatility with machine learning: Panel data perspective Journal article
Zhu, Haibin, Bai, Lu, He, Lidan, Liu, Zhi. Forecasting realized volatility with machine learning: Panel data perspective[J]. Journal of Empirical Finance, 2023, 73, 251-271.
Authors:  Zhu, Haibin;  Bai, Lu;  He, Lidan;  Liu, Zhi
Favorite | TC[WOS]:5 TC[Scopus]:5  IF:2.1/3.0 | Submit date：2023/09/12
Forecasting  Machine Learning  Panel Data Analysis  Realized Volatility  
Large Deviation Principles of Realized Laplace Transform of Volatility Journal article
Feng, Xinwei, He, Lidan, Liu, Zhi. Large Deviation Principles of Realized Laplace Transform of Volatility[J]. Journal of Theoretical Probability, 2021, 35(1), 186-208.
Authors:  Feng, Xinwei;  He, Lidan;  Liu, Zhi
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:0.8/0.7 | Submit date：2022/03/28
High-frequency Data  Large Deviation  Moderate Deviation  Realized Laplace Transform Of Volatility  Semi-martingale  
Large deviation principles of realized Laplace transform of volatility Journal article
Feng Xinwei, He Lianda, Liu Zhi. Large deviation principles of realized Laplace transform of volatility[J]. Journal of Theoretical Probability, 2021, 35(1), 186–208.
Authors:  Feng Xinwei;  He Lianda;  Liu Zhi
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:0.8/0.7 | Submit date：2022/07/27
High-frequency Data  Large Deviation  Moderate Deviation  Realized Laplace Transform Of Volatility  Semi-martingale  
Testing for pure-jump processes for high frequency data Journal article
Kong, X.B., Liu, Z., Jing, B.Y.. Testing for pure-jump processes for high frequency data[J]. The Annals of Statistics, 2015, 847-877.
Authors:  Kong, X.B.;  Liu, Z.;  Jing, B.Y.
Favorite | TC[WOS]:39 TC[Scopus]:45  IF:3.2/4.8 | Submit date：2022/07/27
Ito Semimartingale  Pure-jump Process  Integrated Volatility  Realized Characteristic Function.  
Testing for pure-jump processes for high-frequency data Journal article
Kong X.-B., Liu Z., Jing B.-Y.. Testing for pure-jump processes for high-frequency data[J]. Annals of Statistics, 2015, 43(2), 847.
Authors:  Kong X.-B.;  Liu Z.;  Jing B.-Y.
Favorite | TC[WOS]:39 TC[Scopus]:45 | Submit date：2018/10/30
Integrated Volatility  Itô Semimartingale  Pure-jump Process  Realized Characteristic Function  
Evaluating the hedging error in price processes with jumps present Journal article
Jing B.Y., Kong X.B., Liu Z., Zhang B.. Evaluating the hedging error in price processes with jumps present[J]. Statistics and its Interface, 2013, 6(4), 413-425.
Authors:  Jing B.Y.;  Kong X.B.;  Liu Z.;  Zhang B.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2019/02/14
Hedging Strategy  Jump Diffusion  Quadratic Variation  Realized Bipower Variation  Thresholdvariation  Variation Of Time  Volatility  
Evaluating the hedging error in price processes with jumps present Journal article
Jing,Bing Yi, Kong,Xin Bing, Liu,Zhi, Zhang,Bo. Evaluating the hedging error in price processes with jumps present[J]. Statistics and its Interface, 2013, 6(4), 413-425.
Authors:  Jing,Bing Yi;  Kong,Xin Bing;  Liu,Zhi;  Zhang,Bo
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:0.3/0.4 | Submit date：2021/03/11
Hedging Strategy  Jump Diffusion  Quadratic Variation  Realized Bipower Variation  Thresholdvariation  Variation Of Time  Volatility