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Olivier Ledoit

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.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Olivier Ledoit & Sébastien Lotz, 2011. "The coexistence of commodity money and fiat money," ECON - Working Papers 024, Department of Economics - University of Zurich.

    Mentioned in:

    1. About a (partial) return to the gold standard
      by Economic Logician in Economic Logic on 2011-10-04 19:22:00

Working papers

  1. Gianluca De Nard & Robert F. Engle & Olivier Ledoit & Michael Wolf, 2020. "Large dynamic covariance matrices: enhancements based on intraday data," ECON - Working Papers 356, Department of Economics - University of Zurich, revised Jan 2022.

    Cited by:

    1. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    2. 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.
    3. Anatolyev, Stanislav & Pyrlik, Vladimir, 2022. "Copula shrinkage and portfolio allocation in ultra-high dimensions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    4. Wenyang Huang & Huiwen Wang & Shanshan Wang, 2021. "Dimension reduction of open-high-low-close data in candlestick chart based on pseudo-PCA," Papers 2103.16908, arXiv.org.
    5. Rafael Alves & Diego S. de Brito & Marcelo C. Medeiros & Ruy M. Ribeiro, 2023. "Forecasting Large Realized Covariance Matrices: The Benefits of Factor Models and Shrinkage," Papers 2303.16151, arXiv.org.
    6. Gianluca De Nard & Robert F. Engle & Bryan Kelly, 2024. "Factor-Mimicking Portfolios for Climate Risk," Financial Analysts Journal, Taylor & Francis Journals, vol. 80(3), pages 37-58, July.
    7. 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).
    8. Richard Luger, 2024. "Regularizing stock return covariance matrices via multiple testing of correlations," Papers 2407.09696, arXiv.org.
    9. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    10. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Attention to oil prices and its impact on the oil, gold and stock markets and their covariance," Energy Economics, Elsevier, vol. 120(C).
    11. De Nard, Gianluca & Zhao, Zhao, 2023. "Using, taming or avoiding the factor zoo? A double-shrinkage estimator for covariance matrices," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 23-35.

  2. Zhao Zhao & Olivier Ledoit & Hui Jiang, 2019. "Risk reduction and efficiency increase in large portfolios: leverage and shrinkage," ECON - Working Papers 328, Department of Economics - University of Zurich, revised Jan 2020.

    Cited by:

    1. Michele Costola & Bertrand Maillet & Zhining Yuan & Xiang Zhang, 2024. "Mean-Variance Efficient Large Portfolios : A Simple Machine Learning Heuristic Technique based on the Two-Fund Separation Theorem," Post-Print hal-04514343, HAL.
    2. Apostolos Chalkis & Emmanouil Christoforou & Ioannis Z. Emiris & Theodore Dalamagas, 2021. "Modeling asset allocations and a new portfolio performance score," Digital Finance, Springer, vol. 3(3), pages 333-371, December.
    3. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Sparsity and Stability for Minimum-Variance Portfolios," Papers 1910.11840, arXiv.org.
    4. Vincent Tan & Stefan Zohren, 2020. "Estimation of Large Financial Covariances: A Cross-Validation Approach," Papers 2012.05757, arXiv.org, revised Jan 2023.
    5. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2021. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 309-352, September.

  3. Olivier Ledoit & Michael Wolf, 2019. "The power of (non-)linear shrinking: a review and guide to covariance matrix estimation," ECON - Working Papers 323, Department of Economics - University of Zurich, revised Feb 2020.

    Cited by:

    1. Taras Bodnar & Nestor Parolya & Erik Thors'en, 2022. "Two is better than one: Regularized shrinkage of large minimum variance portfolio," Papers 2202.06666, arXiv.org.
    2. Ortiz, Roberto & Contreras, Mauricio & Mellado, Cristhian, 2023. "Regression, multicollinearity and Markowitz," Finance Research Letters, Elsevier, vol. 58(PC).
    3. Ruslan Tepelyan & Achintya Gopal, 2023. "Generative Machine Learning for Multivariate Equity Returns," Papers 2311.14735, arXiv.org.
    4. Khashanah, Khaldoun & Simaan, Majeed & Simaan, Yusif, 2022. "Do we need higher-order comoments to enhance mean-variance portfolios? Evidence from a simplified jump process," International Review of Financial Analysis, Elsevier, vol. 81(C).
    5. Damir Filipovic & Paul Schneider, 2024. "Fundamental properties of linear factor models," Papers 2409.02521, arXiv.org, revised Oct 2024.
    6. Benoit Oriol & Alexandre Miot, 2023. "Ledoit-Wolf linear shrinkage with unknown mean," Papers 2304.07045, arXiv.org.
    7. Pier Francesco Procacci & Tomaso Aste, 2021. "Portfolio Optimization with Sparse Multivariate Modelling," Papers 2103.15232, arXiv.org.
    8. Simon Hediger & Jeffrey Näf & Marc S. Paolella & Paweł Polak, 2023. "Heterogeneous tail generalized common factor modeling," Digital Finance, Springer, vol. 5(2), pages 389-420, June.
    9. Pier Francesco Procacci & Tomaso Aste, 2022. "Portfolio optimization with sparse multivariate modeling," Journal of Asset Management, Palgrave Macmillan, vol. 23(6), pages 445-465, October.
    10. Alexandru V. Asimit & Ioannis Kyriakou & Simone Santoni & Salvatore Scognamiglio & Rui Zhu, 2022. "Robust Classification via Support Vector Machines," Risks, MDPI, vol. 10(8), pages 1-25, August.
    11. Sylvia Fruhwirth-Schnatter & Darjus Hosszejni & Hedibert Freitas Lopes, 2023. "When it counts -- Econometric identification of the basic factor model based on GLT structures," Papers 2301.06354, arXiv.org.

  4. Olivier Ledoit & Michael Wolf, 2018. "Robust performance hypothesis testing with smooth functions of population moments," ECON - Working Papers 305, Department of Economics - University of Zurich.

    Cited by:

    1. Markus Leippold & Hanlin Yang, 2023. "Mixed‐frequency predictive regressions with parameter learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 1955-1972, December.
    2. Symitsi, Efthymia & Markellos, Raphael N. & Mantrala, Murali K., 2022. "Keyword portfolio optimization in paid search advertising," European Journal of Operational Research, Elsevier, vol. 303(2), pages 767-778.
    3. Łęt Blanka & Sobański Konrad & Świder Wojciech & Włosik Katarzyna, 2022. "Is the cryptocurrency market efficient? Evidence from an analysis of fundamental factors for Bitcoin and Ethereum," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 58(4), pages 351-370, December.

  5. Gianluca De Nard & Olivier Ledoit & Michael Wolf, 2018. "Factor models for portfolio selection in large dimensions: the good, the better and the ugly," ECON - Working Papers 290, Department of Economics - University of Zurich, revised Dec 2018.

    Cited by:

    1. Stanislav Anatolyev & Vladimir Pyrlik, 2021. "Shrinkage for Gaussian and t Copulas in Ultra-High Dimensions," CERGE-EI Working Papers wp699, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    2. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Working Papers 202111, Geary Institute, University College Dublin.
    3. Cipollini, Fabrizio & Gallo, Giampiero M. & Palandri, Alessandro, 2021. "A dynamic conditional approach to forecasting portfolio weights," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1111-1126.
    4. Lucien Boulet, 2021. "Forecasting High-Dimensional Covariance Matrices of Asset Returns with Hybrid GARCH-LSTMs," Papers 2109.01044, arXiv.org.
    5. Ameer Tamoor Khan & Xinwei Cao & Shuai Li, 2023. "Using Quadratic Interpolated Beetle Antennae Search for Higher Dimensional Portfolio Selection Under Cardinality Constraints," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1413-1435, December.

  6. Olivier Ledoit & Michael Wolf, 2017. "Analytical nonlinear shrinkage of large-dimensional covariance matrices," ECON - Working Papers 264, Department of Economics - University of Zurich, revised Nov 2018.

    Cited by:

    1. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Papers 1910.13960, arXiv.org, revised Oct 2020.
    2. Olivier Ledoit & Michael Wolf, 2019. "The power of (non-)linear shrinking: a review and guide to covariance matrix estimation," ECON - Working Papers 323, Department of Economics - University of Zurich, revised Feb 2020.
    3. Olivier Ledoit & Michael Wolf, 2019. "Shrinkage estimation of large covariance matrices: keep it simple, statistician?," ECON - Working Papers 327, Department of Economics - University of Zurich, revised Jun 2021.

  7. Olivier Ledoit & Michael Wolf, 2016. "Numerical implementation of the QuEST function," ECON - Working Papers 215, Department of Economics - University of Zurich, revised Jan 2017.

    Cited by:

    1. Zhao Zhao & Olivier Ledoit & Hui Jiang, 2019. "Risk reduction and efficiency increase in large portfolios: leverage and shrinkage," ECON - Working Papers 328, Department of Economics - University of Zurich, revised Jan 2020.
    2. 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.
    3. Anatolyev, Stanislav & Pyrlik, Vladimir, 2022. "Copula shrinkage and portfolio allocation in ultra-high dimensions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    4. da Costa, B. Freitas Paulo & Pesenti, Silvana M. & Targino, Rodrigo S., 2023. "Risk budgeting portfolios from simulations," European Journal of Operational Research, Elsevier, vol. 311(3), pages 1040-1056.
    5. Olivier Ledoit & Michael Wolf, 2019. "Quadratic shrinkage for large covariance matrices," ECON - Working Papers 335, Department of Economics - University of Zurich, revised Dec 2020.
    6. Maaz Mahadi & Tarig Ballal & Muhammad Moinuddin & Tareq Y. Al-Naffouri & Ubaid Al-Saggaf, 2022. "Portfolio Optimization Using a Consistent Vector-Based MSE Estimation Approach," Papers 2204.05611, arXiv.org.
    7. Moura, Guilherme V. & Santos, André A.P. & Ruiz, Esther, 2020. "Comparing high-dimensional conditional covariance matrices: Implications for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 118(C).
    8. Seonghun Cho & Shota Katayama & Johan Lim & Young-Geun Choi, 2021. "Positive-definite modification of a covariance matrix by minimizing the matrix $$\ell_{\infty}$$ ℓ ∞ norm with applications to portfolio optimization," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(4), pages 601-627, December.
    9. Ledoit, Olivier & Wolf, Michael, 2021. "Shrinkage estimation of large covariance matrices: Keep it simple, statistician?," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    10. Olivier Ledoit & Michael Wolf, 2019. "Shrinkage estimation of large covariance matrices: keep it simple, statistician?," ECON - Working Papers 327, Department of Economics - University of Zurich, revised Jun 2021.
    11. 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.
    12. Moura, Guilherme V. & Santos, André A. P., 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.
    14. Joel Bun & Jean-Philippe Bouchaud & Marc Potters, 2016. "Cleaning large correlation matrices: tools from random matrix theory," Papers 1610.08104, arXiv.org.

