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Yoann Potiron

Personal Details

First Name:Yoann
Middle Name:
Last Name:Potiron
Suffix:
RePEc Short-ID:ppo615
[This author has chosen not to make the email address public]
http://www.fbc.keio.ac.jp/~potiron/

Affiliation

Faculty of Business and Commerce
Keio University

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

Research output

as
Jump to: Working papers Articles

Working papers

  1. Yoann Potiron & O. Scaillet & Vladimir Volkov & Seunghyeon Yu, 2025. "High-Frequency Estimation of ITÔ Semimartingale Baseline for Hawkes Processes," Swiss Finance Institute Research Paper Series 25-13, Swiss Finance Institute.
  2. Simon Clinet & Yoann Potiron, 2019. "Cointegration in high frequency data," Papers 1905.07081, arXiv.org, revised Mar 2021.
  3. Antonin Bergeaud & Yoann Potiron & Juste Raimbault, 2018. "Classifying Patents Based on their Semantic Content," Working papers 685, Banque de France.
  4. Simon Clinet & Yoann Potiron, 2017. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Papers 1701.01185, arXiv.org, revised Jun 2018.
  5. 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.
  6. Simon Clinet & Yoann Potiron, 2017. "Estimation for high-frequency data under parametric market microstructure noise," Papers 1712.01479, arXiv.org, revised Sep 2020.
  7. Yoann Potiron & Per Mykland, 2016. "Local Parametric Estimation in High Frequency Data," Papers 1603.05700, arXiv.org, revised Aug 2018.
  8. Juste Raimbault & Antonin Bergeaud & Yoann Potiron, 2016. "Investigating Patterns of Technological Innovation," Post-Print halshs-01370528, HAL.
  9. Simon Clinet & Yoann Potiron, 2016. "Statistical inference for the doubly stochastic self-exciting process," Papers 1607.05831, arXiv.org, revised Jun 2017.
  10. Yoann Potiron & Per Mykland, 2015. "Estimation of integrated quadratic covariation with endogenous sampling times," Papers 1507.01033, arXiv.org, revised Nov 2016.

Articles

  1. Simon Clinet & Yoann Potiron, 2021. "Estimation for high-frequency data under parametric market microstructure noise," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 649-669, August.
  2. Simon Clinet & Yoann Potiron, 2021. "Disentangling Sources of High Frequency Market Microstructure Noise," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 18-39, January.
  3. Yoann Potiron & Per Mykland, 2020. "Local Parametric Estimation in High Frequency Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(3), pages 679-692, July.
  4. 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.
  5. Clinet, Simon & Potiron, Yoann, 2018. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Journal of Econometrics, Elsevier, vol. 206(1), pages 103-142.
  6. Antonin Bergeaud & Yoann Potiron & Juste Raimbault, 2017. "Classifying patents based on their semantic content," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-22, April.
  7. Potiron, Yoann & Mykland, Per A., 2017. "Estimation of integrated quadratic covariation with endogenous sampling times," Journal of Econometrics, Elsevier, vol. 197(1), pages 20-41.

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. Antonin Bergeaud & Yoann Potiron & Juste Raimbault, 2018. "Classifying Patents Based on their Semantic Content," Working papers 685, Banque de France.

    Cited by:

    1. Gątkowski, Mateusz & Dietl, Marek & Skrok, Lukasz & Whalen, Ryan & Rockett, Katharine, 2018. "Patent Thickets Identification," Economics Discussion Papers 22928, University of Essex, Department of Economics.
    2. A. Fronzetti Colladon & B. Guardabascio & F. Venturini, 2023. "A new mapping of technological interdependence," Papers 2308.00014, arXiv.org, revised Sep 2024.
    3. Philippe Aghion & Antonin Bergeaud & John van Reenen, 2023. "The Impact of Regulation on Innovation," Post-Print halshs-04330712, HAL.
    4. Juste Raimbault, 2019. "Exploration of an interdisciplinary scientific landscape," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 617-641, May.
    5. David Lenz & Peter Winker, 2018. "Measuring the Diffusion of Innovations with Paragraph Vector Topic Models," MAGKS Papers on Economics 201815, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    6. Arts, Sam & Hou, Jianan & Gomez, Juan Carlos, 2021. "Natural language processing to identify the creation and impact of new technologies in patent text: Code, data, and new measures," Research Policy, Elsevier, vol. 50(2).
    7. Gątkowski, Mateusz & Dietl, Marek & Skrok, Łukasz & Whalen, Ryan & Rockett, Katharine, 2020. "Semantically-based patent thicket identification," Research Policy, Elsevier, vol. 49(2).
    8. Antoine Peris & Evert Meijers & Maarten Ham, 2018. "The Evolution of the Systems of Cities Literature Since 1995: Schools of Thought and their Interaction," Networks and Spatial Economics, Springer, vol. 18(3), pages 533-554, September.
    9. Jonathan H. Ashtor, 2019. "Investigating Cohort Similarity as an Ex Ante Alternative to Patent Forward Citations," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 16(4), pages 848-880, December.
    10. Sarah Oh, 2020. "Radio “Fences” and Inventor Attention to Property Rights: Evidence from Wireless Patents," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 56(1), pages 37-72, February.
    11. Ananthan Nambiar & Tobias Rubel & James McCaull & Jon deVries & Mark Bedau, 2021. "Dropping diversity of products of large US firms: Models and measures," Papers 2110.08367, arXiv.org.
    12. Jeffrey P. Clemens & Parker Rogers, 2020. "Demand Shocks, Procurement Policies, and the Nature of Medical Innovation: Evidence from Wartime Prosthetic Device Patents," CESifo Working Paper Series 8781, CESifo.
    13. Sijie Feng, 2020. "The proximity of ideas: An analysis of patent text using machine learning," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-19, July.

  2. 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. 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. 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. "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.
    4. Simon Clinet & Yoann Potiron, 2017. "Estimation for high-frequency data under parametric market microstructure noise," Papers 1712.01479, arXiv.org, revised Sep 2020.
    5. 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.

  3. 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. 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.
    4. Simon Clinet & Yoann Potiron, 2017. "Estimation for high-frequency data under parametric market microstructure noise," Papers 1712.01479, arXiv.org, revised Sep 2020.
    5. Cui, Wenhao & Hu, Jie & Wang, Jiandong, 2024. "Nonparametric estimation for high-frequency data incorporating trading information," Journal of Econometrics, Elsevier, vol. 240(1).
    6. Markus Bibinger & Nikolaus Hautsch & Alexander Ristig, 2024. "Jump detection in high-frequency order prices," Papers 2403.00819, arXiv.org.
    7. 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.

  4. 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. 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. Yang, Xiye, 2020. "Time-invariant restrictions of volatility functionals: Efficient estimation and specification tests," Journal of Econometrics, Elsevier, vol. 215(2), pages 486-516.
    3. Carsten H. Chong & Viktor Todorov, 2023. "Volatility of Volatility and Leverage Effect from Options," Papers 2305.04137, arXiv.org, revised Jan 2024.
    4. 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.
    5. 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.
    6. Carsten H. Chong & Viktor Todorov, 2023. "Asymptotic Expansions for High-Frequency Option Data," Papers 2304.12450, arXiv.org.
    7. Cui, Wenhao & Hu, Jie & Wang, Jiandong, 2024. "Nonparametric estimation for high-frequency data incorporating trading information," Journal of Econometrics, Elsevier, vol. 240(1).
    8. Chong, Carsten H. & Todorov, Viktor, 2024. "Volatility of volatility and leverage effect from options," Journal of Econometrics, Elsevier, vol. 240(1).
    9. 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.

  5. Yoann Potiron & Per Mykland, 2016. "Local Parametric Estimation in High Frequency Data," Papers 1603.05700, arXiv.org, revised Aug 2018.

