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Large Deviation Principles of Realized Laplace Transform of Volatility Journal article
Journal of Theoretical Probability, 2022,Volume: 35,Issue: 1,Page: 186-208
Authors:  Feng, Xinwei;  He, Lidan;  Liu, Zhi
Favorite |  | TC[WOS]:0 TC[Scopus]:0 | Submit date:2022/03/28
High-frequency Data  Large Deviation  Moderate Deviation  Realized Laplace Transform Of Volatility  Semi-martingale  
Jumps at ultra-high frequency: Evidence from the Chinese stock market Journal article
Pacific Basin Finance Journal, 2021,Volume: 68,Issue: 101420
Authors:  Zhang,Chuanhai;  Liu,Zhi;  Liu,Qiang
Favorite |  | TC[WOS]:0 TC[Scopus]:1 | Submit date:2021/03/11
Jumps  Market Microstructure Noise  Pre-averaging  Truncated Bi-power Variation  Ultra High Frequency Data  
Statistical Inference for spot correlation and spot market Beta under infinite variation jumps Journal article
Journal of Financial Econometrics, 2020,Page: 1-30
Authors:  Liu, Q.;  Liu, Z.
Favorite |  | TC[WOS]:0 TC[Scopus]:0 | Submit date:2022/07/27
High frequency data  
Edgeworth corrections for spot volatility estimator Journal article
Statistics and Probability Letters, 2020,Volume: 164
Authors:  He,Lidan;  Liu,Qiang;  Liu,Zhi
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Central Limit Theorem  Confidence Interval  Edgeworth Expansion  High Frequency Data  Spot Volatility  
Asymptotic properties of the realized skewness and related statistics Journal article
Annals of the Institute of Statistical Mathematics, 2019
Authors:  Yuta Koike;  Zhi Liu
Favorite |  | TC[WOS]:0 TC[Scopus]:1 | Submit date:2019/06/10
High-frequency Data  Realized Skewness  Stochastic Sampling  Itô Semimartingale  Jumps  Microstructure Noise  
Realized Laplace Transforms for Pure Jump Semi-martingales with Presence of Microstructure Noise Journal article
Soft Computing, 2019
Authors:  Li Wang;  Zhi Liu;  Xiaochao Xia
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High-frequency Data  Laplace Transform  Microstructure Noise  Pure Jump Processes  
Realized Laplace Transform of Volatility with Microstructure Noise Journal article
Scandinavian Journal of Statistics, 2019
Authors:  Li Wang;  Zhi Liu;  Xiaochao Xia
Favorite |  | TC[WOS]:0 TC[Scopus]:0 | Submit date:2019/06/10
High-frequency Data  Stable Convergence  Laplace Transform Of Volatility  Microstructure Noise  Pre-averaging  
Rate efficient estimation of realized Laplace transform of volatility with microstructure noise Journal article
SCANDINAVIAN JOURNAL OF STATISTICS, 2019,Volume: 46,Issue: 3,Page: 920-953
Authors:  Li Wang;  Zhi Liu;  Xiaochao Xia
Favorite |  | TC[WOS]:2 TC[Scopus]:2 | Submit date:2020/05/22
High-frequency Data  Stable Convergence  Laplace Transform Of Volatility  Microstructure Noise  Pre-averaging  
Rate efficient estimation of realized Laplace transform of volatility with microstructure noise Journal article
SCANDINAVIAN JOURNAL OF STATISTICS, 2019,Volume: 46,Issue: 3,Page: 920-953
Authors:  Li Wang;  Zhi Liu;  Xiaochao Xia
Favorite |  | TC[WOS]:2 TC[Scopus]:2 | Submit date:2020/06/03
High-frequency Data  Stable Convergence  Laplace Transform Of Volatility  Microstructure Noise  Pre-averaging  
Abnormal dynamic functional connectivity and brain states in Alzheimer’s diseases: functional near-infrared spectroscopy study Journal article
Neurophotonics, 2019,Volume: 6,Issue: 2,Page: 025010
Authors:  Haijing Niu;  Zhaojun Zhu;  Mengjing Wan;  Xuanyu Li;  Zhen Yuan;  Yu Sun;  Ying Han
Adobe PDF | Favorite |  | TC[WOS]:22 TC[Scopus]:0 | Submit date:2022/08/21
CommunicAtion WithIn The BraIn Is Highly Dynamic. AlzheI.e.’s dIseAse (Ad) ExhibIts Dynamic.progression COrrespondIng To a DeclIne In MemOry And Cognition. HoWever, Little Is Known Of wheTher BraIn Dynamic. Are dIsrupted In Ad And Its Prodromal Stage, Mild CognitI.e.impairment (Mci). FOr Our Study, We AcquI.e. High samplIng RAte Functional near-InfrAred Spectroscopy imagIng DAta At Rest From The EntI.e.cOrtex Of 23 pAtients With Ad Dementia, 25 pAtients With Amnestic Mild CognitI.e.impairment (aMci), And 30 age-mAtched Healthy Controls (Hcs). slidIng-wIndow cOrrelAtion And K-means clusterIng Analyses Were Used To Construct Dynamic.Functional Connectivity (Fc) Maps FOr Each Participant. We dIscovered thAt The BraIn’s Dynamic.Fc Variability Strength (q) Significantly IncreAsed In Both aMci And Ad Group As compAred To Hcs. usIng The q Value As a meAsurement, The clAssificAtion perFOrmance ExhibI.e. a Good poWer In differentiAtIng aMci [Area Under The Curve (Auc ¼ 82.5%)] Or Ad (Auc ¼ 86.4%) From Hcs. furThermOre, We Identified Two abnOrmal BraIn Fc stAtes In The Ad Group, Of Which The Occurrence Frequency (f) ExhibI.e. a Significant decreAse FOr The First-level Fc stAte (stAte 1) And a Significant IncreAse FOr The Second-level Fc stAte (stAte 2). We Also Found thAt The abnOrmal f In These Two stAtes Significantly cOrrelAted With The CognitI.e.impairment In pAtients. These fIndIngs provI.e.The First EvI.e.ce To demonstRAte The dIsruptions Of Dynamic.BraIn Connectivity In aMci And Ad And Extend The trAditional stAtic (I.e., tI.e.averaged) Fc fIndIngs In The dIseAse (I.e., dIsconnection Syndrome) And Thus provI.e.Insights InTo UnderstAndIng The pAthophysiological mechanIsms occurrIng In aMci And Ad.