  8. Olivier Ledoit & Michael Wolf & Zhao Zhao, 2016. "Efficient Sorting: A More Powerful Test for Cross-Sectional Anomalies," ECON - Working Papers 238, Department of Economics - University of Zurich, revised May 2018.

    Cited by:

    1. van Zundert, Jeroen, 2018. "Empirical studies on the cross-section of corporate bond and stock markets," Other publications TiSEM 338205fc-a031-4e06-a636-9, Tilburg University, School of Economics and Management.

  9. 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.

    Cited by:

    1. Zhao Zhao & Olivier Ledoit & Hui Jiang, 2019. "Risk reduction and efficiency increase in large portfolios: leverage and shrinkage," ECON - Working Papers 328, Department of Economics - University of Zurich, revised Jan 2020.
    2. Chen Tong & Peter Reinhard Hansen & Ilya Archakov, 2024. "Cluster GARCH," Papers 2406.06860, arXiv.org.
    3. Kawakatsu Hiroyuki, 2021. "Simple Multivariate Conditional Covariance Dynamics Using Hyperbolically Weighted Moving Averages," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 33-52, January.
    4. Elliot Beck & Damian Kozbur & Michael Wolf, 2023. "Hedging Forecast Combinations With an Application to the Random Forest," Papers 2308.15384, arXiv.org, revised Aug 2023.
    5. Carlos Trucíos & João H. G. Mazzeu & Marc Hallin & Luiz K. Hotta & Pedro L. Valls Pereira & Mauricio Zevallos, 2022. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: A General Dynamic Factor Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 40-52, December.
    6. Ahmed, Shamim & Bu, Ziwen & Symeonidis, Lazaros & Tsvetanov, Daniel, 2023. "Which factor model? A systematic return covariation perspective," Journal of International Money and Finance, Elsevier, vol. 136(C).
    7. Andries C. van Vlodrop & Andre (A.) Lucas, 2018. "Estimation Risk and Shrinkage in Vast-Dimensional Fundamental Factor Models," Tinbergen Institute Discussion Papers 18-099/III, Tinbergen Institute.
    8. He, Zhongfang, 2018. "A Class of Generalized Dynamic Correlation Models," MPRA Paper 84820, University Library of Munich, Germany.
    9. Morana, Claudio, 2019. "Regularized semiparametric estimation of high dimensional dynamic conditional covariance matrices," Econometrics and Statistics, Elsevier, vol. 12(C), pages 42-65.
    10. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Papers 1910.13960, arXiv.org, revised Oct 2020.
    11. Llorens-Terrazas, Jordi & Brownlees, Christian, 2023. "Projected Dynamic Conditional Correlations," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1761-1776.
    12. Olivier Ledoit & Michael Wolf, 2022. "Markowitz portfolios under transaction costs," ECON - Working Papers 420, Department of Economics - University of Zurich, revised Sep 2024.
    13. Plachel, Lukas, 2019. "A unified model for regularized and robust portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
    14. Kei Nakagawa & Yusuke Uchiyama, 2020. "GO-GJRSK Model with Application to Higher Order Risk-Based Portfolio," Mathematics, MDPI, vol. 8(11), pages 1-12, November.
    15. Christian Francq & Jean-Michel Zakoian, 2019. "Virtual Historical Simulation for estimating the conditional VaR of large portfolios," Papers 1909.04661, arXiv.org.
    16. Chazi, Abdelaziz & Samet, Anis & Azad, A.S.M. Sohel, 2023. "Volatility and correlation of Islamic and conventional indices during crises," Global Finance Journal, Elsevier, vol. 55(C).
    17. Yusuke Uchiyama & Kei Nakagawa, 2020. "TPLVM: Portfolio Construction by Student's $t$-process Latent Variable Model," Papers 2002.06243, arXiv.org.
    18. Kwangmin Jung & Donggyu Kim & Seunghyeon Yu, 2022. "Next generation models for portfolio risk management: An approach using financial big data," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(3), pages 765-787, September.
    19. Ilya Archakov & Peter Reinhard Hansen & Asger Lunde, 2020. "A Multivariate Realized GARCH Model," Papers 2012.02708, arXiv.org, revised May 2024.
    20. Qifa Xu & Junqing Zuo & Cuixia Jiang & Yaoyao He, 2021. "A large constrained time‐varying portfolio selection model with DCC‐MIDAS: Evidence from Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3417-3435, July.
    21. Ge, S. & Li, S. & Linton, O. B. & Liu, W. & Su, W., 2024. "Should We Augment Large Covariance Matrix Estimation with Auxiliary Network Information?," Cambridge Working Papers in Economics 2427, Faculty of Economics, University of Cambridge.
    22. 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.
    23. Anatolyev, Stanislav & Pyrlik, Vladimir, 2022. "Copula shrinkage and portfolio allocation in ultra-high dimensions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    24. Olivier Ledoit & Michael Wolf, 2017. "Analytical nonlinear shrinkage of large-dimensional covariance matrices," ECON - Working Papers 264, Department of Economics - University of Zurich, revised Nov 2018.
    25. Christian Bongiorno & Damien Challet, 2023. "Covariance matrix filtering and portfolio optimisation: the Average Oracle vs Non-Linear Shrinkage and all the variants of DCC-NLS," Papers 2309.17219, arXiv.org.
    26. Catherine D'Hondt & Rudy De Winne & Eric Ghysels & Steve Raymond, 2019. "Artificial Intelligence Alter Egos: Who benefits from Robo-investing?," Papers 1907.03370, arXiv.org.
    27. Hediger, Simon & Näf, Jeffrey, 2024. "Combining the MGHyp distribution with nonlinear shrinkage in modeling financial asset returns," Journal of Empirical Finance, Elsevier, vol. 77(C).
    28. Yusuke Uchiyama & Kei Nakagawa, 2020. "TPLVM: Portfolio Construction by Student’s t -Process Latent Variable Model," Mathematics, MDPI, vol. 8(3), pages 1-10, March.
    29. Benjamin Poignard & Manabu Asai, 2022. "High-Dimensional Sparse Multivariate Stochastic Volatility Models," Papers 2201.08584, arXiv.org, revised May 2022.
    30. László PáL, 2022. "Asset Allocation Strategies Using Covariance Matrix Estimators," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 10(1), pages 133-144, September.
    31. Jian Zhang & Jie Li, 2022. "Factorized estimation of high‐dimensional nonparametric covariance models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(2), pages 542-567, June.
    32. Nikolaus Hautsch & Stefan Voigt, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty," Papers 1709.06296, arXiv.org, revised Jun 2018.
    33. Olivier Ledoit & Michael Wolf, 2019. "Quadratic shrinkage for large covariance matrices," ECON - Working Papers 335, Department of Economics - University of Zurich, revised Dec 2020.
    34. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Sparsity and Stability for Minimum-Variance Portfolios," Papers 1910.11840, arXiv.org.
    35. Christian Bongiorno & Damien Challet, 2021. "Reactive Global Minimum Variance Portfolios with $k-$BAHC covariance cleaning," Post-Print hal-02612262, HAL.
    36. 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.
    37. Stanislav Anatolyev & Vladimir Pyrlik, 2021. "Shrinkage for Gaussian and t Copulas in Ultra-High Dimensions," CERGE-EI Working Papers wp699, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    38. Gianluca De Nard & Robert F. Engle & Olivier Ledoit & Michael Wolf, 2020. "Large dynamic covariance matrices: enhancements based on intraday data," ECON - Working Papers 356, Department of Economics - University of Zurich, revised Jan 2022.
    39. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    40. Emilija Dzuverovic & Matteo Barigozzi, 2023. "Hierarchical DCC-HEAVY Model for High-Dimensional Covariance Matrices," Papers 2305.08488, arXiv.org, revised Jul 2024.
    41. Rafael Alves & Diego S. de Brito & Marcelo C. Medeiros & Ruy M. Ribeiro, 2023. "Forecasting Large Realized Covariance Matrices: The Benefits of Factor Models and Shrinkage," Papers 2303.16151, arXiv.org.
    42. 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).
    43. Khashanah, Khaldoun & Simaan, Majeed & Simaan, Yusif, 2022. "Do we need higher-order comoments to enhance mean-variance portfolios? Evidence from a simplified jump process," International Review of Financial Analysis, Elsevier, vol. 81(C).
    44. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    45. De Nard, Gianluca & Zhao, Zhao, 2022. "A large-dimensional test for cross-sectional anomalies:Efficient sorting revisited," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 654-676.
    46. Damir Filipovic & Paul Schneider, 2024. "Fundamental properties of linear factor models," Papers 2409.02521, arXiv.org, revised Oct 2024.
    47. Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
    48. Firoozye, Nikan & Tan, Vincent & Zohren, Stefan, 2023. "Canonical portfolios: Optimal asset and signal combination," Journal of Banking & Finance, Elsevier, vol. 154(C).
    49. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Working Papers 202111, Geary Institute, University College Dublin.
    50. Cheng Yu & Dong Li & Feiyu Jiang & Ke Zhu, 2023. "Matrix GARCH Model: Inference and Application," Papers 2306.05169, arXiv.org.
    51. 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.
    52. Gianluca De Nard & Robert F. Engle & Bryan Kelly, 2024. "Factor-Mimicking Portfolios for Climate Risk," Financial Analysts Journal, Taylor & Francis Journals, vol. 80(3), pages 37-58, July.
    53. Anja Vinzelberg & Benjamin R. Auer, 2022. "Unprofitability of food market investments," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 2887-2910, October.
    54. Qiao, W. & Bu, D. & Gibberd, A. & Liao, Y. & Wen, T. & Li, E., 2023. "When “time varying” volatility meets “transaction cost” in portfolio selection," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 220-237.
    55. Fan, Qingliang & Wu, Ruike & Yang, Yanrong & Zhong, Wei, 2024. "Time-varying minimum variance portfolio," Journal of Econometrics, Elsevier, vol. 239(2).
    56. Pietro Coretto & Michele La Rocca & Giuseppe Storti, 2020. "Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters," JRFM, MDPI, vol. 13(4), pages 1-23, March.
    57. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    58. Dong, Yingjie & Tse, Yiu-Kuen, 2020. "Forecasting large covariance matrix with high-frequency data using factor approach for the correlation matrix," Economics Letters, Elsevier, vol. 195(C).
    59. Gianluca De Nard & Simon Hediger & Markus Leippold, 2022. "Subsampled factor models for asset pricing: The rise of Vasa," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1217-1247, September.
    60. 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).
    61. Richard Luger, 2024. "Regularizing stock return covariance matrices via multiple testing of correlations," Papers 2407.09696, arXiv.org.
    62. Ge, S. & Li, S. & Linton, O. B. & Liu, W. & Su, W., 2024. "Should We Augment Large Covariance Matrix Estimation with Auxiliary Network Information?," Janeway Institute Working Papers 2416, Faculty of Economics, University of Cambridge.
    63. M. Raddant & T. Di Matteo, 2023. "A Look at Financial Dependencies by Means of Econophysics and Financial Economics," Papers 2302.08208, arXiv.org.
    64. Chuting Sun & Qi Wu & Xing Yan, 2023. "Dynamic CVaR Portfolio Construction with Attention-Powered Generative Factor Learning," Papers 2301.07318, arXiv.org, revised Jan 2024.
    65. Raddant, Matthias & Kenett, Dror Y., 2017. "Interconnectedness in the global financial market," Kiel Working Papers 2076, Kiel Institute for the World Economy (IfW Kiel).
    66. Laura Liu & Christian Matthes & Katerina Petrova, 2018. "Monetary Policy across Space and Time," Working Paper 18-14, Federal Reserve Bank of Richmond.
    67. Wang, Hanchao & Peng, Bin & Li, Degui & Leng, Chenlei, 2021. "Nonparametric estimation of large covariance matrices with conditional sparsity," Journal of Econometrics, Elsevier, vol. 223(1), pages 53-72.
    68. Sylvia Gottschalk, 2023. "From Black Wednesday to Brexit: Macroeconomic shocks and correlations of equity returns in France, Germany, Italy, Spain, and the United Kingdom," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2843-2873, July.
    69. Sun, Chuting & Wu, Qi & Yan, Xing, 2024. "Dynamic CVaR portfolio construction with attention-powered generative factor learning," Journal of Economic Dynamics and Control, Elsevier, vol. 160(C).
    70. Cipollini, Fabrizio & Gallo, Giampiero M. & Palandri, Alessandro, 2021. "A dynamic conditional approach to forecasting portfolio weights," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1111-1126.
    71. Moura, Guilherme V. & Santos, André A.P. & Ruiz, Esther, 2020. "Comparing high-dimensional conditional covariance matrices: Implications for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 118(C).
    72. Grønborg, Niels S. & Lunde, Asger & Olesen, Kasper V. & Vander Elst, Harry, 2022. "Realizing correlations across asset classes," Journal of Financial Markets, Elsevier, vol. 59(PA).
    73. Trucíos, Carlos & Hotta, Luiz K. & Valls Pereira, Pedro L., 2019. "On the robustness of the principal volatility components," Journal of Empirical Finance, Elsevier, vol. 52(C), pages 201-219.
    74. Olivier Ledoit & Michael Wolf, 2019. "The power of (non-)linear shrinking: a review and guide to covariance matrix estimation," ECON - Working Papers 323, Department of Economics - University of Zurich, revised Feb 2020.
    75. 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.
    76. Niels S. Grønborg & Asger Lunde & Kasper V. Olesen & Harry Vander Elst, 2018. "Realizing Correlations Across Asset Classes," CREATES Research Papers 2018-37, Department of Economics and Business Economics, Aarhus University.
    77. Vincent Tan & Stefan Zohren, 2020. "Estimation of Large Financial Covariances: A Cross-Validation Approach," Papers 2012.05757, arXiv.org, revised Jan 2023.
    78. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    79. Gianluca De Nard & Olivier Ledoit & Michael Wolf, 2018. "Factor models for portfolio selection in large dimensions: the good, the better and the ugly," ECON - Working Papers 290, Department of Economics - University of Zurich, revised Dec 2018.
    80. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2022. "Sparsity and stability for minimum-variance portfolios," Risk Management, Palgrave Macmillan, vol. 24(3), pages 214-235, September.
    81. Ledoit, Olivier & Wolf, Michael, 2017. "Numerical implementation of the QuEST function," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 199-223.
    82. Stadtmüller, Immo & Auer, Benjamin R. & Schuhmacher, Frank, 2022. "On the benefits of active stock selection strategies for diversified investors," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 342-354.
    83. Liu, Cheng & Wang, Moming & Xia, Ningning, 2022. "Design-free estimation of integrated covariance matrices for high-frequency data," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    84. Ledoit, Olivier & Wolf, Michael, 2021. "Shrinkage estimation of large covariance matrices: Keep it simple, statistician?," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    85. Olivier Ledoit & Michael Wolf, 2019. "Shrinkage estimation of large covariance matrices: keep it simple, statistician?," ECON - Working Papers 327, Department of Economics - University of Zurich, revised Jun 2021.
    86. Marc Hallin & Carlos Trucíos, 2020. "Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios: a General Dynamic Factor Approach," Working Papers ECARES 2020-50, ULB -- Universite Libre de Bruxelles.
    87. Bian, Zhicun & Liao, Yin & O’Neill, Michael & Shi, Jing & Zhang, Xueyong, 2020. "Large-scale minimum variance portfolio allocation using double regularization," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    88. Moura, Guilherme V. & Santos, André A. P., 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
    89. Kei Nakagawa & Mitsuyoshi Imamura & Kenichi Yoshida, 2018. "Risk-Based Portfolios with Large Dynamic Covariance Matrices," IJFS, MDPI, vol. 6(2), pages 1-14, May.
    90. Ding, Yi & Li, Yingying & Zheng, Xinghua, 2021. "High dimensional minimum variance portfolio estimation under statistical factor models," Journal of Econometrics, Elsevier, vol. 222(1), pages 502-515.
    91. Lam, Clifford, 2020. "High-dimensional covariance matrix estimation," LSE Research Online Documents on Economics 101667, London School of Economics and Political Science, LSE Library.
    92. Yfanti, Stavroula & Karanasos, Menelaos & Zopounidis, Constantin & Christopoulos, Apostolos, 2023. "Corporate credit risk counter-cyclical interdependence: A systematic analysis of cross-border and cross-sector correlation dynamics," European Journal of Operational Research, Elsevier, vol. 304(2), pages 813-831.
    93. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    94. Karim M Abadir, 2023. "Explicit minimal representation of variance matrices, and its implication for dynamic volatility models," The Econometrics Journal, Royal Economic Society, vol. 26(1), pages 88-104.
    95. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.
    96. Hallin, Marc & Trucíos, Carlos, 2023. "Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach," Econometrics and Statistics, Elsevier, vol. 27(C), pages 1-15.
    97. D’Hondt, Catherine & De Winne, Rudy & Ghysels, Eric & Raymond, Steve, 2020. "Artificial Intelligence Alter Egos: Who might benefit from robo-investing?," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 278-299.
    98. Xiaoning Kang & Xinwei Deng & Kam‐Wah Tsui & Mohsen Pourahmadi, 2020. "On variable ordination of modified Cholesky decomposition for estimating time‐varying covariance matrices," International Statistical Review, International Statistical Institute, vol. 88(3), pages 616-641, December.
    99. Sama Haddad, 2023. "Global Financial Market Integration: A Literature Survey," JRFM, MDPI, vol. 16(12), pages 1-27, November.
    100. Jilber Urbina & Miguel Santolino & Montserrat Guillen, 2021. "Covariance Principle for Capital Allocation: A Time-Varying Approach," Mathematics, MDPI, vol. 9(16), pages 1-13, August.
    101. Christis Katsouris, 2021. "Optimal Portfolio Choice and Stock Centrality for Tail Risk Events," Papers 2112.12031, arXiv.org.
    102. van Zundert, Jeroen, 2018. "Empirical studies on the cross-section of corporate bond and stock markets," Other publications TiSEM 338205fc-a031-4e06-a636-9, Tilburg University, School of Economics and Management.
    103. Masaya Abe & Kei Nakagawa, 2020. "Cross-sectional Stock Price Prediction using Deep Learning for Actual Investment Management," Papers 2002.06975, arXiv.org.
    104. Cai, Zhanrui & Li, Changcheng & Wen, Jiawei & Yang, Songshan, 2024. "Asset splitting algorithm for ultrahigh dimensional portfolio selection and its theoretical property," Journal of Econometrics, Elsevier, vol. 239(2).
    105. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2021. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 309-352, September.
    106. Alessandra Amendola & Vincenzo Candila & Antonio Naimoli & Giuseppe Storti, 2024. "Adaptive combinations of tail-risk forecasts," Papers 2406.06235, arXiv.org.
    107. De Nard, Gianluca & Zhao, Zhao, 2023. "Using, taming or avoiding the factor zoo? A double-shrinkage estimator for covariance matrices," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 23-35.

