The Citing articles tool gives a list of articles citing the current article. The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program . You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).
Cited article:
Arnaud Gloter , Jean Jacod
ESAIM: PS, 5 (2001) 243-260
Published online: 2002-08-15
This article has been cited by the following article(s):
83 articles
Volatility estimation of hidden Markov processes and adaptive filtration
Yury A. Kutoyants Stochastic Processes and their Applications 173 104381 (2024) https://doi.org/10.1016/j.spa.2024.104381
Volatility of volatility: Estimation and tests based on noisy high frequency data with jumps
Yingying Li, Guangying Liu and Zhiyuan Zhang Journal of Econometrics 229 (2) 422 (2022) https://doi.org/10.1016/j.jeconom.2021.02.007
Misspecified diffusion models with high-frequency observations and an application to neural networks
Teppei Ogihara Stochastic Processes and their Applications 142 245 (2021) https://doi.org/10.1016/j.spa.2021.08.007
Bayesian inference on volatility in the presence of infinite jump activity and microstructure noise
Qi Wang, José E. Figueroa-López and Todd A. Kuffner Electronic Journal of Statistics 15 (1) (2021) https://doi.org/10.1214/20-EJS1794
Adaptive estimation for degenerate diffusion processes
Arnaud Gloter and Nakahiro Yoshida Electronic Journal of Statistics 15 (1) (2021) https://doi.org/10.1214/20-EJS1777
Hybrid estimation for ergodic diffusion processes based on noisy discrete observations
Yusuke Kaino, Shogo H. Nakakita and Masayuki Uchida Statistical Inference for Stochastic Processes 23 (1) 171 (2020) https://doi.org/10.1007/s11203-019-09203-2
Nonparametric estimation of volatility function in the jump-diffusion model with noisy data
Xu-Guo Ye, Yan-Yong Zhao and Kong-Sheng Zhang Journal of Nonparametric Statistics 32 (3) 587 (2020) https://doi.org/10.1080/10485252.2020.1759599
Dependent microstructure noise and integrated volatility estimation from high-frequency data
Z. Merrick Li, Roger J.A. Laeven and Michel H. Vellekoop Journal of Econometrics 215 (2) 536 (2020) https://doi.org/10.1016/j.jeconom.2019.10.004
Adaptive test for ergodic diffusions plus noise
Shogo H. Nakakita and Masayuki Uchida Journal of Statistical Planning and Inference 203 131 (2019) https://doi.org/10.1016/j.jspi.2019.03.006
Inference for ergodic diffusions plus noise
Shogo H. Nakakita and Masayuki Uchida Scandinavian Journal of Statistics 46 (2) 470 (2019) https://doi.org/10.1111/sjos.12360
Separating Information Maximum Likelihood Method for High-Frequency Financial Data
Naoto Kunitomo, Seisho Sato and Daisuke Kurisu SpringerBriefs in Statistics, Separating Information Maximum Likelihood Method for High-Frequency Financial Data 17 (2018) https://doi.org/10.1007/978-4-431-55930-6_3
Efficient estimation of stable Lévy process with symmetric jumps
Alexandre Brouste and Hiroki Masuda Statistical Inference for Stochastic Processes 21 (2) 289 (2018) https://doi.org/10.1007/s11203-018-9181-0
Power Variations and Testing for Co‐Jumps: The Small Noise Approach
Daisuke Kurisu Scandinavian Journal of Statistics 45 (3) 482 (2018) https://doi.org/10.1111/sjos.12309
On the inference about the spectral distribution of high-dimensional covariance matrix based on high-frequency noisy observations
Ningning Xia and Xinghua Zheng The Annals of Statistics 46 (2) (2018) https://doi.org/10.1214/17-AOS1558
Local asymptotic normality property for fractional Gaussian noise under high-frequency observations
