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Dacheng Xiu

Personal Details

First Name:Dacheng
Middle Name:
Last Name:Xiu
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RePEc Short-ID:pxi68
http://faculty.chicagobooth.edu/dacheng.xiu/

Affiliation

Booth School of Business
University of Chicago

Chicago, Illinois (United States)
http://www.chicagobooth.edu/

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:1101 East 58th Street, Chicago, Illinois 60637
RePEc:edi:sbuchus (more details at EDIRC)

Research output

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Jump to: Working papers Articles

Working papers

  1. Neil Shephard & Dacheng Xiu, 2012. "Econometric analysis of multivariate realised QML: efficient positive semi-definite estimators of the covariation of equity prices," Economics Series Working Papers 604, University of Oxford, Department of Economics.

Articles

  1. Xiu, Dacheng, 2010. "Quasi-maximum likelihood estimation of volatility with high frequency data," Journal of Econometrics, Elsevier, vol. 159(1), pages 235-250, November.
  2. Aït-Sahalia, Yacine & Fan, Jianqing & Xiu, Dacheng, 2010. "High-Frequency Covariance Estimates With Noisy and Asynchronous Financial Data," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1504-1517.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Neil Shephard & Dacheng Xiu, 2012. "Econometric analysis of multivariate realised QML: efficient positive semi-definite estimators of the covariation of equity prices," Economics Series Working Papers 604, University of Oxford, Department of Economics.

    Cited by:

    1. Yuta Koike, 2014. "An estimator for the cumulative co-volatility of asynchronously observed semimartingales with jumps," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 460-481, June.
    2. Veredas, David & Vander Elst, Harry, 2014. "Disentangled jump-robust realized covariances and correlations with non-synchronous prices," DES - Working Papers. Statistics and Econometrics. WS ws142416, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Stefano Peluso & Fulvio Corsi & Antonietta Mira, 2015. "A Bayesian High-Frequency Estimator of the Multivariate Covariance of Noisy and Asynchronous Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 13(3), pages 665-697.
    4. Kim, Donggyu & Wang, Yazhen & Zou, Jian, 2016. "Asymptotic theory for large volatility matrix estimation based on high-frequency financial data," Stochastic Processes and their Applications, Elsevier, vol. 126(11), pages 3527-3577.
    5. Harry Vander Elst & David Veredas, 2017. "Smoothing it Out: Empirical and Simulation Results for Disentangled Realized Covariances," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 15(1), pages 106-138.

Articles

  1. Xiu, Dacheng, 2010. "Quasi-maximum likelihood estimation of volatility with high frequency data," Journal of Econometrics, Elsevier, vol. 159(1), pages 235-250, November.

    Cited by:

    1. Ulrich Hounyo & Sílvia Goncalves & Nour Meddahi, 2013. "Bootstrapping pre-averaged realized volatility under market microstructure noise," CREATES Research Papers 2013-28, Department of Economics and Business Economics, Aarhus University.
    2. Chen, Richard Y. & Mykland, Per A., 2017. "Model-free approaches to discern non-stationary microstructure noise and time-varying liquidity in high-frequency data," Journal of Econometrics, Elsevier, vol. 200(1), pages 79-103.
    3. Hounyo, Ulrich, 2017. "Bootstrapping integrated covariance matrix estimators in noisy jump–diffusion models with non-synchronous trading," Journal of Econometrics, Elsevier, vol. 197(1), pages 130-152.
    4. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 0509. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
    5. Neil Shephard & Dacheng Xiu, 2012. "Econometric analysis of multivariate realised QML: efficient positive semi-definite estimators of the covariation of equity prices," Economics Series Working Papers 604, University of Oxford, Department of Economics.
    6. Norman R. Swanson & Valentina Corradi & Walter Distaso, 2011. "Predictive Inference for Integrated Volatility," Departmental Working Papers 201109, Rutgers University, Department of Economics.
    7. IKEDA Shin Suke, 2017. "Illiquidity in the Japan Electric Power Exchange," Discussion papers 17122, Research Institute of Economy, Trade and Industry (RIETI).
    8. Altmeyer, Randolf & Bibinger, Markus, 2015. "Functional stable limit theorems for quasi-efficient spectral covolatility estimators," Stochastic Processes and their Applications, Elsevier, vol. 125(12), pages 4556-4600.
    9. Markus Bibinger & Lars Winkelmann, 2013. "Econometrics of co-jumps in high-frequency data with noise," SFB 649 Discussion Papers SFB649DP2013-021, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Dmitry Levando & Maxim Sakharov, 2018. "Natural Instability of Equilibrium Prices," Working Papers 2018:01, Department of Economics, University of Venice "Ca' Foscari".
    11. Richard Y. Chen & Per A. Mykland, 2015. "Model-Free Approaches to Discern Non-Stationary Microstructure Noise and Time-Varying Liquidity in High-Frequency Data," Papers 1512.06159, arXiv.org, revised Jan 2017.
    12. Seifoddini , Jalal & Rahnamay Roodposhti , Fraydoon & Nikoomaram , Hashem, 2015. "Parametric Estimates of High Frequency Market Microstructure Noise as an Unsystematic Risk," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 10(4), pages 29-50, October.
    13. Li, Yingying & Zhang, Zhiyuan & Zheng, Xinghua, 2013. "Volatility inference in the presence of both endogenous time and microstructure noise," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2696-2727.
    14. Li, Yingying & Zhang, Zhiyuan & Li, Yichu, 2018. "A unified approach to volatility estimation in the presence of both rounding and random market microstructure noise," Journal of Econometrics, Elsevier, vol. 203(2), pages 187-222.
    15. Fangfang Wang, 2016. "An Unbiased Measure of Integrated Volatility in the Frequency Domain," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(2), pages 147-164, March.
    16. Markus Bibinger & Per A. Mykland, 2016. "Inference for Multi-dimensional High-frequency Data with an Application to Conditional Independence Testing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1078-1102, December.
    17. Aït-Sahalia, Yacine & Fan, Jianqing & Li, Yingying, 2013. "The leverage effect puzzle: Disentangling sources of bias at high frequency," Journal of Financial Economics, Elsevier, vol. 109(1), pages 224-249.
    18. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    19. Markus Bibinger & Markus Reiß, 2011. "Spectral estimation of covolatility from noisy observations using local weights," SFB 649 Discussion Papers SFB649DP2011-086, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    20. Jacod, Jean & Mykland, Per A., 2015. "Microstructure noise in the continuous case: Approximate efficiency of the adaptive pre-averaging method," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2910-2936.
    21. Corsi, Fulvio & Peluso, Stefano & Audrino, Francesco, 2012. "Missing in Asynchronicity: A Kalman-EM Approach for Multivariate Realized Covariance Estimation," Economics Working Paper Series 1202, University of St. Gallen, School of Economics and Political Science.
    22. Bibinger, Markus & Winkelmann, Lars, 2015. "Econometrics of co-jumps in high-frequency data with noise," Journal of Econometrics, Elsevier, vol. 184(2), pages 361-378.
    23. Yoann Potiron & Per Mykland, 2016. "Local Parametric Estimation in High Frequency Data," Papers 1603.05700, arXiv.org, revised Mar 2017.
    24. Simon Clinet & Yoann Potiron, 2016. "Statistical inference for the doubly stochastic self-exciting process," Papers 1607.05831, arXiv.org, revised Jun 2017.