  10. Olivier Ledoit & Michael Wolf, 2014. "Nonlinear shrinkage of the covariance matrix for portfolio selection: Markowitz meets Goldilocks," ECON - Working Papers 137, Department of Economics - University of Zurich, revised Feb 2017.

    Cited by:

    1. Francesco Lautizi, 2015. "Large Scale Covariance Estimates for Portfolio Selection," CEIS Research Paper 353, Tor Vergata University, CEIS, revised 07 Aug 2015.
    2. Hsu, Po-Hsuan & Han, Qiheng & Wu, Wensheng & Cao, Zhiguang, 2018. "Asset allocation strategies, data snooping, and the 1 / N rule," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 257-269.
    3. Ledoit, Olivier & Wolf, Michael, 2017. "Numerical implementation of the QuEST function," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 199-223.

  11. Olivier Ledoit & Michael Wolf, 2013. "Optimal estimation of a large-dimensional covariance matrix under Stein’s loss," ECON - Working Papers 122, Department of Economics - University of Zurich, revised Mar 2017.

    Cited by:

    1. Olivier Ledoit & Michael Wolf, 2014. "Nonlinear shrinkage of the covariance matrix for portfolio selection: Markowitz meets Goldilocks," ECON - Working Papers 137, Department of Economics - University of Zurich, revised Feb 2017.
    2. Brett Naul & Bala Rajaratnam & Dario Vincenzi, 2016. "The role of the isotonizing algorithm in Stein’s covariance matrix estimator," Computational Statistics, Springer, vol. 31(4), pages 1453-1476, December.

  12. Olivier Ledoit & Michael Wolf, 2013. "Spectrum estimation: a unified framework for covariance matrix estimation and PCA in large dimensions," ECON - Working Papers 105, Department of Economics - University of Zurich, revised Jul 2013.