    Cited by:

    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. Yoann Potiron & Per Mykland, 2015. "Estimation of integrated quadratic covariation with endogenous sampling times," Papers 1507.01033, arXiv.org, revised Nov 2016.
    3. Simon Clinet & Yoann Potiron, 2016. "Statistical inference for the doubly stochastic self-exciting process," Papers 1607.05831, arXiv.org, revised Jun 2017.
    4. 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.
    5. Simon Clinet & Yoann Potiron, 2017. "Estimation for high-frequency data under parametric market microstructure noise," Papers 1712.01479, arXiv.org, revised Sep 2020.
    6. Casini, Alessandro & Perron, Pierre, 2024. "Prewhitened long-run variance estimation robust to nonstationarity," Journal of Econometrics, Elsevier, vol. 242(1).

  6. 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. 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 & 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.
    3. 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.
    4. 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.
    5. Simon Clinet, 2020. "Quasi-likelihood analysis for marked point processes and application to marked Hawkes processes," Papers 2001.11624, arXiv.org, revised Aug 2021.

  7. Yoann Potiron & Per Mykland, 2015. "Estimation of integrated quadratic covariation with endogenous sampling times," Papers 1507.01033, arXiv.org, revised Nov 2016.

    Cited by:

    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. Aleksey Kolokolov & Giulia Livieri & Davide Pirino, 2022. "Testing for Endogeneity of Irregular Sampling Schemes," CEIS Research Paper 547, Tor Vergata University, CEIS, revised 19 Dec 2022.
    3. Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
    4. Zhao, X. & Hong, S. Y. & Linton, O. B., 2024. "Jumps Versus Bursts: Dissection and Origins via a New Endogenous Thresholding Approach," Janeway Institute Working Papers 2423, Faculty of Economics, University of Cambridge.
    5. Simon Clinet & Yoann Potiron, 2017. "Estimation for high-frequency data under parametric market microstructure noise," Papers 1712.01479, arXiv.org, revised Sep 2020.
    6. Cui, Wenhao & Hu, Jie & Wang, Jiandong, 2024. "Nonparametric estimation for high-frequency data incorporating trading information," Journal of Econometrics, Elsevier, vol. 240(1).
    7. Hall, George & Rust, John, 2021. "Estimation of endogenously sampled time series: The case of commodity price speculation in the steel market," Journal of Econometrics, Elsevier, vol. 222(1), pages 219-243.

Articles

  1. Simon Clinet & Yoann Potiron, 2021. "Estimation for high-frequency data under parametric market microstructure noise," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 649-669, August.
    See citations under working paper version above.
  2. Simon Clinet & Yoann Potiron, 2021. "Disentangling Sources of High Frequency Market Microstructure Noise," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 18-39, January.

    Cited by:

    1. 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).
    2. Cui, Wenhao & Hu, Jie & Wang, Jiandong, 2024. "Nonparametric estimation for high-frequency data incorporating trading information," Journal of Econometrics, Elsevier, vol. 240(1).
    3. 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.

  3. Yoann Potiron & Per Mykland, 2020. "Local Parametric Estimation in High Frequency Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(3), pages 679-692, July.
    See citations under working paper version above.
  4. 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.
    See citations under working paper version above.
  5. Clinet, Simon & Potiron, Yoann, 2018. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Journal of Econometrics, Elsevier, vol. 206(1), pages 103-142.
    See citations under working paper version above.
  6. Antonin Bergeaud & Yoann Potiron & Juste Raimbault, 2017. "Classifying patents based on their semantic content," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-22, April.
    See citations under working paper version above.
  7. Potiron, Yoann & Mykland, Per A., 2017. "Estimation of integrated quadratic covariation with endogenous sampling times," Journal of Econometrics, Elsevier, vol. 197(1), pages 20-41.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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 8 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 (7) 2015-07-11 2016-04-04 2016-07-23 2017-01-08 2017-09-17 2017-12-11 2019-05-27. Author is listed
  2. NEP-MST: Market Microstructure (5) 2016-04-04 2017-01-08 2017-09-17 2017-12-11 2019-05-27. Author is listed
  3. NEP-ETS: Econometric Time Series (4) 2015-07-11 2016-07-23 2017-01-08 2019-05-27
  4. NEP-BIG: Big Data (1) 2018-08-13
  5. NEP-FMK: Financial Markets (1) 2017-12-11
  6. NEP-INO: Innovation (1) 2018-08-13
  7. NEP-IPR: Intellectual Property Rights (1) 2018-08-13

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