    25. Markus Bibinger & Per A. Mykland, 2013. "Inference for Multi-Dimensional High-Frequency Data: Equivalence of Methods, Central Limit Theorems, and an Application to Conditional Independence Testing," SFB 649 Discussion Papers SFB649DP2013-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    26. Yacine Aït-Sahalia & Jean Jacod, 2010. "Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data," NBER Working Papers 15808, National Bureau of Economic Research, Inc.
    27. Liu, Cheng & Tang, Cheng Yong, 2014. "A quasi-maximum likelihood approach for integrated covariance matrix estimation with high frequency data," Journal of Econometrics, Elsevier, vol. 180(2), pages 217-232.
    28. Donggyu Kim, 2016. "Statistical Inference for Unified Garch–Itô Models with High-Frequency Financial Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(4), pages 513-532, July.
    29. Aït-Sahalia, Yacine & Jacod, Jean & Li, Jia, 2012. "Testing for jumps in noisy high frequency data," Journal of Econometrics, Elsevier, vol. 168(2), pages 207-222.
    30. Simon Clinet & Yoann Potiron, 2017. "Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book," Papers 1709.02502, arXiv.org, revised Jun 2018.
    31. Yuta Koike, 2017. "Time endogeneity and an optimal weight function in pre-averaging covariance estimation," Statistical Inference for Stochastic Processes, Springer, vol. 20(1), pages 15-56, April.
    32. Zhi Liu, 2017. "Jump-robust estimation of volatility with simultaneous presence of microstructure noise and multiple observations," Finance and Stochastics, Springer, vol. 21(2), pages 427-469, April.
    33. Simon Clinet & Yoann Potiron, 2017. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Papers 1701.01185, arXiv.org, revised Jun 2018.
    34. Simon Clinet & Yoann Potiron, 2017. "Estimation for high-frequency data under parametric market microstructure noise," Papers 1712.01479, arXiv.org.
    35. Aït-Sahalia, Yacine & Xiu, Dacheng, 2016. "Increased correlation among asset classes: Are volatility or jumps to blame, or both?," Journal of Econometrics, Elsevier, vol. 194(2), pages 205-219.
    36. Zu, Yang & Peter Boswijk, H., 2014. "Estimating spot volatility with high-frequency financial data," Journal of Econometrics, Elsevier, vol. 181(2), pages 117-135.
    37. Liang-Ching Lin & Meihui Guo, 2016. "Optimal restricted quadratic estimator of integrated volatility," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(3), pages 673-703, June.
    38. Kim, Donggyu & Wang, Yazhen & Zou, Jian, 2016. "Asymptotic theory for large volatility matrix estimation based on high-frequency financial data," Stochastic Processes and their Applications, Elsevier, vol. 126(11), pages 3527-3577.
    39. Shephard, Neil & Xiu, Dacheng, 2017. "Econometric analysis of multivariate realised QML: Estimation of the covariation of equity prices under asynchronous trading," Journal of Econometrics, Elsevier, vol. 201(1), pages 19-42.
    40. Markus Bibinger & Markus Reiß, 2014. "Spectral Estimation of Covolatility from Noisy Observations Using Local Weights," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(1), pages 23-50, March.
    41. Chaker, Selma, 2017. "On high frequency estimation of the frictionless price: The use of observed liquidity variables," Journal of Econometrics, Elsevier, vol. 201(1), pages 127-143.
    42. Ulrich Hounyo, 2014. "Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading," CREATES Research Papers 2014-35, Department of Economics and Business Economics, Aarhus University.
    43. Xin Zhang & Donggyu Kim & Yazhen Wang, 2016. "Jump Variation Estimation with Noisy High Frequency Financial Data via Wavelets," Econometrics, MDPI, Open Access Journal, vol. 4(3), pages 1-26, August.
    44. Mykland, Per A. & Zhang, Lan, 2016. "Between data cleaning and inference: Pre-averaging and robust estimators of the efficient price," Journal of Econometrics, Elsevier, vol. 194(2), pages 242-262.
    45. Bibinger, Markus, 2012. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," Stochastic Processes and their Applications, Elsevier, vol. 122(6), pages 2411-2453.
    46. Randolf Altmeyer & Markus Bibinger, 2014. "Functional stable limit theorems for efficient spectral covolatility estimators," SFB 649 Discussion Papers SFB649DP2014-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    47. Liu, Zhi & Kong, Xin-Bing & Jing, Bing-Yi, 2018. "Estimating the integrated volatility using high-frequency data with zero durations," Journal of Econometrics, Elsevier, vol. 204(1), pages 18-32.
    48. Li, Yingying & Xie, Shangyu & Zheng, Xinghua, 2016. "Efficient estimation of integrated volatility incorporating trading information," Journal of Econometrics, Elsevier, vol. 195(1), pages 33-50.
    49. Kim, Donggyu & Wang, Yazhen, 2016. "Unified discrete-time and continuous-time models and statistical inferences for merged low-frequency and high-frequency financial data," Journal of Econometrics, Elsevier, vol. 194(2), pages 220-230.
    50. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2016. "Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach," CREATES Research Papers 2016-27, Department of Economics and Business Economics, Aarhus University.