    Cited by:

    1. Zhao Zhao & Olivier Ledoit & Hui Jiang, 2019. "Risk reduction and efficiency increase in large portfolios: leverage and shrinkage," ECON - Working Papers 328, Department of Economics - University of Zurich, revised Jan 2020.
    2. Andries C. van Vlodrop & Andre (A.) Lucas, 2018. "Estimation Risk and Shrinkage in Vast-Dimensional Fundamental Factor Models," Tinbergen Institute Discussion Papers 18-099/III, Tinbergen Institute.
    3. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Papers 1910.13960, arXiv.org, revised Oct 2020.
    4. Plachel, Lukas, 2019. "A unified model for regularized and robust portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
    5. Wen, Jun, 2018. "Estimation of two high-dimensional covariance matrices and the spectrum of their ratio," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 1-29.
    6. Ikeda, Yuki & Kubokawa, Tatsuya & Srivastava, Muni S., 2016. "Comparison of linear shrinkage estimators of a large covariance matrix in normal and non-normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 95(C), pages 95-108.
    7. Hafner, Christian & Linton, Oliver & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," LIDAM Reprints ISBA 2020028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. 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.
    9. Huang, Na & Fryzlewicz, Piotr, 2018. "NOVELIST estimator of large correlation and covariance matrices and their inverses," LSE Research Online Documents on Economics 89055, London School of Economics and Political Science, LSE Library.
    10. Olivier Ledoit & Michael Wolf, 2017. "Analytical nonlinear shrinkage of large-dimensional covariance matrices," ECON - Working Papers 264, Department of Economics - University of Zurich, revised Nov 2018.
    11. Tsubasa Ito & Tatsuya Kubokawa, 2015. "Linear Ridge Estimator of High-Dimensional Precision Matrix Using Random Matrix Theory ," CIRJE F-Series CIRJE-F-995, CIRJE, Faculty of Economics, University of Tokyo.
    12. Hediger, Simon & Näf, Jeffrey, 2024. "Combining the MGHyp distribution with nonlinear shrinkage in modeling financial asset returns," Journal of Empirical Finance, Elsevier, vol. 77(C).
    13. Olivier Ledoit & Michael Wolf, 2019. "Quadratic shrinkage for large covariance matrices," ECON - Working Papers 335, Department of Economics - University of Zurich, revised Dec 2020.
    14. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Sparsity and Stability for Minimum-Variance Portfolios," Papers 1910.11840, arXiv.org.
    15. Tae-Hwy Lee & Ekaterina Seregina, 2020. "Learning from Forecast Errors: A New Approach to Forecast Combinations," Papers 2011.02077, arXiv.org, revised May 2021.
    16. Gianluca De Nard & Robert F. Engle & Olivier Ledoit & Michael Wolf, 2020. "Large dynamic covariance matrices: enhancements based on intraday data," ECON - Working Papers 356, Department of Economics - University of Zurich, revised Jan 2022.
    17. Patrik Guggenberger & Frank Kleibergen & Sophocles Mavroeidis, 2020. "A Test for Kronecker Product Structure Covariance Matrix," Papers 2010.10961, arXiv.org, revised Jan 2022.
    18. Firoozye, Nikan & Tan, Vincent & Zohren, Stefan, 2023. "Canonical portfolios: Optimal asset and signal combination," Journal of Banking & Finance, Elsevier, vol. 154(C).
    19. Olivier Ledoit & Michael Wolf, 2014. "Nonlinear shrinkage of the covariance matrix for portfolio selection: Markowitz meets Goldilocks," ECON - Working Papers 137, Department of Economics - University of Zurich, revised Feb 2017.
    20. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    21. Richard Luger, 2024. "Regularizing stock return covariance matrices via multiple testing of correlations," Papers 2407.09696, arXiv.org.
    22. Yuasa, Ryota & Kubokawa, Tatsuya, 2020. "Ridge-type linear shrinkage estimation of the mean matrix of a high-dimensional normal distribution," Journal of Multivariate Analysis, Elsevier, vol. 178(C).
    23. Olivier Ledoit & Michael Wolf, 2019. "The power of (non-)linear shrinking: a review and guide to covariance matrix estimation," ECON - Working Papers 323, Department of Economics - University of Zurich, revised Feb 2020.
    24. Joongyeub Yeo & George Papanicolaou, 2016. "Random matrix approach to estimation of high-dimensional factor models," Papers 1611.05571, arXiv.org, revised Nov 2017.
    25. Yang, Guangren & Liu, Yiming & Pan, Guangming, 2019. "Weighted covariance matrix estimation," Computational Statistics & Data Analysis, Elsevier, vol. 139(C), pages 82-98.
    26. Vincent Tan & Stefan Zohren, 2020. "Estimation of Large Financial Covariances: A Cross-Validation Approach," Papers 2012.05757, arXiv.org, revised Jan 2023.
    27. Gianluca De Nard & Olivier Ledoit & Michael Wolf, 2018. "Factor models for portfolio selection in large dimensions: the good, the better and the ugly," ECON - Working Papers 290, Department of Economics - University of Zurich, revised Dec 2018.
    28. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2022. "Sparsity and stability for minimum-variance portfolios," Risk Management, Palgrave Macmillan, vol. 24(3), pages 214-235, September.
    29. 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.
    30. Ledoit, Olivier & Wolf, Michael, 2017. "Numerical implementation of the QuEST function," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 199-223.
    31. 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.
    32. Liusha Yang & Matthew R. Mckay & Romain Couillet, 2018. "High-Dimensional MVDR Beamforming: Optimized Solutions Based on Spiked Random Matrix Models," Post-Print hal-01957672, HAL.
    33. Liu, Cheng & Wang, Moming & Xia, Ningning, 2022. "Design-free estimation of integrated covariance matrices for high-frequency data," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    34. Ikeda, Yuki & Kubokawa, Tatsuya, 2016. "Linear shrinkage estimation of large covariance matrices using factor models," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 61-81.
    35. Jamshid Namdari & Debashis Paul & Lili Wang, 2021. "High-Dimensional Linear Models: A Random Matrix Perspective," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 645-695, August.
    36. Ledoit, Olivier & Wolf, Michael, 2021. "Shrinkage estimation of large covariance matrices: Keep it simple, statistician?," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    37. Tsukuma, Hisayuki, 2016. "Estimation of a high-dimensional covariance matrix with the Stein loss," Journal of Multivariate Analysis, Elsevier, vol. 148(C), pages 1-17.
    38. Olivier Ledoit & Michael Wolf, 2019. "Shrinkage estimation of large covariance matrices: keep it simple, statistician?," ECON - Working Papers 327, Department of Economics - University of Zurich, revised Jun 2021.
    39. 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.
    40. Farnè, Matteo & Montanari, Angela, 2020. "A large covariance matrix estimator under intermediate spikiness regimes," Journal of Multivariate Analysis, Elsevier, vol. 176(C).
    41. Esra Ulasan & A. Özlem Önder, 2023. "Large portfolio optimisation approaches," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 485-497, October.
    42. Zhonghui Zhang & Huarui Jing & Chihwa Kao, 2023. "High-Dimensional Distributionally Robust Mean-Variance Efficient Portfolio Selection," Mathematics, MDPI, vol. 11(5), pages 1-16, March.
    43. Lam, Clifford, 2020. "High-dimensional covariance matrix estimation," LSE Research Online Documents on Economics 101667, London School of Economics and Political Science, LSE Library.
    44. Olivier Ledoit & Michael Wolf, 2013. "Optimal estimation of a large-dimensional covariance matrix under Stein’s loss," ECON - Working Papers 122, Department of Economics - University of Zurich, revised Mar 2017.
    45. Joel Bun & Jean-Philippe Bouchaud & Marc Potters, 2016. "Cleaning large correlation matrices: tools from random matrix theory," Papers 1610.08104, arXiv.org.
    46. Na Huang & Piotr Fryzlewicz, 2019. "NOVELIST estimator of large correlation and covariance matrices and their inverses," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 694-727, September.
    47. Linton, O. & Tang, H., 2020. "Estimation of the Kronecker Covariance Model by Quadratic Form," Cambridge Working Papers in Economics 2050, Faculty of Economics, University of Cambridge.
    48. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2021. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 309-352, September.
    49. De Nard, Gianluca & Zhao, Zhao, 2023. "Using, taming or avoiding the factor zoo? A double-shrinkage estimator for covariance matrices," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 23-35.

  13. Olivier Ledoit, 2011. "The redistributive effects of monetary policy," ECON - Working Papers 044, Department of Economics - University of Zurich.

    Cited by:

    1. Villarreal, Francisco G., 2014. "Financial Services and Household Inequality in Mexico," MPRA Paper 57075, University Library of Munich, Germany.
    2. Nils M. Gornemann & Keith Kuester & Makoto Nakajima, 2012. "Monetary policy with heterogeneous agents," Working Papers 12-21, Federal Reserve Bank of Philadelphia.
    3. Romain Baeriswyl & Camille Cornand, 2015. "The distortionary effect of monetary policy : credit expansion vs. lump-sum transfers in the lab," Working Papers 1516, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    4. Pierre Monnin, 2014. "Inflation and Income Inequality in Developed Economies," Working Papers 1401, Council on Economic Policies.
    5. Süssmuth, Bernd & Wieschemeyer, Matthias, 2022. "Taxation and the distributional impact of inflation: The U.S. post-war experience," Economic Modelling, Elsevier, vol. 111(C).
    6. Arkadiusz Sieron, 2017. "Inflation and Income Inequality," Prague Economic Papers, Prague University of Economics and Business, vol. 2017(6), pages 633-645.
    7. Ohad Raveh, 2020. "Monetary Policy, Natural Resources, and Federal Redistribution," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(3), pages 585-613, March.
    8. Ohad Raveh, 2016. "Monetary Policy, Fisal Federalism, and Capital Intensity," OxCarre Working Papers 181, Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford.
    9. Pierre Monnin & Alexander Barkawi, 2015. "Monetary Policy and Sustainability. The Case of Bangladesh," Discussion Notes 1501, Council on Economic Policies.
    10. Hazra, Devika, 2022. "Does monetary policy favor the skilled? − Distributional role of monetary policy," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 65-86.

  14. Olivier Ledoit & Michael Wolf, 2011. "Nonlinear shrinkage estimation of large-dimensional covariance matrices," IEW - Working Papers 515, Institute for Empirical Research in Economics - University of Zurich.

    Cited by:

    1. Imre Kondor & G'abor Papp & Fabio Caccioli, 2017. "Analytic approach to variance optimization under an $\ell_1$ constraint," Papers 1709.08755, arXiv.org, revised Jul 2018.
    2. Imre Kondor & G'abor Papp & Fabio Caccioli, 2016. "Analytic solution to variance optimization with no short-selling," Papers 1612.07067, arXiv.org, revised Jan 2017.

  15. Oliver Ledoit & Michael Wolf, 2008. "Robust Performance Hypothesis Testing with the Sharpe Ratio," IEW - Working Papers 320, Institute for Empirical Research in Economics - University of Zurich.

