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Cleaning large correlation matrices: tools from random matrix theory

Citations

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Cited by:

  1. Hideto Nakashima & Piotr Graczyk, 2022. "Wigner and Wishart ensembles for sparse Vinberg models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(3), pages 399-433, June.
  2. Chun-Xiao Nie, 2021. "Studying the correlation structure based on market geometry," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 411-441, April.
  3. K. B. Gubbels & J. Y. Ypma & C. W. Oosterlee, 2023. "Principal Component Copulas for Capital Modelling and Systemic Risk," Papers 2312.13195, arXiv.org, revised Dec 2024.
  4. Paolo Giudici & Gloria Polinesi & Alessandro Spelta, 2022. "Network models to improve robot advisory portfolios," Annals of Operations Research, Springer, vol. 313(2), pages 965-989, June.
  5. Tacchella, Andrea & Zaccaria, Andrea & Miccheli, Marco & Pietronero, Luciano, 2023. "Relatedness in the era of machine learning," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
  6. G. L. Zitelli, 2022. "Amalgamated Free Lévy Processes as Limits of Sample Covariance Matrices," Journal of Theoretical Probability, Springer, vol. 35(4), pages 2176-2193, December.
  7. Mattia Guerini & Duc Thi Luu & Mauro Napoletano, 2023. "Synchronization patterns in the European Union," Applied Economics, Taylor & Francis Journals, vol. 55(18), pages 2038-2059, April.
  8. repec:spo:wpmain:info:hdl:2441/5q8fnecj1u87ka099dc571bhi2 is not listed on IDEAS
  9. Tae-Hwy Lee & Millie Yi Mao & Aman Ullah, 2021. "Estimation of high-dimensional dynamic conditional precision matrices with an application to forecast combination," Econometric Reviews, Taylor & Francis Journals, vol. 40(10), pages 905-918, November.
  10. Andr'es Garc'ia-Medina & Benito Rodrigu'ez-Camejo, 2023. "Random matrix theory and nested clustered portfolios on Mexican markets," Papers 2306.05667, arXiv.org.
  11. Gautier Marti, 2019. "CorrGAN: Sampling Realistic Financial Correlation Matrices Using Generative Adversarial Networks," Papers 1910.09504, arXiv.org, revised Dec 2019.
  12. Armine Karami & Raphael Benichou & Michael Benzaquen & Jean-Philippe Bouchaud, 2020. "Conditional Correlations And Principal Regression Analysis For Futures," Working Papers hal-02567501, HAL.
  13. Christian Bongiorno & Damien Challet, 2022. "Reactive global minimum variance portfolios with k-BAHC covariance cleaning," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1344-1360, October.
  14. Armine Karami & Raphael Benichou & Michael Benzaquen & Jean-Philippe Bouchaud, 2019. "Conditional Correlations and Principal Regression Analysis for Futures," Papers 1912.12354, arXiv.org, revised Jan 2020.
  15. Firoozye, Nikan & Tan, Vincent & Zohren, Stefan, 2023. "Canonical portfolios: Optimal asset and signal combination," Journal of Banking & Finance, Elsevier, vol. 154(C).
  16. Sumanjay Dutta & Shashi Jain, 2023. "Precision versus Shrinkage: A Comparative Analysis of Covariance Estimation Methods for Portfolio Allocation," Papers 2305.11298, arXiv.org.
  17. Jerome Garnier-Brun & Michael Benzaquen & Stefano Ciliberti & Jean-Philippe Bouchaud, 2021. "A new spin on optimal portfolios and ecological equilibria," Papers 2104.00668, arXiv.org, revised Oct 2021.
  18. repec:hal:spmain:info:hdl:2441/5q8fnecj1u87ka099dc571bhi2 is not listed on IDEAS
  19. Andrew Butler & Roy H. Kwon, 2021. "Data-driven integration of norm-penalized mean-variance portfolios," Papers 2112.07016, arXiv.org, revised Nov 2022.
  20. Nie, Chun-Xiao, 2021. "Analyzing financial correlation matrix based on the eigenvector–eigenvalue identity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
  21. Lei Wang & Yan Yan & Xiaoteng Li & Xiaosong Chen, 2018. "General Component Analysis (GCA): A new approach to identify Chinese corporate bond market structures," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-18, July.
  22. Sebastien Valeyre, 2022. "Optimal trend following portfolios," Papers 2201.06635, arXiv.org.
  23. Ahmad W. Bitar & Nathan de Carvalho & Valentin Gatignol, 2023. "Covariance matrix estimation for robust portfolio allocation," Working Papers hal-04046454, HAL.
  24. Vincent Tan & Stefan Zohren, 2020. "Estimation of Large Financial Covariances: A Cross-Validation Approach," Papers 2012.05757, arXiv.org, revised Jan 2023.
  25. Jean-Philippe Bouchaud & Iacopo Mastromatteo & Marc Potters & Konstantin Tikhonov, 2022. "Excess Out-of-Sample Risk and Fleeting Modes," Papers 2205.01012, arXiv.org.
  26. Bongiorno, Christian & Challet, Damien, 2023. "Non-linear shrinkage of the price return covariance matrix is far from optimal for portfolio optimization," Finance Research Letters, Elsevier, vol. 52(C).
  27. Christian Bongiorno & Damien Challet, 2020. "Nonparametric sign prediction of high-dimensional correlation matrix coefficients," Papers 2001.11214, arXiv.org.
  28. Ding, Xiucai & Ji, Hong Chang, 2023. "Spiked multiplicative random matrices and principal components," Stochastic Processes and their Applications, Elsevier, vol. 163(C), pages 25-60.
  29. Emmanuelle Jay & Thibault Soler & Eugénie Terreaux & Jean-Philippe Ovarlez & Frédéric Pascal & Philippe de Peretti & Christophe Chorro, 2019. "Improving portfolios global performance using a cleaned and robust covariance matrix estimate," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02354596, HAL.
