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Simon Clinet

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Personal Details

First Name:Simon
Middle Name:
Last Name:Clinet
Suffix:
RePEc Short-ID:pcl144
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http://user.keio.ac.jp/~clinet/

Affiliation

Faculty of Economics
Keio University

Tokyo, Japan
http://www.econ.keio.ac.jp/
RePEc:edi:fekeijp (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Simon Clinet & Yoann Potiron, 2017. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Papers 1701.01185, arXiv.org, revised Jun 2018.
  2. 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 Feb 2019.
  3. Simon Clinet & Yoann Potiron, 2017. "Estimation for high-frequency data under parametric market microstructure noise," Papers 1712.01479, arXiv.org, revised Sep 2020.
  4. Simon Clinet & Yoann Potiron, 2016. "Statistical inference for the doubly stochastic self-exciting process," Papers 1607.05831, arXiv.org, revised Jun 2017.

Articles

  1. Clinet, Simon & Yoshida, Nakahiro, 2017. "Statistical inference for ergodic point processes and application to Limit Order Book," Stochastic Processes and their Applications, Elsevier, vol. 127(6), pages 1800-1839.

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. Simon Clinet & Yoann Potiron, 2017. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Papers 1701.01185, arXiv.org, revised Jun 2018.

    Cited by:

    1. Clinet, Simon & Potiron, Yoann, 2019. "Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book," Journal of Econometrics, Elsevier, vol. 209(2), pages 289-337.
    2. Richard Y. Chen, 2018. "Inference for Volatility Functionals of Multivariate It\^o Semimartingales Observed with Jump and Noise," Papers 1810.04725, arXiv.org, revised Nov 2019.
    3. Simon Clinet & Yoann Potiron, 2017. "Estimation for high-frequency data under parametric market microstructure noise," Papers 1712.01479, arXiv.org, revised Sep 2020.
    4. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2017. "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. Li, Z. M. & Laeven, R. J. A. & Vellekoop, M. H., 2019. "Dependent Microstructure Noise and Integrated Volatility: Estimation from High-Frequency Data," Cambridge Working Papers in Economics 1952, Faculty of Economics, University of Cambridge.

  2. 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 Feb 2019.

    Cited by:

    1. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    2. Long, Yunshen & Yan, Jingzhou & Wu, Liang & Long, Xingchen, 2024. "Market price determination: Interpreting quote order imbalance under zero-profit equilibrium," Economic Modelling, Elsevier, vol. 134(C).
    3. Simon Clinet & Yoann Potiron, 2017. "Estimation for high-frequency data under parametric market microstructure noise," Papers 1712.01479, arXiv.org, revised Sep 2020.
    4. Markus Bibinger & Nikolaus Hautsch & Alexander Ristig, 2024. "Jump detection in high-frequency order prices," Papers 2403.00819, arXiv.org.
    5. Li, Z. M. & Laeven, R. J. A. & Vellekoop, M. H., 2019. "Dependent Microstructure Noise and Integrated Volatility: Estimation from High-Frequency Data," Cambridge Working Papers in Economics 1952, Faculty of Economics, University of Cambridge.
    6. Yinfen Tang & Tao Su & Zhiyuan Zhang, 2022. "Distribution-free specification test for volatility function based on high-frequency data with microstructure noise," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(8), pages 977-1022, November.
    7. Cui, Wenhao & Hu, Jie & Wang, Jiandong, 2024. "Nonparametric estimation for high-frequency data incorporating trading information," Journal of Econometrics, Elsevier, vol. 240(1).

  3. Simon Clinet & Yoann Potiron, 2017. "Estimation for high-frequency data under parametric market microstructure noise," Papers 1712.01479, arXiv.org, revised Sep 2020.

    Cited by:

    1. Carsten H. Chong & Viktor Todorov, 2023. "Asymptotic Expansions for High-Frequency Option Data," Papers 2304.12450, arXiv.org.
    2. Clinet, Simon & Potiron, Yoann, 2019. "Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book," Journal of Econometrics, Elsevier, vol. 209(2), pages 289-337.
    3. Yang, Xiye, 2020. "Time-invariant restrictions of volatility functionals: Efficient estimation and specification tests," Journal of Econometrics, Elsevier, vol. 215(2), pages 486-516.
    4. Carsten H. Chong & Viktor Todorov, 2023. "Volatility of Volatility and Leverage Effect from Options," Papers 2305.04137, arXiv.org, revised Jan 2024.
    5. Simon Clinet & Yoann Potiron, 2017. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Papers 1701.01185, arXiv.org, revised Jun 2018.
    6. Li, Yingying & Liu, Guangying & Zhang, Zhiyuan, 2022. "Volatility of volatility: Estimation and tests based on noisy high frequency data with jumps," Journal of Econometrics, Elsevier, vol. 229(2), pages 422-451.
    7. Li, Z. M. & Laeven, R. J. A. & Vellekoop, M. H., 2019. "Dependent Microstructure Noise and Integrated Volatility: Estimation from High-Frequency Data," Cambridge Working Papers in Economics 1952, Faculty of Economics, University of Cambridge.
    8. Cui, Wenhao & Hu, Jie & Wang, Jiandong, 2024. "Nonparametric estimation for high-frequency data incorporating trading information," Journal of Econometrics, Elsevier, vol. 240(1).
    9. Chong, Carsten H. & Todorov, Viktor, 2024. "Volatility of volatility and leverage effect from options," Journal of Econometrics, Elsevier, vol. 240(1).