    Cited by:

    1. Gabriel Frahm & Tobias Wickern & Christof Wiechers, 2012. "Multiple tests for the performance of different investment strategies," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(3), pages 343-383, July.
    2. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Bond portfolio optimization using dynamic factor models," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 128-158.
    3. Haffar, Adlane & Le Fur, Éric, 2022. "Time-varying dependence of Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 211-220.
    4. João Caldeira & Guilherme Moura & André A.P. Santos, 2012. "Portfolio optimization using a parsimonious multivariate GARCH model: application to the Brazilian stock market," Economics Bulletin, AccessEcon, vol. 32(3), pages 1848-1857.
    5. Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Miffre, Joëlle, 2019. "A comprehensive appraisal of style-integration methods," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 134-150.
    6. Santos, André A.P. & Nogales, Francisco J. & Ruiz, Esther & Dijk, Dick Van, 2012. "Optimal portfolios with minimum capital requirements," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1928-1942.
    7. Malavasi, Matteo & Ortobelli Lozza, Sergio & Trück, Stefan, 2021. "Second order of stochastic dominance efficiency vs mean variance efficiency," European Journal of Operational Research, Elsevier, vol. 290(3), pages 1192-1206.
    8. Giovanni Bonaccolto & Massimiliano Caporin & Sandra Paterlini, 2015. "Asset Allocation Strategies Based On Penalized Quantile Regression," "Marco Fanno" Working Papers 0199, Dipartimento di Scienze Economiche "Marco Fanno".
    9. Ding, Wenliang & Shu, Lianjie & Gu, Xinhua, 2023. "A robust Glasso approach to portfolio selection in high dimensions," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 22-37.
    10. Bernd Scherer, 2021. "Adding alternative assets: return enhancement, diversification or hedging?," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 437-442, October.
    11. Bertrand Candelon & Christophe Hurlin & Sessi Tokpavi, 2012. "Sampling Error and Double Shrinkage Estimation of Minimum Variance Portfolios," Post-Print hal-01385835, HAL.
    12. Alex Huang, 2013. "Value at risk estimation by quantile regression and kernel estimator," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 225-251, August.
    13. DeMiguel, Victor & Lassance, Nathan & Vrins, Frédéric, 2021. "Optimal Portfolio Diversification via Independent Component Analysis," LIDAM Discussion Papers LFIN 2021014, Université catholique de Louvain, Louvain Finance (LFIN).
    14. Liusha Yang & Romain Couillet & Matthew R. McKay, 2015. "A Robust Statistics Approach to Minimum Variance Portfolio Optimization," Papers 1503.08013, arXiv.org.
    15. Pedro Barroso & Jurij-Andrei Reichenecker & Marco J. Menichetti, 2022. "Hedging with an Edge: Parametric Currency Overlay," Management Science, INFORMS, vol. 68(1), pages 669-689, January.
    16. Ahmed, Shamim & Bu, Ziwen & Symeonidis, Lazaros & Tsvetanov, Daniel, 2023. "Which factor model? A systematic return covariation perspective," Journal of International Money and Finance, Elsevier, vol. 136(C).
    17. Sleire, Anders D. & Støve, Bård & Otneim, Håkon & Berentsen, Geir Drage & Tjøstheim, Dag & Haugen, Sverre Hauso, 2022. "Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations," Finance Research Letters, Elsevier, vol. 46(PB).
    18. Hao Jiang & Marno Verbeek & Yu Wang, 2014. "Information Content When Mutual Funds Deviate from Benchmarks," Management Science, INFORMS, vol. 60(8), pages 2038-2053, August.
    19. Philipp J. Kremer & Andreea Talmaciu & Sandra Paterlini, 2018. "Risk minimization in multi-factor portfolios: What is the best strategy?," Annals of Operations Research, Springer, vol. 266(1), pages 255-291, July.
    20. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Efficient skewness/semivariance portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 17(5), pages 331-346, September.
    21. Christian Fieberg & Gerrit Liedtke & Daniel Metko & Adam Zaremba, 2023. "Cryptocurrency factor momentum," Quantitative Finance, Taylor & Francis Journals, vol. 23(12), pages 1853-1869, November.
    22. Olga Biedova & Victoria Steblovskaya, 2020. "Multiplier Optimization For Constant Proportion Portfolio Insurance (Cppi) Strategy," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 23(02), pages 1-22, March.
    23. Seyoung Park & Eun Ryung Lee & Sungchul Lee & Geonwoo Kim, 2019. "Dantzig Type Optimization Method with Applications to Portfolio Selection," Sustainability, MDPI, vol. 11(11), pages 1-32, June.
    24. Márcio Poletti Laurini & Roberto Baltieri Mauad & Fernando Antonio Lucena Aiube, 2016. "Multivariate Stochastic Volatility-Double Jump Model: an application for oil assets," Working Papers Series 415, Central Bank of Brazil, Research Department.
    25. de Groot, Wilma & Karstanje, Dennis & Zhou, Weili, 2014. "Exploiting commodity momentum along the futures curves," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 79-93.
    26. McDowell, Shaun, 2018. "An empirical evaluation of estimation error reduction strategies applied to international diversification," Journal of Multinational Financial Management, Elsevier, vol. 44(C), pages 1-13.
    27. Anlan Wang & Aleš Kresta & Tomáš Tichý, 2024. "Evaluation of strategy portfolios," Computational Management Science, Springer, vol. 21(1), pages 1-27, June.
    28. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Papers 1910.13960, arXiv.org, revised Oct 2020.
    29. Llorens-Terrazas, Jordi & Brownlees, Christian, 2023. "Projected Dynamic Conditional Correlations," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1761-1776.
    30. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
    31. Jacobs, Heiko & Müller, Sebastian & Weber, Martin, 2014. "How should individual investors diversify? An empirical evaluation of alternative asset allocation policies," Journal of Financial Markets, Elsevier, vol. 19(C), pages 62-85.
    32. Olivier Ledoit & Michael Wolf, 2022. "Markowitz portfolios under transaction costs," ECON - Working Papers 420, Department of Economics - University of Zurich, revised Sep 2024.
    33. 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).
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  16. Olivier Ledoit & Michael Wolf, 2003. "Honey, I Shrunk the Sample Covariance Matrix," Working Papers 92, Barcelona School of Economics.

    Cited by:

    1. Daniel Espinoza & Eduardo Moreno, 2014. "A primal-dual aggregation algorithm for minimizing conditional value-at-risk in linear programs," Computational Optimization and Applications, Springer, vol. 59(3), pages 617-638, December.
    2. Loriana Pelizzon & Massimiliano Caporin, 2012. "Market volatility, optimal portfolios and naive asset allocations," Working Papers 2012_08, Department of Economics, University of Venice "Ca' Foscari".
    3. Michael Wolf, 2006. "Resampling vs. Shrinkage for Benchmarked Managers," IEW - Working Papers 263, Institute for Empirical Research in Economics - University of Zurich.
    4. Brandt, Michael W & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "Parametric Portfolio Policies: Exploiting Characteristics in the Cross Section of Equity Returns," University of California at Los Angeles, Anderson Graduate School of Management qt4ft420b6, Anderson Graduate School of Management, UCLA.
    5. Popovic, Gordana C. & Hui, Francis K.C. & Warton, David I., 2018. "A general algorithm for covariance modeling of discrete data," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 86-100.
    6. Yuanrong Wang & Tomaso Aste, 2021. "Dynamic Portfolio Optimization with Inverse Covariance Clustering," Papers 2112.15499, arXiv.org, revised Jan 2022.
    7. Soufiane Hayou, 2017. "On the overestimation of the largest eigenvalue of a covariance matrix," Papers 1708.03551, arXiv.org.
    8. Bessler, Wolfgang & Leonhardt, Alexander & Wolff, Dominik, 2016. "Analyzing hedging strategies for fixed income portfolios: A Bayesian approach for model selection," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 239-256.
    9. Perreault, Samuel & Duchesne, Thierry & Nešlehová, Johanna G., 2019. "Detection of block-exchangeable structure in large-scale correlation matrices," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 400-422.
    10. Caicedo-Llano, Juliana & Dionysopoulos, Thomas, 2008. "Market integration: A risk-budgeting guide for pure alpha investors," Journal of Multinational Financial Management, Elsevier, vol. 18(4), pages 313-327, October.
    11. Gopal K. Basak & Ravi Jagannathan & Tongshu Ma, 2004. "A Jackknife Estimator for Tracking Error Variance of Optimal Portfolios Constructed Using Estimated Inputs1," NBER Working Papers 10447, National Bureau of Economic Research, Inc.
    12. Paolo Andreini & Donato Ceci, 2019. "A Horse Race in High Dimensional Space," CEIS Research Paper 452, Tor Vergata University, CEIS, revised 14 Feb 2019.
    13. 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).
    14. Massimo Guidolin & Kai Wang, 2022. "The Empirical Performance of Option Implied Volatility Surface-Driven Optimal Portfolios," BAFFI CAREFIN Working Papers 22190, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

  17. Ledoit, Olivier & Santa-Clara, Pedro & Yan, Shu, 2002. "Relative Pricing of Options with Stochastic Volatility," University of California at Los Angeles, Anderson Graduate School of Management qt7jp8f42t, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. Aït-Sahalia, Yacine & Amengual, Dante & Manresa, Elena, 2015. "Market-based estimation of stochastic volatility models," Journal of Econometrics, Elsevier, vol. 187(2), pages 418-435.
    2. Aït-Sahalia, Yacine & Li, Chenxu & Li, Chen Xu, 2021. "Closed-form implied volatility surfaces for stochastic volatility models with jumps," Journal of Econometrics, Elsevier, vol. 222(1), pages 364-392.
    3. Alexey MEDVEDEV & Olivier SCAILLET, 2004. "A Simple Calibration Procedure of Stochastic Volatility Models with Jumps by Short Term Asymptotics," FAME Research Paper Series rp93, International Center for Financial Asset Management and Engineering.
    4. Tim Bollerslev & Hao Zhou, 2003. "Volatility puzzles: a unified framework for gauging return-volatility regressions," Finance and Economics Discussion Series 2003-40, Board of Governors of the Federal Reserve System (U.S.).
    5. Ai[diaeresis]t-Sahalia, Yacine & Kimmel, Robert, 2007. "Maximum likelihood estimation of stochastic volatility models," Journal of Financial Economics, Elsevier, vol. 83(2), pages 413-452, February.
    6. Martin Schweizer & Johannes Wissel, 2008. "Term Structures Of Implied Volatilities: Absence Of Arbitrage And Existence Results," Mathematical Finance, Wiley Blackwell, vol. 18(1), pages 77-114, January.
    7. Yuhyeon Bak & Cheolbeom Park, 2020. "Exchange Rate Predictability, Risk Premiums, and Predictive System," Discussion Paper Series 2006, Institute of Economic Research, Korea University.
    8. Carey, Alexander, 2008. "Natural volatility and option pricing," MPRA Paper 6709, University Library of Munich, Germany.
    9. Sebastian Herrmann & Johannes Muhle-Karbe, 2017. "Model Uncertainty, Recalibration, and the Emergence of Delta-Vega Hedging," Papers 1704.04524, arXiv.org.
    10. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2008. "High Idiosyncratic Volatility and Low Returns: International and Further U.S. Evidence," NBER Working Papers 13739, National Bureau of Economic Research, Inc.
    11. Moriggia, V. & Muzzioli, S. & Torricelli, C., 2009. "On the no-arbitrage condition in option implied trees," European Journal of Operational Research, Elsevier, vol. 193(1), pages 212-221, February.
    12. Yacine Ait-Sahalia & Robert Kimmel, 2004. "Maximum Likelihood Estimation of Stochastic Volatility Models," NBER Working Papers 10579, National Bureau of Economic Research, Inc.
    13. Carol Alexander & Leonardo Nogueira, 2004. "Stochastic Local Volatility," ICMA Centre Discussion Papers in Finance icma-dp2008-02, Henley Business School, University of Reading, revised Mar 2008.
    14. Sebastian Herrmann & Johannes Muhle-Karbe, 2017. "Model uncertainty, recalibration, and the emergence of delta–vega hedging," Finance and Stochastics, Springer, vol. 21(4), pages 873-930, October.
    15. Yu, Jialin, 2007. "Closed-form likelihood approximation and estimation of jump-diffusions with an application to the realignment risk of the Chinese Yuan," Journal of Econometrics, Elsevier, vol. 141(2), pages 1245-1280, December.
    16. Carol Alexander & Leonardo M. Nogueira, 2004. "Hedging with Stochastic and Local Volatility," ICMA Centre Discussion Papers in Finance icma-dp2004-10, Henley Business School, University of Reading, revised Dec 2004.
    17. Itkin, Andrey, 2015. "To sigmoid-based functional description of the volatility smile," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 264-291.
    18. Martin Schweizer & Johannes Wissel, 2008. "Arbitrage-free market models for option prices: the multi-strike case," Finance and Stochastics, Springer, vol. 12(4), pages 469-505, October.
    19. Bas Peeters, 2012. "Risk premiums in a simple market model for implied volatility," Quantitative Finance, Taylor & Francis Journals, vol. 13(5), pages 739-748, January.