Alexandre Brouste and Masaaki Fukasawa The Annals of Statistics 46 (5) (2018) https://doi.org/10.1214/17-AOS1611
Parametric inference for nonsynchronously observed diffusion processes in the presence of market microstructure noise
Teppei Ogihara Bernoulli 24 (4B) (2018) https://doi.org/10.3150/17-BEJ962
Parameter identification for a stochastic logistic growth model with extinction
Fabien Campillo, Marc Joannides and Irène Larramendy-Valverde Communications in Statistics - Simulation and Computation 47 (3) 721 (2018) https://doi.org/10.1080/03610918.2017.1291960
Separating Information Maximum Likelihood Method for High-Frequency Financial Data
Naoto Kunitomo, Seisho Sato and Daisuke Kurisu SpringerBriefs in Statistics, Separating Information Maximum Likelihood Method for High-Frequency Financial Data 1 (2018) https://doi.org/10.1007/978-4-431-55930-6_1
A unified approach to volatility estimation in the presence of both rounding and random market microstructure noise
Yingying Li, Zhiyuan Zhang and Yichu Li Journal of Econometrics 203 (2) 187 (2018) https://doi.org/10.1016/j.jeconom.2017.11.006
Inference from high-frequency data: A subsampling approach
K. Christensen, M. Podolskij, N. Thamrongrat and B. Veliyev Journal of Econometrics 197 (2) 245 (2017) https://doi.org/10.1016/j.jeconom.2016.07.010
Continuous Time Analysis of Fleeting Discrete Price Moves
Neil Shephard and Justin J. Yang Journal of the American Statistical Association 112 (519) 1090 (2017) https://doi.org/10.1080/01621459.2016.1192544
Edgeworth expansion for the pre-averaging estimator
Mark Podolskij, Bezirgen Veliyev and Nakahiro Yoshida Stochastic Processes and their Applications 127 (11) 3558 (2017) https://doi.org/10.1016/j.spa.2017.03.001
Econometric analysis of multivariate realised QML: Estimation of the covariation of equity prices under asynchronous trading
Neil Shephard and Dacheng Xiu Journal of Econometrics 201 (1) 19 (2017) https://doi.org/10.1016/j.jeconom.2017.04.003
ESTIMATING THE QUADRATIC VARIATION SPECTRUM OF NOISY ASSET PRICES USING GENERALIZED FLAT-TOP REALIZED KERNELS
Rasmus Tangsgaard Varneskov Econometric Theory 33 (6) 1457 (2017) https://doi.org/10.1017/S0266466616000475
On the Asymptotic Structure of Brownian Motions with a Small Lead-Lag Effect
Yuta Koike JOURNAL OF THE JAPAN STATISTICAL SOCIETY 47 (2) 75 (2017) https://doi.org/10.14490/jjss.47.75
Trading Noise and Default Risk
Qiqi Zou SSRN Electronic Journal (2016) https://doi.org/10.2139/ssrn.2786047
Between data cleaning and inference: Pre-averaging and robust estimators of the efficient price
Per A. Mykland and Lan Zhang Journal of Econometrics 194 (2) 242 (2016) https://doi.org/10.1016/j.jeconom.2016.05.005
Between Data Cleaning and Inference: Pre-Averaging and Robust Estimators of the Efficient Price
Per A. Mykland and Lan Zhang SSRN Electronic Journal (2016) https://doi.org/10.2139/ssrn.2754318
On the Inference About the Spectral Distribution of High-Dimensional Covariance Matrix Based on High-Frequency Noisy Observations
Ningning Xia and Xinghua Zheng SSRN Electronic Journal (2016) https://doi.org/10.2139/ssrn.2764654
Efficient estimation of integrated volatility incorporating trading information
Yingying Li, Shangyu Xie and Xinghua Zheng Journal of Econometrics 195 (1) 33 (2016) https://doi.org/10.1016/j.jeconom.2016.05.017
Estimating functions for noisy observations of ergodic diffusions
Benjamin Favetto Statistical Inference for Stochastic Processes 19 (1) 1 (2016) https://doi.org/10.1007/s11203-015-9121-1
Modeling and Stochastic Learning for Forecasting in High Dimensions