  2. Aït-Sahalia, Yacine & Fan, Jianqing & Xiu, Dacheng, 2010. "High-Frequency Covariance Estimates With Noisy and Asynchronous Financial Data," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1504-1517.

    Cited by:

    1. Yoann Potiron & Per Mykland, 2015. "Estimation of integrated quadratic covariation with endogenous sampling times," Papers 1507.01033, arXiv.org, revised Nov 2016.
    2. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    3. Zhi Liu, 2016. "Estimating integrated co-volatility with partially miss-ordered high frequency data," Statistical Inference for Stochastic Processes, Springer, vol. 19(2), pages 175-197, July.
    4. Hounyo, Ulrich, 2017. "Bootstrapping integrated covariance matrix estimators in noisy jump–diffusion models with non-synchronous trading," Journal of Econometrics, Elsevier, vol. 197(1), pages 130-152.
    5. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
    6. Koike, Yuta, 2014. "Limit theorems for the pre-averaged Hayashi–Yoshida estimator with random sampling," Stochastic Processes and their Applications, Elsevier, vol. 124(8), pages 2699-2753.
    7. Larry G. Epstein & Yoram Halevy, 2017. "Ambiguous Correlation," Boston University - Department of Economics - Working Papers Series WP2017-006, Boston University - Department of Economics.
    8. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    9. Altmeyer, Randolf & Bibinger, Markus, 2015. "Functional stable limit theorems for quasi-efficient spectral covolatility estimators," Stochastic Processes and their Applications, Elsevier, vol. 125(12), pages 4556-4600.
    10. Aït-Sahalia, Yacine & Xiu, Dacheng, 2017. "Using principal component analysis to estimate a high dimensional factor model with high-frequency data," Journal of Econometrics, Elsevier, vol. 201(2), pages 384-399.
    11. Richard Y. Chen & Per A. Mykland, 2015. "Model-Free Approaches to Discern Non-Stationary Microstructure Noise and Time-Varying Liquidity in High-Frequency Data," Papers 1512.06159, arXiv.org, revised Jan 2017.
    12. Yin Liao & Heather M. Anderson, 2011. "Testing for co-jumps in high-frequency financial data: an approach based on first-high-low-last prices," Monash Econometrics and Business Statistics Working Papers 9/11, Monash University, Department of Econometrics and Business Statistics.
    13. Djellout, Hacène & Samoura, Yacouba, 2014. "Large and moderate deviations of realized covolatility," Statistics & Probability Letters, Elsevier, vol. 86(C), pages 30-37.
    14. Aït-Sahalia, Yacine & Fan, Jianqing & Li, Yingying, 2013. "The leverage effect puzzle: Disentangling sources of bias at high frequency," Journal of Financial Economics, Elsevier, vol. 109(1), pages 224-249.
    15. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    16. Corsi, Fulvio & Peluso, Stefano & Audrino, Francesco, 2012. "Missing in Asynchronicity: A Kalman-EM Approach for Multivariate Realized Covariance Estimation," Economics Working Paper Series 1202, University of St. Gallen, School of Economics and Political Science.
    17. Bibinger, Markus & Winkelmann, Lars, 2015. "Econometrics of co-jumps in high-frequency data with noise," Journal of Econometrics, Elsevier, vol. 184(2), pages 361-378.
    18. Yoann Potiron & Per Mykland, 2016. "Local Parametric Estimation in High Frequency Data," Papers 1603.05700, arXiv.org, revised Mar 2017.
    19. Liu, Cheng & Tang, Cheng Yong, 2014. "A quasi-maximum likelihood approach for integrated covariance matrix estimation with high frequency data," Journal of Econometrics, Elsevier, vol. 180(2), pages 217-232.
    20. Veredas, David & Vander Elst, Harry, 2014. "Disentangled jump-robust realized covariances and correlations with non-synchronous prices," DES - Working Papers. Statistics and Econometrics. WS ws142416, Universidad Carlos III de Madrid. Departamento de Estadística.
    21. Yuta Koike, 2017. "Time endogeneity and an optimal weight function in pre-averaging covariance estimation," Statistical Inference for Stochastic Processes, Springer, vol. 20(1), pages 15-56, April.
    22. Simon Clinet & Yoann Potiron, 2017. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Papers 1701.01185, arXiv.org, revised Jun 2018.