  18. Olivier Ledoit & Michael Wolf, 2001. "Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size," Economics Working Papers 575, Department of Economics and Business, Universitat Pompeu Fabra.

    Cited by:

    1. Stanislav Anatolyev, 2009. "Inference in Regression Models with Many Regressors," Working Papers w0125, New Economic School (NES).
    2. Arnab Bhattacharjee & Jagjit Chadha & Qi Sun, 2010. "Productivity, Preferences and UIP Deviations in an Open Economy Business Cycle Model," Open Economies Review, Springer, vol. 21(3), pages 365-391, July.
    3. Olivier Ledoit & Sandrine P�ch�, 2009. "Eigenvectors of some large sample covariance matrices ensembles," IEW - Working Papers 407, Institute for Empirical Research in Economics - University of Zurich.

  19. Ledoit, Olivier & Wolf, Michael, 2000. "A well conditioned estimator for large dimensional covariance matrices," DES - Working Papers. Statistics and Econometrics. WS 10087, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Zhao Zhao & Olivier Ledoit & Hui Jiang, 2019. "Risk reduction and efficiency increase in large portfolios: leverage and shrinkage," ECON - Working Papers 328, Department of Economics - University of Zurich, revised Jan 2020.
    2. Hannart, Alexis & Naveau, Philippe, 2014. "Estimating high dimensional covariance matrices: A new look at the Gaussian conjugate framework," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 149-162.
    3. Tae-Hwy Lee & Ekaterina Seregina, 2020. "Optimal Portfolio Using Factor Graphical Lasso," Working Papers 202025, University of California at Riverside, Department of Economics.
    4. Stanislav Anatolyev, 2009. "Inference in Regression Models with Many Regressors," Working Papers w0125, New Economic School (NES).
    5. Taras Bodnar & Nestor Parolya & Erik Thors'en, 2022. "Two is better than one: Regularized shrinkage of large minimum variance portfolio," Papers 2202.06666, arXiv.org.
    6. Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Miffre, Joëlle, 2019. "A comprehensive appraisal of style-integration methods," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 134-150.
    7. Sancetta, Alessio, 2008. "Sample covariance shrinkage for high dimensional dependent data," Journal of Multivariate Analysis, Elsevier, vol. 99(5), pages 949-967, May.
    8. Lee, Sangin & Kim, Yongdai & Kwon, Sunghoon, 2012. "Quadratic approximation for nonconvex penalized estimations with a diverging number of parameters," Statistics & Probability Letters, Elsevier, vol. 82(9), pages 1710-1717.
    9. Ding, Wenliang & Shu, Lianjie & Gu, Xinhua, 2023. "A robust Glasso approach to portfolio selection in high dimensions," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 22-37.
    10. Bertrand Candelon & Christophe Hurlin & Sessi Tokpavi, 2012. "Sampling Error and Double Shrinkage Estimation of Minimum Variance Portfolios," Post-Print hal-01385835, HAL.
    11. Avagyan, Vahe & Nogales, Francisco J., 2015. "D-trace Precision Matrix Estimation Using Adaptive Lasso Penalties," DES - Working Papers. Statistics and Econometrics. WS 21775, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Badi H. Baltagi & Chihwa Kao & Bin Peng, 2014. ""On Testing for Sphericity with Non-normality in a Fixed Effects Panel Data Model," Center for Policy Research Working Papers 176, Center for Policy Research, Maxwell School, Syracuse University.
    13. Besson, Olivier & Abramovich, Yuri I., 2014. "Invariance properties of the likelihood ratio for covariance matrix estimation in some complex elliptically contoured distributions," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 237-246.
    14. Mishra, Anil V., 2016. "Foreign bias in Australian-domiciled mutual fund holdings," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 101-123.
    15. Guan-Hua Huang & Su-Mei Wang & Chung-Chu Hsu, 2011. "Optimization-Based Model Fitting for Latent Class and Latent Profile Analyses," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 584-611, October.
    16. Girolimetto, Daniele & Athanasopoulos, George & Di Fonzo, Tommaso & Hyndman, Rob J., 2024. "Cross-temporal probabilistic forecast reconciliation: Methodological and practical issues," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1134-1151.
    17. Stanislav Anatolyev & Nikolay Gospodinov, 2008. "Specification Testing in Models with Many Instruments," Working Papers w0124, New Economic School (NES).
    18. Wang, Xuanci & Zhang, Bin, 2024. "Target selection in shrinkage estimation of covariance matrix: A structural similarity approach," Statistics & Probability Letters, Elsevier, vol. 208(C).
    19. Dées, Stéphane & Pesaran, Hashem & Smith, Vanessa & Smith, Ron P., 2010. "Supply, demand and monetary policy shocks in a multi-country New Keynesian Model," Working Paper Series 1239, European Central Bank.
    20. Papp, Gábor & Caccioli, Fabio & Kondor, Imre, 2019. "Bias-variance trade-off in portfolio optimization under expected shortfall with ℓ 2 regularization," LSE Research Online Documents on Economics 100294, London School of Economics and Political Science, LSE Library.
    21. Marco Avellaneda & Brian Healy & Andrew Papanicolaou & George Papanicolaou, 2020. "PCA for Implied Volatility Surfaces," Papers 2002.00085, arXiv.org.
    22. Yuki Ikeda & Tatsuya Kubokawa & Muni S. Srivastava, 2015. "Comparison of Linear Shrinkage Estimators of a Large Covariance Matrix in Normal and Non-normal Distributions," CIRJE F-Series CIRJE-F-970, CIRJE, Faculty of Economics, University of Tokyo.
    23. Imre Kondor & G'abor Papp & Fabio Caccioli, 2017. "Analytic approach to variance optimization under an $\ell_1$ constraint," Papers 1709.08755, arXiv.org, revised Jul 2018.
    24. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    25. McDowell, Shaun, 2018. "An empirical evaluation of estimation error reduction strategies applied to international diversification," Journal of Multinational Financial Management, Elsevier, vol. 44(C), pages 1-13.
    26. Craig, Ben & Giuzio, Margherita & Paterlini, Sandra, 2020. "The effect of possible EU diversification requirements on the risk of banks’ sovereign bond portfolios," Working Paper Series 2384, European Central Bank.
    27. Huang, Zhenzhen & Wei, Pengyu & Weng, Chengguo, 2024. "Tail mean-variance portfolio selection with estimation risk," Insurance: Mathematics and Economics, Elsevier, vol. 116(C), pages 218-234.
    28. Ghaemi Asl, Mahdi & Rashidi, Muhammad Mahdi & Tavakkoli, Hamid Raza & Rezgui, Hichem, 2024. "Does Islamic investing modify portfolio performance? Time-varying optimization strategies for conventional and Shariah energy-ESG-utilities portfolio," The Quarterly Review of Economics and Finance, Elsevier, vol. 94(C), pages 37-57.
    29. Hongxin Zhao & Lingchen Kong & Hou-Duo Qi, 2021. "Optimal portfolio selections via $$\ell _{1, 2}$$ ℓ 1 , 2 -norm regularization," Computational Optimization and Applications, Springer, vol. 80(3), pages 853-881, December.
    30. Olivier Ledoit & Michael Wolf, 2003. "Honey, I Shrunk the Sample Covariance Matrix," Working Papers 92, Barcelona School of Economics.
    31. Plachel, Lukas, 2019. "A unified model for regularized and robust portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
    32. Fays, Boris & Papageorgiou, Nicolas & Lambert, Marie, 2021. "Risk optimizations on basis portfolios: The role of sorting," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 136-163.
    33. Chavez-Bedoya, Luis & Rosales, Francisco, 2022. "Orthogonal portfolios to assess estimation risk," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 906-937.
    34. Badi H. Baltagi & Qu Feng & Chihwa Kao, 2009. "Testing for Sphericity in a Fixed Effects Panel Data Model (Revised July 2009)," Center for Policy Research Working Papers 112, Center for Policy Research, Maxwell School, Syracuse University.
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    119. Adrian Grosanu & Paula Ramona Rachisan, 2008. "The Implementation Of Profit Centres Inside An Economic Entity," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    120. Hafner, Christian M. & Herwartz, Helmut, 2023. "Asymmetric volatility impulse response functions," Economics Letters, Elsevier, vol. 222(C).

  22. Bernardo, Antonio & Ledoit, Olivier, 1999. "Approximate Arbitrage," University of California at Los Angeles, Anderson Graduate School of Management qt5dj834hk, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. Carr, Peter & Geman, Helyette & Madan, Dilip B., 2001. "Pricing and hedging in incomplete markets," Journal of Financial Economics, Elsevier, vol. 62(1), pages 131-167, October.
    2. Taylor, Alan M. & Jordà , Òscar, 2009. "The Carry Trade and Fundamentals: Nothing to Fear But FEER Itself," CEPR Discussion Papers 7568, C.E.P.R. Discussion Papers.
    3. Huang, Yu-Lieh & Tsai, Jeffrey Tzuhao & Yang, Sharon S. & Cheng, Hung-Wen, 2014. "Price bounds of mortality-linked security in incomplete insurance market," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 30-39.