  30. Mörstedt, Torsten & Lutz, Bernhard & Neumann, Dirk, 2024. "Cross validation based transfer learning for cross-sectional non-linear shrinkage: A data-driven approach in portfolio optimization," European Journal of Operational Research, Elsevier, vol. 318(2), pages 670-685.
  31. Anshul Verma & Orazio Angelini & Tiziana Di Matteo, 2019. "A new set of cluster driven composite development indicators," Papers 1911.11226, arXiv.org, revised Mar 2020.
  32. Antti J Tanskanen & Jani Lukkarinen & Kari Vatanen, 2018. "Random selection of factors preserves the correlation structure in a linear factor model to a high degree," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-22, December.
  33. Jovanovic, Franck & Mantegna, Rosario N. & Schinckus, Christophe, 2019. "When financial economics influences physics: The role of Econophysics," International Review of Financial Analysis, Elsevier, vol. 65(C).
  34. Adil Rengim Cetingoz & Jean-David Fermanian & Olivier Gu'eant, 2022. "Risk Budgeting Portfolios: Existence and Computation," Papers 2211.07212, arXiv.org, revised Sep 2023.
  35. Dimitar Kitanovski & Igor Mishkovski & Viktor Stojkoski & Miroslav Mirchev, 2024. "Network-based diversification of stock and cryptocurrency portfolios," Papers 2408.11739, arXiv.org.
  36. Adil Rengim Cetingoz & Jean‐David Fermanian & Olivier Guéant, 2024. "Risk Budgeting portfolios: Existence and computation," Mathematical Finance, Wiley Blackwell, vol. 34(3), pages 896-924, July.
  37. George Barnes & Sanjaye Ramgoolam & Michael Stephanou, 2023. "Permutation invariant Gaussian matrix models for financial correlation matrices," Papers 2306.04569, arXiv.org.
  38. Christian Bongiorno & Damien Challet, 2024. "Covariance matrix filtering and portfolio optimisation: the average oracle vs non-linear shrinkage and all the variants of DCC-NLS," Quantitative Finance, Taylor & Francis Journals, vol. 24(9), pages 1227-1234, September.
  39. Barnes, George & Ramgoolam, Sanjaye & Stephanou, Michael, 2024. "Permutation invariant Gaussian matrix models for financial correlation matrices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 651(C).
  40. Armine Karami & Raphael Benichou & Michael Benzaquen & Jean-Philippe Bouchaud, 2021. "Conditional Correlations and Principal Regression Analysis for Futures," Post-Print hal-02567501, HAL.
  41. Andrea Tacchella & Andrea Zaccaria & Marco Miccheli & Luciano Pietronero, 2021. "Relatedness in the Era of Machine Learning," Papers 2103.06017, arXiv.org.
  42. Naoki Masuda & Kazuyuki Aihara & Neil G. MacLaren, 2024. "Anticipating regime shifts by mixing early warning signals from different nodes," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
  43. Nystrup, Peter & Lindström, Erik & Møller, Jan K. & Madsen, Henrik, 2021. "Dimensionality reduction in forecasting with temporal hierarchies," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1127-1146.
  44. Rubio-García, Álvaro & Fernández-Lorenzo, Samuel & García-Ripoll, Juan José & Porras, Diego, 2024. "Accurate solution of the Index Tracking problem with a hybrid simulated annealing algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 639(C).
  45. Jerome Garnier-Brun & Michael Benzaquen & Stefano Ciliberti & Jean-Philippe Bouchaud, 2021. "A new spin on optimal portfolios and ecological equilibria," Post-Print hal-03378915, HAL.
  46. Emmanuelle Jay & Thibault Soler & Eugénie Terreaux & Jean-Philippe Ovarlez & Frédéric Pascal & Philippe De Peretti & Christophe Chorro, 2019. "Improving portfolios global performance using a cleaned and robust covariance matrix estimate," Documents de travail du Centre d'Economie de la Sorbonne 19022, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  47. Lars Heinrich & Antoniya Shivarova & Martin Zurek, 2021. "Factor investing: alpha concentration versus diversification," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 464-487, October.
  48. Feng, Wenjun & Zhang, Zhengjun, 2023. "Risk-weighted cryptocurrency indices," Finance Research Letters, Elsevier, vol. 51(C).
  49. Baskerville, Nicholas P. & Granziol, Diego & Keating, Jonathan P., 2022. "Appearance of Random Matrix Theory in deep learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
  50. Yan Zhang & Jiyuan Tao & Zhixiang Yin & Guoqiang Wang, 2022. "Improved Large Covariance Matrix Estimation Based on Efficient Convex Combination and Its Application in Portfolio Optimization," Mathematics, MDPI, vol. 10(22), pages 1-15, November.
  51. László PáL, 2022. "Asset Allocation Strategies Using Covariance Matrix Estimators," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 10(1), pages 133-144, September.
  52. Anshul Verma & Riccardo Junior Buonocore & Tiziana di Matteo, 2017. "A cluster driven log-volatility factor model: a deepening on the source of the volatility clustering," Papers 1712.02138, arXiv.org, revised May 2018.
  53. Emmanuelle Jay & Thibault Soler & Eugénie Terreaux & Jean-Philippe Ovarlez & Frédéric Pascal & Philippe de Peretti & Christophe Chorro, 2019. "Improving portfolios global performance using a cleaned and robust covariance matrix estimate," Post-Print halshs-02354596, HAL.
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