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Principal Component Analysis of High Frequency Data

Citations

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Cited by:

  1. Aït-Sahalia, Yacine & Kalnina, Ilze & Xiu, Dacheng, 2020. "High-frequency factor models and regressions," Journal of Econometrics, Elsevier, vol. 216(1), pages 86-105.
  2. Dovonon, Prosper & Taamouti, Abderrahim & Williams, Julian, 2022. "Testing the eigenvalue structure of spot and integrated covariance," Journal of Econometrics, Elsevier, vol. 229(2), pages 363-395.
  3. Iara da Silva & Caroline Fernanda Hei Wikuats & Elizabeth Mie Hashimoto & Leila Droprinchinski Martins, 2022. "Effects of Environmental and Socioeconomic Inequalities on Health Outcomes: A Multi-Region Time-Series Study," IJERPH, MDPI, vol. 19(24), pages 1-22, December.
  4. Ruijun Bu & Degui Li & Oliver Linton & Hanchao Wang, 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Working Papers 202212, University of Liverpool, Department of Economics.
  5. Bollerslev, Tim & Patton, Andrew J. & Zhang, Haozhe, 2022. "Equity clusters through the lens of realized semicorrelations," Economics Letters, Elsevier, vol. 211(C).
  6. Bu, R. & Li, D. & Linton, O. & Wang, H., 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Cambridge Working Papers in Economics 2218, Faculty of Economics, University of Cambridge.
  7. 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.
  8. Jianqing Fan & Yuan Liao & Han Liu, 2016. "An overview of the estimation of large covariance and precision matrices," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 1-32, February.
  9. Benth, Fred Espen & Schroers, Dennis & Veraart, Almut E.D., 2022. "A weak law of large numbers for realised covariation in a Hilbert space setting," Stochastic Processes and their Applications, Elsevier, vol. 145(C), pages 241-268.
  10. Guangbao Guo & Chunjie Wei & Guoqi Qian, 2023. "Sparse online principal component analysis for parameter estimation in factor model," Computational Statistics, Springer, vol. 38(2), pages 1095-1116, June.
  11. YAMAMOTO, Yohei & 山本, 庸平, 2015. "Asymptotic Inference for Common Factor Models in the Presence of Jumps," Discussion Papers 2015-05, Graduate School of Economics, Hitotsubashi University.
  12. repec:hit:hiasdp:2015-04 is not listed on IDEAS
  13. Chang, Jinyuan & Qiu, Yumou & Yao, Qiwei & Zou, Tao, 2018. "Confidence regions for entries of a large precision matrix," Journal of Econometrics, Elsevier, vol. 206(1), pages 57-82.
  14. Chang, Jinyuan & Qiu, Yumou & Yao, Qiwei & Zou, Tao, 2018. "Confidence regions for entries of a large precision matrix," LSE Research Online Documents on Economics 87513, London School of Economics and Political Science, LSE Library.
  15. Cheng, Mingmian & Swanson, Norman R. & Yang, Xiye, 2021. "Forecasting volatility using double shrinkage methods," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 46-61.
  16. Jos'e E. Figueroa-L'opez & Bei Wu, 2020. "Kernel Estimation of Spot Volatility with Microstructure Noise Using Pre-Averaging," Papers 2004.01865, arXiv.org, revised Feb 2022.
  17. Xianyu Yu & Huachen Gao, 2020. "A landslide susceptibility map based on spatial scale segmentation: A case study at Zigui-Badong in the Three Gorges Reservoir Area, China," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-20, March.
  18. Li, Jia & Todorov, Viktor & Tauchen, George, 2016. "Inference theory for volatility functional dependencies," Journal of Econometrics, Elsevier, vol. 193(1), pages 17-34.
  19. Reiß, Markus & Winkelmann, Lars, 2021. "Inference on the maximal rank of time-varying covariance matrices using high-frequency data," Discussion Papers 2021/14, Free University Berlin, School of Business & Economics.
  20. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
  21. Muhammad Riaz & Babar Zaman & Ishaq Adeyanju Raji & M. Hafidz Omar & Rashid Mehmood & Nasir Abbas, 2022. "An Adaptive EWMA Control Chart Based on Principal Component Method to Monitor Process Mean Vector," Mathematics, MDPI, vol. 10(12), pages 1-27, June.
  22. Li, Hong & Porth, Lysa & Tan, Ken Seng & Zhu, Wenjun, 2021. "Improved index insurance design and yield estimation using a dynamic factor forecasting approach," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 208-221.
  23. Kim Christensen & Mikkel Slot Nielsen & Mark Podolskij, 2023. "High-dimensional estimation of quadratic variation based on penalized realized variance," Statistical Inference for Stochastic Processes, Springer, vol. 26(2), pages 331-359, July.
  24. Calypso Herrera & Florian Krach & Anastasis Kratsios & Pierre Ruyssen & Josef Teichmann, 2020. "Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices," Papers 2004.13612, arXiv.org, revised Jun 2023.
  25. Richard Y. Chen, 2019. "The Fourier Transform Method for Volatility Functional Inference by Asynchronous Observations," Papers 1911.02205, arXiv.org.
  26. Markus Pelger, 2020. "Understanding Systematic Risk: A High‐Frequency Approach," Journal of Finance, American Finance Association, vol. 75(4), pages 2179-2220, August.
  27. Choi, Jungjun & Yang, Xiye, 2022. "Asymptotic properties of correlation-based principal component analysis," Journal of Econometrics, Elsevier, vol. 229(1), pages 1-18.
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