  23. Johansen, Anders & Ledoit, Olivier & Sornette, Didier, 1998. "Crashes at Critical Points," University of California at Los Angeles, Anderson Graduate School of Management qt2s77r0rk, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. Li Lin & Didier Sornette, 2023. "The inverse Cox-Ingersoll-Ross process for parsimonious financial price modeling," Papers 2302.11423, arXiv.org, revised Jun 2023.
    2. Leiss, Matthias & Nax, Heinrich H. & Sornette, Didier, 2015. "Super-exponential growth expectations and the global financial crisis," Journal of Economic Dynamics and Control, Elsevier, vol. 55(C), pages 1-13.
    3. Ide, Kayo & Sornette, Didier, 2002. "Oscillatory finite-time singularities in finance, population and rupture," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 307(1), pages 63-106.
    4. Li, Chong, 2017. "Log-periodic view on critical dates of the Chinese stock market bubbles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 305-311.
    5. Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    6. Zhou, Wei-Xing & Sornette, Didier, 2009. "A case study of speculative financial bubbles in the South African stock market 2003–2006," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 869-880.
    7. Zhang, Yue-Jun & Yao, Ting, 2016. "Interpreting the movement of oil prices: Driven by fundamentals or bubbles?," Economic Modelling, Elsevier, vol. 55(C), pages 226-240.
    8. Terry Bossomaier & Lionel Barnett & Adam Steen & Mike Harré & Steve d'Alessandro & Rod Duncan, 2018. "Information flow around stock market collapse," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 45-58, November.
    9. Vladimir Filimonov & Didier Sornette, 2011. "A Stable and Robust Calibration Scheme of the Log-Periodic Power Law Model," Papers 1108.0099, arXiv.org, revised Jun 2013.
    10. Fantazzini, Dean & Nigmatullin, Erik & Sukhanovskaya, Vera & Ivliev, Sergey, 2016. "Everything you always wanted to know about bitcoin modelling but were afraid to ask," MPRA Paper 71946, University Library of Munich, Germany, revised 2016.
    11. Ruiqiang Song & Min Shu & Wei Zhu, 2021. "The 2020 Global Stock Market Crash: Endogenous or Exogenous?," Papers 2101.00327, arXiv.org.
    12. Wong, Jian Cheng & Lian, Heng & Cheong, Siew Ann, 2009. "Detecting macroeconomic phases in the Dow Jones Industrial Average time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(21), pages 4635-4645.
    13. Papastamatiou, Konstantinos & Karakasidis, Theodoros, 2022. "Bubble detection in Greek Stock Market: A DS-LPPLS model approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    14. Rendón, Stephanie, 2013. "Detección de caídas en mercados financieros mediante análisis multifractal (exponentes locales y puntuales de Hölder): Índice accionario IPC y tipo de cambio USD/MXN [Stock crack detection using mu," MPRA Paper 47699, University Library of Munich, Germany, revised 19 May 2013.
    15. Qun Zhang & Qunzhi Zhang & Didier Sornette, 2016. "Early Warning Signals of Financial Crises with Multi-Scale Quantile Regressions of Log-Periodic Power Law Singularities," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-43, November.
    16. Renee van Eyden & Rangan Gupta & Joshua Nielsen & Elie Bouri, 2022. "Investor Sentiment and Multi-Scale Positive and Negative Stock Market Bubbles in a Panel of G7 Countries," Working Papers 202256, University of Pretoria, Department of Economics.
    17. A. Corcos & J. -P. Eckmann & A. Malaspinas & Y. Malevergne & D. Sornette, 2001. "Imitation and contrarian behavior: hyperbolic bubbles, crashes and chaos," Papers cond-mat/0109410, arXiv.org.
    18. Daniel T. Pele, 2012. "An Lppl Algorithm For Estimating The Critical Time Of A Stock Market Bubble," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 1(2), pages 14-22, DECEMBER.
    19. Zhou, Wei-Xing & Sornette, Didier, 2004. "Antibubble and prediction of China's stock market and real-estate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 337(1), pages 243-268.
    20. Andreas D. Huesler & Didier Sornette & C. H. Hommes, 2012. "Super-Exponential Bubbles in Lab Experiments: Evidence for Anchoring Over-Optimistic Expectations on Price," Swiss Finance Institute Research Paper Series 12-20, Swiss Finance Institute.
    21. Bikramaditya Ghosh & Spyros Papathanasiou & Georgios Pergeris, 2022. "Did cryptocurrencies exhibit log‐periodic power law signature during the second wave of COVID‐19?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(3), November.
    22. Rangan Gupta & Joshua Nielsen & Christian Pierdzioch, 2023. "Stock Market Bubbles and the Realized Volatility of Oil Price Returns," Working Papers 202325, University of Pretoria, Department of Economics.
    23. Andersen, J.V. & Sornette, D., 2004. "Fearless versus fearful speculative financial bubbles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 337(3), pages 565-585.
    24. Juan M. Romero & Ilse B. Zubieta-Mart'inez, 2016. "Relativistic Quantum Finance," Papers 1604.01447, arXiv.org.
    25. Wei-Xing Zhou & Didier Sornette, 2003. "Nonparametric Analyses Of Log-Periodic Precursors To Financial Crashes," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 14(08), pages 1107-1125.
    26. Guilherme Demos & Didier Sornette, 2017. "Lagrange regularisation approach to compare nested data sets and determine objectively financial bubbles' inceptions," Papers 1707.07162, arXiv.org.
    27. Balcilar, Mehmet & Katzke, Nico & Gupta, Rangan, 2017. "Date-stamping US housing market explosivity," Economics Discussion Papers 2017-44, Kiel Institute for the World Economy (IfW Kiel).
    28. da Fonseca, Eder Lucio & Ferreira, Fernando F. & Muruganandam, Paulsamy & Cerdeira, Hilda A., 2013. "Identifying financial crises in real time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1386-1392.
    29. IKEDA Yuichi & YOSHIKAWA Hiroshi, 2018. "Macroprudential Modeling Based on Spin Dynamics in a Supply Chain Network," Discussion papers 18045, Research Institute of Economy, Trade and Industry (RIETI).
    30. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    31. Spencer Wheatley & Didier Sornette & Tobias Huber & Max Reppen & Robert N. Gantner, 2018. "Are Bitcoin Bubbles Predictable? Combining a Generalized Metcalfe's Law and the LPPLS Model," Papers 1803.05663, arXiv.org.
    32. Wanfeng Yan & Edgar van Tuyll van Serooskerken, 2015. "Forecasting Financial Extremes: A Network Degree Measure of Super-Exponential Growth," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-15, September.
    33. A. Johansen & D. Sornette, 2002. "Endogenous versus Exogenous Crashes in Financial Markets," Papers cond-mat/0210509, arXiv.org.
    34. Song, Ruiqiang & Shu, Min & Zhu, Wei, 2022. "The 2020 global stock market crash: Endogenous or exogenous?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    35. Sabri Boubaker & Zhenya Liu & Yaosong Zhan, 2022. "Risk management for crude oil futures: an optimal stopping-timing approach," Annals of Operations Research, Springer, vol. 313(1), pages 9-27, June.
    36. Dong-Rui Chen & Chuang Liu & Yi-Cheng Zhang & Zi-Ke Zhang, 2019. "Predicting Financial Extremes Based on Weighted Visual Graph of Major Stock Indices," Complexity, Hindawi, vol. 2019, pages 1-17, October.
    37. Jerome L Kreuser & Didier Sornette, 2017. "Super-Exponential RE Bubble Model with Efficient Crashes," Swiss Finance Institute Research Paper Series 17-33, Swiss Finance Institute.
    38. Li Lin & Didier Sornette, 2018. "“Speculative Influence Network” during financial bubbles: application to Chinese stock markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(2), pages 385-431, July.
    39. Bikramaditya Ghosh & Spyros Papathanasiou & Nikita Ramchandani & Dimitrios Kenourgios, 2021. "Diagnosis and Prediction of IIGPS’ Countries Bubble Crashes during BREXIT," Mathematics, MDPI, vol. 9(9), pages 1-14, April.
    40. Shu-Peng Chen & Ling-Yun He, 2013. "Bubble Formation and Heterogeneity of Traders: A Multi-Agent Perspective," Computational Economics, Springer;Society for Computational Economics, vol. 42(3), pages 267-289, October.
    41. Yuichi Ikeda, 2020. "An Interacting Agent Model of Economic Crisis," Papers 2001.11843, arXiv.org.
    42. W. -X. Zhou & D. Sornette, 2003. "Causal Slaving of the U.S. Treasury Bond Yield Antibubble by the Stock Market Antibubble of August 2000," Papers cond-mat/0312658, arXiv.org.
    43. Zhi-Qiang Jiang & Wei-Xing Zhou & Didier Sornette & Ryan Woodard & Ken Bastiaensen & Peter Cauwels, 2009. "Bubble Diagnosis and Prediction of the 2005-2007 and 2008-2009 Chinese stock market bubbles," Papers 0909.1007, arXiv.org, revised Oct 2009.
    44. Fry, John, 2012. "Exogenous and endogenous crashes as phase transitions in complex financial systems," MPRA Paper 36202, University Library of Munich, Germany.
    45. Yan, Wanfeng & Woodard, Ryan & Sornette, Didier, 2012. "Diagnosis and prediction of rebounds in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1361-1380.
    46. Mariani, M.C. & Bezdek, P. & Serpa, L. & Florescu, I., 2011. "Ising type models applied to Geophysics and high frequency market data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4396-4402.
    47. Sornette, Didier & Woodard, Ryan & Zhou, Wei-Xing, 2009. "The 2006–2008 oil bubble: Evidence of speculation, and prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1571-1576.
    48. Johansen, Anders, 2003. "Characterization of large price variations in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 157-166.
    49. Sornette, Didier & Woodard, Ryan & Yan, Wanfeng & Zhou, Wei-Xing, 2013. "Clarifications to questions and criticisms on the Johansen–Ledoit–Sornette financial bubble model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4417-4428.
    50. Giulio Cifarelli and Paolo Paesani, 2021. "Navigating the Oil Bubble: A Non-linear Heterogeneous-agent Dynamic Model of Futures Oil Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    51. Mariani, M.C. & Florescu, I. & SenGupta, I. & Beccar Varela, M.P. & Bezdek, P. & Serpa, L., 2013. "Lévy models and scale invariance properties applied to Geophysics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 824-839.
    52. Zhou, Wei & Huang, Yang & Chen, Jin, 2018. "The bubble and anti-bubble risk resistance analysis on the metal futures in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 947-957.
    53. Wanfeng YAN & Ryan WOODARD & Didier SORNETTE, 2010. "Diagnosis and Prediction of Market Rebounds in Financial Markets," Swiss Finance Institute Research Paper Series 10-15, Swiss Finance Institute.