Till Sabel, Johannes Schmidt-Hieber and Axel Munk Lecture Notes in Statistics, Modeling and Stochastic Learning for Forecasting in High Dimensions 217 213 (2015) https://doi.org/10.1007/978-3-319-18732-7_12
Difference based estimators and infill statistics
José R. León and Carenne Ludeña Statistical Inference for Stochastic Processes 18 (1) 1 (2015) https://doi.org/10.1007/s11203-014-9103-8
Jian Zou, Yunbo An and Hong Yan 2437 (2015) https://doi.org/10.1109/BigData.2015.7364038
Microstructure noise in the continuous case: Approximate efficiency of the adaptive pre-averaging method
Jean Jacod and Per A. Mykland Stochastic Processes and their Applications 125 (8) 2910 (2015) https://doi.org/10.1016/j.spa.2015.02.005
Parameter estimation by contrast minimization for noisy observations of a diffusion process
Benjamin Favetto Statistics 48 (6) 1344 (2014) https://doi.org/10.1080/02331888.2013.828058
Statistics and Related Topics in Single-Molecule Biophysics
Hong Qian and S.C. Kou Annual Review of Statistics and Its Application 1 (1) 465 (2014) https://doi.org/10.1146/annurev-statistics-022513-115535
Asymptotically efficient estimation of a scale parameter in Gaussian time series and closed-form expressions for the Fisher information
Till Sabel and Johannes Schmidt-Hieber Bernoulli 20 (2) (2014) https://doi.org/10.3150/12-BEJ505
Volatility analysis in high‐frequency financial data
Yazhen Wang and Jian Zou WIREs Computational Statistics 6 (6) 393 (2014) https://doi.org/10.1002/wics.1330
Fact or friction: Jumps at ultra high frequency
Kim Christensen, Roel C.A. Oomen and Mark Podolskij Journal of Financial Economics 114 (3) 576 (2014) https://doi.org/10.1016/j.jfineco.2014.07.007
Modelling microstructure noise with mutually exciting point processes
E. Bacry, S. Delattre, M. Hoffmann and J. F. Muzy Quantitative Finance 13 (1) 65 (2013) https://doi.org/10.1080/14697688.2011.647054
Inference for Diffusion Processes
Christiane Fuchs Inference for Diffusion Processes 133 (2013) https://doi.org/10.1007/978-3-642-25969-2_6
On covariation estimation for multivariate continuous Itô semimartingales with noise in non-synchronous observation schemes
Kim Christensen, Mark Podolskij and Mathias Vetter Journal of Multivariate Analysis 120 59 (2013) https://doi.org/10.1016/j.jmva.2013.05.002
Optimal sparse volatility matrix estimation for high-dimensional Itô processes with measurement errors
Minjing Tao, Yazhen Wang and Harrison H. Zhou The Annals of Statistics 41 (4) (2013) https://doi.org/10.1214/13-AOS1128
Efficient Estimation of Integrated Volatility Incorporating Trading Information
Yingying Li, Shangyu Xie and Xinghua Zheng SSRN Electronic Journal (2013) https://doi.org/10.2139/ssrn.2373489
Separating Information Maximum Likelihood estimation of the integrated volatility and covariance with micro-market noise
Naoto Kunitomo and Seisho Sato The North American Journal of Economics and Finance 26 282 (2013) https://doi.org/10.1016/j.najef.2013.02.006
Preaveraging-Based Estimation of Quadratic Variation in the Presence of Noise and Jumps: Theory, Implementation, and Empirical Evidence
Nikolaus Hautsch and Mark Podolskij Journal of Business & Economic Statistics 31 (2) 165 (2013) https://doi.org/10.1080/07350015.2012.754313
Adaptive wavelet estimation of the diffusion coefficient under additive error measurements
M. Hoffmann, A. Munk and J. Schmidt-Hieber Annales de l'Institut Henri Poincaré, Probabilités et Statistiques 48 (4) (2012) https://doi.org/10.1214/11-AIHP472