  4. Simon Clinet & Yoann Potiron, 2016. "Statistical inference for the doubly stochastic self-exciting process," Papers 1607.05831, arXiv.org, revised Jun 2017.

    Cited by:

    1. Clinet, Simon & Potiron, Yoann, 2019. "Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book," Journal of Econometrics, Elsevier, vol. 209(2), pages 289-337.
    2. Simon Clinet, 2020. "Quasi-likelihood analysis for marked point processes and application to marked Hawkes processes," Papers 2001.11624, arXiv.org, revised Aug 2021.
    3. Simon Clinet & Yoann Potiron, 2017. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Papers 1701.01185, arXiv.org, revised Jun 2018.
    4. Simon Clinet & William T. M. Dunsmuir & Gareth W. Peters & Kylie-Anne Richards, 2021. "Asymptotic distribution of the score test for detecting marks in hawkes processes," Statistical Inference for Stochastic Processes, Springer, vol. 24(3), pages 635-668, October.
    5. Simon Clinet & William T. M. Dunsmuir & Gareth W. Peters & Kylie-Anne Richards, 2019. "Asymptotic Distribution of the Score Test for Detecting Marks in Hawkes Processes," Research Paper Series 404, Quantitative Finance Research Centre, University of Technology, Sydney.

Articles

  1. Clinet, Simon & Yoshida, Nakahiro, 2017. "Statistical inference for ergodic point processes and application to Limit Order Book," Stochastic Processes and their Applications, Elsevier, vol. 127(6), pages 1800-1839.

    Cited by:

    1. Masatoshi Goda, 2021. "Hawkes process and Edgeworth expansion with application to maximum likelihood estimator," Statistical Inference for Stochastic Processes, Springer, vol. 24(2), pages 277-325, July.
    2. Maxime Morariu-Patrichi & Mikko S. Pakkanen, 2018. "State-dependent Hawkes processes and their application to limit order book modelling," Papers 1809.08060, arXiv.org, revised Sep 2021.
    3. Rachele Foschi & Francesca Lilla & Cecilia Mancini, 2020. "Warnings about future jumps: properties of the exponential Hawkes model," Working Papers 13/2020, University of Verona, Department of Economics.
    4. Nakahiro Yoshida, 2022. "Quasi-likelihood analysis and its applications," Statistical Inference for Stochastic Processes, Springer, vol. 25(1), pages 43-60, April.
    5. Yoann Potiron & Per Mykland, 2016. "Local Parametric Estimation in High Frequency Data," Papers 1603.05700, arXiv.org, revised Aug 2018.
    6. Simon Clinet & Yoann Potiron, 2016. "Statistical inference for the doubly stochastic self-exciting process," Papers 1607.05831, arXiv.org, revised Jun 2017.
    7. Simon Clinet, 2020. "Quasi-likelihood analysis for marked point processes and application to marked Hawkes processes," Papers 2001.11624, arXiv.org, revised Aug 2021.
    8. Simon Clinet, 2022. "Quasi-likelihood analysis for marked point processes and application to marked Hawkes processes," Statistical Inference for Stochastic Processes, Springer, vol. 25(2), pages 189-225, July.
    9. Simon Clinet & William T. M. Dunsmuir & Gareth W. Peters & Kylie-Anne Richards, 2021. "Asymptotic distribution of the score test for detecting marks in hawkes processes," Statistical Inference for Stochastic Processes, Springer, vol. 24(3), pages 635-668, October.
    10. Simon Clinet & William T. M. Dunsmuir & Gareth W. Peters & Kylie-Anne Richards, 2019. "Asymptotic Distribution of the Score Test for Detecting Marks in Hawkes Processes," Research Paper Series 404, Quantitative Finance Research Centre, University of Technology, Sydney.
    11. Cavaliere, Giuseppe & Lu, Ye & Rahbek, Anders & Stærk-Østergaard, Jacob, 2023. "Bootstrap inference for Hawkes and general point processes," Journal of Econometrics, Elsevier, vol. 235(1), pages 133-165.
    12. Shogo H. Nakakita & Yusuke Kaino & Masayuki Uchida, 2021. "Quasi-likelihood analysis and Bayes-type estimators of an ergodic diffusion plus noise," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(1), pages 177-225, February.
    13. Mercuri, Lorenzo & Perchiazzo, Andrea & Rroji, Edit, 2024. "A Hawkes model with CARMA(p,q) intensity," Insurance: Mathematics and Economics, Elsevier, vol. 116(C), pages 1-26.
    14. Masatoshi Goda, 2023. "Sparse estimation for generalized exponential marked Hawkes process," Statistical Inference for Stochastic Processes, Springer, vol. 26(1), pages 139-169, April.
    15. Maxime Morariu-Patrichi & Mikko Pakkanen, 2018. "State-dependent Hawkes processes and their application to limit order book modelling," CREATES Research Papers 2018-26, Department of Economics and Business Economics, Aarhus University.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 4 papers 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 (4) 2016-07-23 2017-01-08 2017-09-17 2017-12-11. Author is listed
  2. NEP-MST: Market Microstructure (3) 2017-01-08 2017-09-17 2017-12-11. Author is listed
  3. NEP-ETS: Econometric Time Series (2) 2016-07-23 2017-01-08. Author is listed
  4. NEP-FMK: Financial Markets (1) 2017-12-11. Author is listed

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