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- Z. Merrick Li & Oliver Linton, 2022.
"A ReMeDI for Microstructure Noise,"
Econometrica, Econometric Society, vol. 90(1), pages 367-389, January.
- Merrick Li, Z. & Linton, O., 2019. "A ReMeDI for Microstructure Noise," Cambridge Working Papers in Economics 1908, Faculty of Economics, University of Cambridge.
- Jianqing Fan & Yuan Liao & Martina Mincheva, 2013.
"Large covariance estimation by thresholding principal orthogonal complements,"
Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(4), pages 603-680, September.
- Fan, Jianqing & Liao, Yuan & Mincheva, Martina, 2011. "Large covariance estimation by thresholding principal orthogonal complements," MPRA Paper 38697, University Library of Munich, Germany.
- Ziqi Chen & Chenlei Leng, 2016. "Dynamic Covariance Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1196-1207, July.
- Israelsen, Ryan D., 2016. "Does Common Analyst Coverage Explain Excess Comovement?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(4), pages 1193-1229, August.
- Tobias J. Moskowitz & Mark Grinblatt, 1999.
"Do Industries Explain Momentum?,"
Journal of Finance, American Finance Association, vol. 54(4), pages 1249-1290, August.
- Tobias J. Moskowitz & Mark Grinblatt, "undated". "Do Industries Explain Momentum?," CRSP working papers 480, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
- Tobias J. Moskowitz & Mark Grinblatt, "undated". "Do Industries Explain Momentum?," CRSP working papers 352, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
- Chen, Jia & Li, Degui & Linton, Oliver, 2019.
"A new semiparametric estimation approach for large dynamic covariance matrices with multiple conditioning variables,"
Journal of Econometrics, Elsevier, vol. 212(1), pages 155-176.
- Jia Chen & Degui Li & Oliver Linton, 2018. "A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables," Discussion Papers 18/14, Department of Economics, University of York.
- Chen, J. & Li, D. & Linton, O., 2018. "A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables," Cambridge Working Papers in Economics 1876, Faculty of Economics, University of Cambridge.
- Cai, Tony & Liu, Weidong, 2011. "Adaptive Thresholding for Sparse Covariance Matrix Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 672-684.
- Jianqing Fan & Alex Furger & Dacheng Xiu, 2016. "Incorporating Global Industrial Classification Standard Into Portfolio Allocation: A Simple Factor-Based Large Covariance Matrix Estimator With High-Frequency Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 489-503, October.
- Linton,Oliver, 2019.
"Financial Econometrics,"
Cambridge Books,
Cambridge University Press, number 9781107177154, November.
- Linton,Oliver, 2019. "Financial Econometrics," Cambridge Books, Cambridge University Press, number 9781316630334, November.
- Robert F. Engle & Olivier Ledoit & Michael Wolf, 2019.
"Large Dynamic Covariance Matrices,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 363-375, April.
- Robert F. Engle & Olivier Ledoit & Michael Wolf, 2016. "Large dynamic covariance matrices," ECON - Working Papers 231, Department of Economics - University of Zurich, revised Apr 2017.
- Ali, Usman & Hirshleifer, David, 2020.
"Shared analyst coverage: Unifying momentum spillover effects,"
Journal of Financial Economics, Elsevier, vol. 136(3), pages 649-675.
- Usman Ali & David Hirshleifer, 2018. "Shared Analyst Coverage: Unifying Momentum Spillover Effects," NBER Working Papers 25201, National Bureau of Economic Research, Inc.
- Engelberg, Joseph & Ozoguz, Arzu & Wang, Sean, 2018. "Know Thy Neighbor: Industry Clusters, Information Spillovers, and Market Efficiency," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(5), pages 1937-1961, October.
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More about this item
Keywords
Banding; Big Data; Large Covariance Matrix; Network; Thresholding;All these keywords.
JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ETS-2024-06-24 (Econometric Time Series)
- NEP-NET-2024-06-24 (Network Economics)
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