Statistical Methods for Stochastic Differential Equations
Per Mykland and Lan Zhang C&H/CRC Monographs on Statistics & Applied Probability, Statistical Methods for Stochastic Differential Equations 20122069 109 (2012) https://doi.org/10.1201/b12126-3
Model checks for the volatility under microstructure noise
Mathias Vetter and Holger Dette Bernoulli 18 (4) (2012) https://doi.org/10.3150/11-BEJ384
Non-parametric estimation of the diffusion coefficient from noisy data
Emeline Schmisser Statistical Inference for Stochastic Processes 15 (3) 193 (2012) https://doi.org/10.1007/s11203-012-9072-8
Econometric Analysis of Multivariate Realised QML: Efficient Positive Semi-Definite Estimators of the Covariation of Equity Prices
Neil Shephard and Dacheng Xiu SSRN Electronic Journal (2012) https://doi.org/10.2139/ssrn.2045571
VOLATILITY AND COVARIATION ESTIMATION WHEN MICROSTRUCTURE NOISE AND TRADING TIMES ARE ENDOGENOUS
Christian Yann Robert and Mathieu Rosenbaum Mathematical Finance 22 (1) 133 (2012) https://doi.org/10.1111/j.1467-9965.2010.00454.x
Integrated variance forecasting: Model based vs. reduced form
Natalia Sizova Journal of Econometrics 162 (2) 294 (2011) https://doi.org/10.1016/j.jeconom.2011.02.004
Asymptotic equivalence for inference on the volatility from noisy observations
Markus Reiß The Annals of Statistics 39 (2) (2011) https://doi.org/10.1214/10-AOS855
Non-parametric drift estimation for diffusions from noisy data
Emeline Schmisser Statistics & Decisions 28 (2) 119 (2011) https://doi.org/10.1524/stnd.2011.1063
The SIML estimation of realized volatility of the Nikkei-225 Futures and hedging coefficient with micro-market noise
Naoto Kunitomo and Seisho Sato Mathematics and Computers in Simulation 81 (7) 1272 (2011) https://doi.org/10.1016/j.matcom.2010.08.003
On Covariation Estimation for Multivariate Continuous Itô Semimartingales with Noise in Non-Synchronous Observation Schemes
Kim Christensen, Mark Podolskij and Mathias Vetter SSRN Electronic Journal (2011) https://doi.org/10.2139/ssrn.2050642
Nonparametric Estimation of the Volatility Under Microstructure Noise: Wavelet Adaptation
Marc Hoffmann, Axel Munk and Johannes Schmidt-Hieber SSRN Electronic Journal (2010) https://doi.org/10.2139/ssrn.1661906
Handbook of Financial Econometrics: Applications
Jean Jacod Handbook of Financial Econometrics: Applications 197 (2010) https://doi.org/10.1016/B978-0-444-53548-1.50006-4
Nonparametric estimation of the volatility function in a high-frequency model corrupted by noise
Axel Munk and Johannes Schmidt-Hieber Electronic Journal of Statistics 4 (none) (2010) https://doi.org/10.1214/10-EJS568
Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data
Kim Christensen, Silja Kinnebrock and Mark Podolskij Journal of Econometrics 159 (1) 116 (2010) https://doi.org/10.1016/j.jeconom.2010.05.001
Realised quantile-based estimation of the integrated variance
Kim Christensen, Roel Oomen and Mark Podolskij Journal of Econometrics 159 (1) 74 (2010) https://doi.org/10.1016/j.jeconom.2010.04.008
A Short Overview on Limit Theorems and Microstructure Noise Modeling for (Ultra) High Frequency Data
Joachim Yaakov Nahmani SSRN Electronic Journal (2010) https://doi.org/10.2139/ssrn.2087910
Limit theorems for moving averages of discretized processes plus noise
Jean Jacod, Mark Podolskij and Mathias Vetter The Annals of Statistics 38 (3) (2010) https://doi.org/10.1214/09-AOS756
Integrated Variance Forecasting: Model-Based vs. Reduced-Form
Natalia Sizova SSRN Electronic Journal (2009) https://doi.org/10.2139/ssrn.1574418
