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High frequency market microstructure noise estimates and liquidity measures

Citations

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Cited by:

  1. Duffie, Darrell & Dworczak, Piotr, 2021. "Robust benchmark design," Journal of Financial Economics, Elsevier, vol. 142(2), pages 775-802.
  2. Ciamac C. Moallemi & Mehmet Sağlam, 2013. "OR Forum---The Cost of Latency in High-Frequency Trading," Operations Research, INFORMS, vol. 61(5), pages 1070-1086, October.
  3. Haochen Li & Yi Cao & Maria Polukarov & Carmine Ventre, 2023. "An Empirical Analysis on Financial Markets: Insights from the Application of Statistical Physics," Papers 2308.14235, arXiv.org, revised Jun 2024.
  4. Masahiro Watanabe, 2003. "A Model of Stochastic Liquidity," Yale School of Management Working Papers ysm385, Yale School of Management.
  5. Winkelmann, Lars & Yao, Wenying, 2020. "Cojump anchoring," Discussion Papers 2020/17, Free University Berlin, School of Business & Economics.
  6. Kim, Donggyu & Song, Xinyu & Wang, Yazhen, 2022. "Unified discrete-time factor stochastic volatility and continuous-time Itô models for combining inference based on low-frequency and high-frequency," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
  7. Mathias Pohl & Alexander Ristig & Walter Schachermayer & Ludovic Tangpi, 2018. "Theoretical and empirical analysis of trading activity," Papers 1803.04892, arXiv.org, revised Oct 2018.
  8. 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.
  9. Amaya, Diego & Christoffersen, Peter & Jacobs, Kris & Vasquez, Aurelio, 2015. "Does realized skewness predict the cross-section of equity returns?," Journal of Financial Economics, Elsevier, vol. 118(1), pages 135-167.
  10. Großmaß Lidan, 2014. "Liquidity and the Value at Risk," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 234(5), pages 572-602, October.
  11. Xu, Zheng, 2013. "Estimation of parametric homogeneous stochastic volatility pricing formulae based on option data," Economics Letters, Elsevier, vol. 120(3), pages 369-373.
  12. Xiu, Dacheng, 2010. "Quasi-maximum likelihood estimation of volatility with high frequency data," Journal of Econometrics, Elsevier, vol. 159(1), pages 235-250, November.
  13. Sha Wang & Jean-Philippe Vergne, 2017. "Buzz Factor or Innovation Potential: What Explains Cryptocurrencies’ Returns?," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-17, January.
  14. Peter Christoffersen & Bruno Feunou & Yoontae Jeon & Chayawat Ornthanalai, 2016. "Time-Varying Crash Risk: The Role of Stock Market Liquidity," Staff Working Papers 16-35, Bank of Canada.
  15. Ranjan R. Chakravarty & Sudhanshu Pani, 2021. "A Data Paradigm to Operationalise Expanded Filtration: Realized Volatilities and Kernels from Non-Synchronous NASDAQ Quotes and Trades," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 617-652, December.
  16. Oliver Linton & Soheil Mahmoodzadeh, 2018. "Implications of High-Frequency Trading for Security Markets," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 237-259, August.
  17. 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.
  18. Lars Winkelmann & Wenying Yao, 2024. "Tests for Jumps in Yield Spreads," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 946-957, July.
  19. Luo, Jiawen & Klein, Tony & Walther, Thomas & Ji, Qiang, 2021. "Forecasting Realized Volatility of Crude Oil Futures Prices based on Machine Learning," QBS Working Paper Series 2021/04, Queen's University Belfast, Queen's Business School.
  20. 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.
  21. Lee Jihyun & Kim Tong S & Lee Hoe Kyung, 2010. "Return-Volatility Relationship in High Frequency Data: Multiscale Horizon Dependency," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(1), pages 1-43, December.
  22. Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015. "Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes," Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
  23. Song, Xinyu & Kim, Donggyu & Yuan, Huiling & Cui, Xiangyu & Lu, Zhiping & Zhou, Yong & Wang, Yazhen, 2021. "Volatility analysis with realized GARCH-Itô models," Journal of Econometrics, Elsevier, vol. 222(1), pages 393-410.