    23. Ikeda, Shin S., 2016. "A bias-corrected estimator of the covariation matrix of multiple security prices when both microstructure effects and sampling durations are persistent and endogenous," Journal of Econometrics, Elsevier, vol. 193(1), pages 203-214.
    24. Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org.
    25. Aït-Sahalia, Yacine & Xiu, Dacheng, 2016. "Increased correlation among asset classes: Are volatility or jumps to blame, or both?," Journal of Econometrics, Elsevier, vol. 194(2), pages 205-219.
    26. Park, Sujin & Hong, Seok Young & Linton, Oliver, 2016. "Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error," Journal of Econometrics, Elsevier, vol. 191(2), pages 325-347.
    27. Zhang, Zhengjun & Zhu, Bin, 2016. "Copula structured M4 processes with application to high-frequency financial data," Journal of Econometrics, Elsevier, vol. 194(2), pages 231-241.
    28. Michael Ho & Jack Xin, 2016. "Sparse Kalman Filtering Approaches to Covariance Estimation from High Frequency Data in the Presence of Jumps," Papers 1602.02185, arXiv.org, revised Apr 2016.
    29. Kim, Donggyu & Wang, Yazhen & Zou, Jian, 2016. "Asymptotic theory for large volatility matrix estimation based on high-frequency financial data," Stochastic Processes and their Applications, Elsevier, vol. 126(11), pages 3527-3577.
    30. Shephard, Neil & Xiu, Dacheng, 2017. "Econometric analysis of multivariate realised QML: Estimation of the covariation of equity prices under asynchronous trading," Journal of Econometrics, Elsevier, vol. 201(1), pages 19-42.
    31. Kim, Donggyu & Wang, Yazhen, 2016. "Sparse PCA-based on high-dimensional Itô processes with measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 172-189.
    32. Ulrich Hounyo, 2014. "Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading," CREATES Research Papers 2014-35, Department of Economics and Business Economics, Aarhus University.
    33. Djellout, Hacène & Guillin, Arnaud & Samoura, Yacouba, 2017. "Estimation of the realized (co-)volatility vector: Large deviations approach," Stochastic Processes and their Applications, Elsevier, vol. 127(9), pages 2926-2960.
    34. Ogihara, Teppei & Yoshida, Nakahiro, 2014. "Quasi-likelihood analysis for nonsynchronously observed diffusion processes," Stochastic Processes and their Applications, Elsevier, vol. 124(9), pages 2954-3008.
    35. Markus Bibinger & Markus Reiss & Nikolaus Hautsch & Peter Malec, 2014. "Estimating the Spot Covariation of Asset Prices – Statistical Theory and Empirical Evidence," SFB 649 Discussion Papers SFB649DP2014-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    36. Bibinger, Markus, 2012. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," Stochastic Processes and their Applications, Elsevier, vol. 122(6), pages 2411-2453.
    37. Randolf Altmeyer & Markus Bibinger, 2014. "Functional stable limit theorems for efficient spectral covolatility estimators," SFB 649 Discussion Papers SFB649DP2014-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    38. Liu, Zhi & Kong, Xin-Bing & Jing, Bing-Yi, 2018. "Estimating the integrated volatility using high-frequency data with zero durations," Journal of Econometrics, Elsevier, vol. 204(1), pages 18-32.
    39. Hacène Djellout & Arnaud Guillin & Yacouba Samoura, 2017. "Large Deviations Of The Realized (Co-)Volatility Vector," Post-Print hal-01082903, HAL.
    40. Haugom, Erik & Lien, Gudbrand & Veka, Steinar & Westgaard, Sjur, 2014. "Covariance estimation using high-frequency data: Sensitivities of estimation methods," Economic Modelling, Elsevier, vol. 43(C), pages 416-425.
    41. Hwang, Eunju & Shin, Dong Wan, 2018. "Two-stage stationary bootstrapping for bivariate average realized volatility matrix under market microstructure noise and asynchronicity," Journal of Econometrics, Elsevier, vol. 202(2), pages 178-195.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (1) 2012-05-02. Author is listed
  2. NEP-ETS: Econometric Time Series (1) 2012-05-02. Author is listed
  3. NEP-MST: Market Microstructure (1) 2012-05-02. Author is listed
  4. NEP-ORE: Operations Research (1) 2012-05-02. Author is listed

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