Bipower-type estimation in a noisy diffusion setting
Mark Podolskij and Mathias Vetter Stochastic Processes and their Applications 119 (9) 2803 (2009) https://doi.org/10.1016/j.spa.2009.02.006
Estimation of volatility functionals in the simultaneous presence of microstructure noise and jumps
Mark Podolskij and Mathias Vetter Bernoulli 15 (3) (2009) https://doi.org/10.3150/08-BEJ167
Microstructure noise in the continuous case: The pre-averaging approach
Jean Jacod, Yingying Li, Per A. Mykland, Mark Podolskij and Mathias Vetter Stochastic Processes and their Applications 119 (7) 2249 (2009) https://doi.org/10.1016/j.spa.2008.11.004
Bias-correcting the realized range-based variance in the presence of market microstructure noise
Kim Christensen, Mark Podolskij and Mathias Vetter Finance and Stochastics 13 (2) 239 (2009) https://doi.org/10.1007/s00780-009-0089-9
Assessing Market Microstructure Effects via Realized Volatility Measures with an Application to the Dow Jones Industrial Average Stocks
Basel Awartani, Valentina Corradi and Walter Distaso Journal of Business & Economic Statistics 27 (2) 251 (2009) https://doi.org/10.1198/jbes.2009.0018
Microstructure Noise, Realized Variance, and Optimal Sampling
F. M. BANDI and J. R. RUSSELL Review of Economic Studies 75 (2) 339 (2008) https://doi.org/10.1111/j.1467-937X.2008.00474.x
Limit Theorems for Moving Averages of Discretized Processes Plus Noise
Jean Jacod, Mark Podolskij and Mathias Vetter SSRN Electronic Journal (2008) https://doi.org/10.2139/ssrn.1309568
Bias-Correcting the Realized Range-Based Variance in the Presence of Market Microstructure Noise
Kim Christensen, Mark Podolskij and Mathias Vetter SSRN Electronic Journal (2008) https://doi.org/10.2139/ssrn.935419
Bipower-Type Estimation in a Noisy Diffusion Setting
Mark Podolskij and Mathias Vetter SSRN Electronic Journal (2008) https://doi.org/10.2139/ssrn.1148161
An Econometric Analysis of Modulated Realised Covariance, Regression and Correlation in Noisy Diffusion Models
Silja Kinnebrock and Mark Podolskij SSRN Electronic Journal (2008) https://doi.org/10.2139/ssrn.1148159
Designing Realised Kernels to Measure the Ex-Post Variation of Equity Prices in the Presence of Noise
Ole E. Barndorff-Nielsen, Peter Reinhard Hansen, Asger Lunde and Neil Shephard SSRN Electronic Journal (2008) https://doi.org/10.2139/ssrn.620203
Parametric inference for mixed models defined by stochastic differential equations
Sophie Donnet and Adeline Samson ESAIM: Probability and Statistics 12 196 (2008) https://doi.org/10.1051/ps:2007045
Microstructure Noise in the Continuous Case: The Pre-Averaging Approach - JLMPV-9
Jean Jacod, Yingying Li, Per A. Mykland, Mark Podolskij and Mathias Vetter SSRN Electronic Journal (2007) https://doi.org/10.2139/ssrn.1150685
Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps
Mark Podolskij, Mathias Vetter and Margit Sommer SSRN Electronic Journal (2007) https://doi.org/10.2139/ssrn.950344
LIMIT THEOREMS FOR BIPOWER VARIATION IN FINANCIAL ECONOMETRICS
Ole E. Barndorff-Nielsen, Svend Erik Graversen, Jean Jacod and Neil Shephard Econometric Theory 22 (04) (2006) https://doi.org/10.1017/S0266466606060324
Variation, Jumps, Market Frictions and High Frequency Data in Financial Econometrics
Ole E. Barndorff-Nielsen and Neil Shephard SSRN Electronic Journal (2005) https://doi.org/10.2139/ssrn.751984
Diffusions with measurement errors. I. Local Asymptotic Normality
Arnaud Gloter and Jean Jacod ESAIM: Probability and Statistics 5 225 (2001) https://doi.org/10.1051/ps:2001110