  24. 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.
  25. Szymon Stereńczak, 2021. "Minimum tick size reduction and stock liquidity: lessons from the Warsaw Stock Exchange," Bank i Kredyt, Narodowy Bank Polski, vol. 52(6), pages 545-576.
  26. Liu, Qiang & Liu, Yiqi & Liu, Zhi & Wang, Li, 2018. "Estimation of spot volatility with superposed noisy data," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 62-79.
  27. Donggyu Kim & Xinyu Song & Yazhen Wang, 2020. "Unified Discrete-Time Factor Stochastic Volatility and Continuous-Time Ito Models for Combining Inference Based on Low-Frequency and High-Frequency," Papers 2006.12039, arXiv.org.
  28. Chang, Jinyuan & Hu, Qiao & Liu, Cheng & Tang, Cheng Yong, 2024. "Optimal covariance matrix estimation for high-dimensional noise in high-frequency data," Journal of Econometrics, Elsevier, vol. 239(2).
  29. Naimoli, Antonio & Gerlach, Richard & Storti, Giuseppe, 2022. "Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators," Economic Modelling, Elsevier, vol. 107(C).
  30. Malgorzata Doman, 2010. "Liquidity and Market Microstructure Noise: Evidence from the Pekao Data," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 10, pages 5-14.
  31. Xinyu Song, 2019. "Large Volatility Matrix Prediction with High-Frequency Data," Papers 1907.01196, arXiv.org, revised Sep 2019.
  32. Magdalena Osinska & Andrzej Dobrzynski & Yochanan Shachmurove, 2016. "Performance Of American And Russian Joint Stock Companies On Financial Market. A Microstructure Perspective," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(4), pages 819-851, December.
  33. Seema REHMAN & Saqib SHARIF & Wali ULLAH, 2021. "Higher Realized Moments and Stock Return Predictability," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 48-70, December.
  34. Giorgio Mirone, 2018. "Cross-sectional noise reduction and more efficient estimation of Integrated Variance," CREATES Research Papers 2018-18, Department of Economics and Business Economics, Aarhus University.
  35. A. Saichev & D. Sornette, 2012. "A simple microstructure return model explaining microstructure noise and Epps effects," Papers 1202.3915, arXiv.org.
  36. Haugom, Erik & Ray, Rina, 2017. "Heterogeneous traders, liquidity, and volatility in crude oil futures market," Journal of Commodity Markets, Elsevier, vol. 5(C), pages 36-49.
  37. Nikolai Dokuchaev, 2012. "On statistical indistinguishability of the complete and incomplete markets," Papers 1209.4695, arXiv.org, revised May 2013.
  38. Guido Russi, 2012. "Estimating the Leverage Effect Using High Frequency Data," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 1-24, February.
  39. Zhang, Chuanhai & Liu, Zhi & Liu, Qiang, 2021. "Jumps at ultra-high frequency: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
  40. Huong Le & Andros Gregoriou, 2020. "How Do You Capture Liquidity? A Review Of The Literature On Low‐Frequency Stock Liquidity," Journal of Economic Surveys, Wiley Blackwell, vol. 34(5), pages 1170-1186, December.
  41. 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 Oct 2018.
  42. Lin, Hai & Lo, Ingrid & Qiao, Rui, 2021. "Macroeconomic news announcements and market efficiency: Evidence from the U.S. Treasury market," Journal of Banking & Finance, Elsevier, vol. 133(C).
  43. Masahiro Watanabe, 2003. "A Model of Stochastic Liquidity," Yale School of Management Working Papers ysm385, Yale School of Management.
  44. 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.
  45. 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.
  46. Alfelt, Gustav & Bodnar, Taras & Javed, Farrukh & Tyrcha, Joanna, 2020. "Singular conditional autoregressive Wishart model for realized covariance matrices," Working Papers 2021:1, Örebro University, School of Business.
  47. Selma Chaker, 2013. "Volatility and Liquidity Costs," Staff Working Papers 13-29, Bank of Canada.
  48. Ghysels, Eric & Sinko, Arthur, 2011. "Volatility forecasting and microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 257-271, January.
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