    54. Didier Sornette & Wei-Xing Zhou, 2005. "Importance of Positive Feedbacks and Over-confidence in a Self-Fulfilling Ising Model of Financial Markets," Papers cond-mat/0503607, arXiv.org, revised Mar 2005.
    55. Misha Perepelitsa, 2021. "Investing in crypto: speculative bubbles and cyclic stochastic price pumps," Papers 2111.11315, arXiv.org, revised Oct 2022.
    56. Wosnitza, Jan Henrik & Leker, Jens, 2014. "Why credit risk markets are predestined for exhibiting log-periodic power law structures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 427-449.
    57. Daniel Traian Pele & Miruna Mazurencu-Marinescu & Peter Nijkamp, 2013. "Herding Behaviour, Bubbles and Log Periodic Power Laws in Illiquid Stock Markets. A Case Study on the Bucharest Stock Exchange," Tinbergen Institute Discussion Papers 13-109/VIII, Tinbergen Institute.
    58. Neto, David, 2021. "Are Google searches making the Bitcoin market run amok? A tail event analysis," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    59. Fry, J. M., 2010. "Bubbles and crashes in finance: A phase transition from random to deterministic behaviour in prices," MPRA Paper 24778, University Library of Munich, Germany.
    60. Charles-Cadogan, G., 2021. "Market Instability, Investor Sentiment, And Probability Judgment Error in Index Option Prices," CRETA Online Discussion Paper Series 71, Centre for Research in Economic Theory and its Applications CRETA.
    61. Jang, Hanwool & Song, Yena & Ahn, Kwangwon, 2020. "Can government stabilize the housing market? The evidence from South Korea," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    62. Zhou, Wei-Xing & Sornette, Didier, 2003. "2000–2003 real estate bubble in the UK but not in the USA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 329(1), pages 249-263.
    63. Misha Perepelitsa & Ilya Timofeyev, 2022. "Self-sustained price bubbles driven by digital currency innovations and adaptive market behavior," SN Business & Economics, Springer, vol. 2(3), pages 1-15, March.
    64. John Fry, 2014. "Bubbles, shocks and elementary technical trading strategies," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 87(1), pages 1-13, January.
    65. Baruník, Jozef & Kukacka, Jiri, 2014. "Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility," FinMaP-Working Papers 15, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    66. Maximilian Brauers & Matthias Thomas & Joachim Zietz, 2014. "Are There Rational Bubbles in REITs? New Evidence from a Complex Systems Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 49(2), pages 165-184, August.
    67. Sanjay Rajagopal & Patrick Hays, 2012. "Return Persistence in the Indian Real Estate Market," International Real Estate Review, Global Social Science Institute, vol. 15(3), pages 283-305.
    68. Zhou, Wei-Xing & Sornette, Didier, 2003. "Evidence of a worldwide stock market log-periodic anti-bubble since mid-2000," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 330(3), pages 543-583.
    69. Cajueiro, Daniel O. & Tabak, Benjamin M. & Werneck, Filipe K., 2009. "Can we predict crashes? The case of the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1603-1609.
    70. Tarlie, Martin B. & Sakoulis, Georgios & Henriksson, Roy, 2022. "Stock market bubbles and anti-bubbles," International Review of Financial Analysis, Elsevier, vol. 81(C).
    71. Fang, Ming & Lin, Yizhou & Chang, Chiu-Lan, 2023. "Positive and negative price bubbles of Chinese agricultural commodity futures," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 456-471.
    72. Veglio, A. & Marsili, M., 2007. "Stochastic analysis of an agent-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 631-636.
    73. B. M. Roehner & D. Sornette, 2000. ""Thermometers" of Speculative Frenzy," Papers cond-mat/0001353, arXiv.org.
    74. Sornette, D., 2002. "“Slimming” of power-law tails by increasing market returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 309(3), pages 403-418.
    75. Riza Demirer & David Gabauer & Rangan Gupta & Joshua Nielsen, 2023. "Gold-to-Platinum Price Ratio and the Predictability of Bubbles in Financial Markets," Working Papers 202317, University of Pretoria, Department of Economics.
    76. Leiss, Matthias & Nax, Heinrich H. & Sornette, Didier, 2015. "Super-exponential growth expectations and the global financial crisis," LSE Research Online Documents on Economics 65434, London School of Economics and Political Science, LSE Library.
    77. Li Lin & Didier Sornette, 2009. "Diagnostics of Rational Expectation Financial Bubbles with Stochastic Mean-Reverting Termination Times," Papers 0911.1921, arXiv.org.
    78. Graf v. Bothmer, Hans-Christian & Meister, Christian, 2003. "Predicting critical crashes? A new restriction for the free variables," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 320(C), pages 539-547.
    79. Didier SORNETTE, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based Models," Swiss Finance Institute Research Paper Series 14-25, Swiss Finance Institute.
    80. Andreas Pyka & Uwe Cantner & Alfred Greiner & Thomas Kuhn (ed.), 2009. "Recent Advances in Neo-Schumpeterian Economics," Books, Edward Elgar Publishing, number 12982.
    81. Filimonov, Vladimir & Sornette, Didier, 2015. "Power law scaling and “Dragon-Kings” in distributions of intraday financial drawdowns," Chaos, Solitons & Fractals, Elsevier, vol. 74(C), pages 27-45.
    82. D. Sornette & W. -X. Zhou, 2003. "Evidence of Fueling of the 2000 New Economy Bubble by Foreign Capital Inflow: Implications for the Future of the US Economy and its Stock Market," Papers cond-mat/0306496, arXiv.org.
    83. Shihai Dong & Yandong Wang & Yanyan Gu & Shiwei Shao & Hui Liu & Shanmei Wu & Mengmeng Li, 2020. "Predicting the turning points of housing prices by combining the financial model with genetic algorithm," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-20, April.
    84. Shu, Min & Zhu, Wei, 2020. "Real-time prediction of Bitcoin bubble crashes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    85. Gupta, Rangan & Nel, Jacobus & Nielsen, Joshua, 2023. "US monetary policy and BRICS stock market bubbles," Finance Research Letters, Elsevier, vol. 51(C).
    86. Wosnitza, Jan Henrik & Denz, Cornelia, 2013. "Liquidity crisis detection: An application of log-periodic power law structures to default prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3666-3681.
    87. Zhong, Li-Xin & Xu, Wen-Juan & Chen, Rong-Da & Zhong, Chen-Yang & Qiu, Tian & Ren, Fei & He, Yun-Xing, 2018. "Self-reinforcing feedback loop in financial markets with coupling of market impact and momentum traders," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 301-310.
    88. Wosnitza, Jan Henrik & Leker, Jens, 2014. "Can log-periodic power law structures arise from random fluctuations?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 228-250.
    89. Fantazzini, Dean, 2016. "The Oil Price Crash in 2014/15: Was There a (Negative) Financial Bubble?," MPRA Paper 72094, University Library of Munich, Germany.
    90. Negrea, Bogdan, 2014. "A statistical measure of financial crises magnitude," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 397(C), pages 54-75.
    91. Shu, Min & Song, Ruiqiang & Zhu, Wei, 2021. "The ‘COVID’ crash of the 2020 U.S. Stock market," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    92. Mark Setterfield & Bill Gibson, 2013. "Real and financial crises: A multi-agent approach," Working Papers 1309, Trinity College, Department of Economics, revised Jul 2014.
    93. Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019. "Metcalfe's law and herding behaviour in the cryptocurrencies market," Economics Discussion Papers 2019-16, Kiel Institute for the World Economy (IfW Kiel).
    94. Marcel Ausloos, 2013. "Econophysics: Comments on a Few Applications, Successes, Methods and Models," IIM Kozhikode Society & Management Review, , vol. 2(2), pages 101-115, July.
    95. Brée, David S. & Joseph, Nathan Lael, 2013. "Testing for financial crashes using the Log Periodic Power Law model," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 287-297.
    96. Kensuke Ito & Kyohei Shibano & Gento Mogi, 2022. "Bubble Prediction of Non-Fungible Tokens (NFTs): An Empirical Investigation," Papers 2203.12587, arXiv.org, revised Jun 2022.
    97. Caraiani, Petre & Gupta, Rangan & Nel, Jacobus & Nielsen, Joshua, 2023. "Monetary policy and bubbles in G7 economies using a panel VAR approach: Implications for sustainable development," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 133-155.
    98. Demos, G. & Sornette, D., 2019. "Comparing nested data sets and objectively determining financial bubbles’ inceptions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 661-675.
    99. Li Lin & Didier Sornette, 2015. ""Speculative Influence Network" during financial bubbles: application to Chinese Stock Markets," Papers 1510.08162, arXiv.org.
    100. Habtemicael, Semere & SenGupta, Indranil, 2014. "Ornstein–Uhlenbeck processes for geophysical data analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 147-156.
    101. D. Sornette & R. Woodard, "undated". "Financial Bubbles, Real Estate bubbles, Derivative Bubbles, and the Financial and Economic Crisis," Working Papers CCSS-09-003, ETH Zurich, Chair of Systems Design.
    102. Romain Bocher, 2022. "The Intersubjective Markets Hypothesis," Journal of Interdisciplinary Economics, , vol. 34(1), pages 35-50, January.
    103. Damian Smug & Peter Ashwin & Didier Sornette, 2018. "Predicting financial market crashes using ghost singularities," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-20, March.
    104. Filimonov, V. & Sornette, D., 2013. "A stable and robust calibration scheme of the log-periodic power law model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3698-3707.
    105. Yang, Jinyu & Dong, Dayong & Liang, Chao & Cao, Yang, 2024. "Monetary policy uncertainty and the price bubbles in energy markets," Energy Economics, Elsevier, vol. 133(C).
    106. C. Vladimir Rodríguez-Caballero & Mauricio Villanueva-Domínguez, 2022. "Predicting cryptocurrency crash dates," Empirical Economics, Springer, vol. 63(6), pages 2855-2873, December.
    107. Christopher Lynch & Benjamin Mestel, 2017. "Logistic Model For Stock Market Bubbles And Anti-Bubbles," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(06), pages 1-24, September.
    108. Kwangwon Ahn & Hanwool Jang & Jinu Kim & Inug Ryu, 2024. "COVID-19 and REITs Crash: Predictability and Market Conditions," Computational Economics, Springer;Society for Computational Economics, vol. 63(3), pages 1159-1172, March.
    109. Sergio Luis Náñez Alonso & Javier Jorge-Vázquez & Miguel Ángel Echarte Fernández & David Sanz-Bas, 2024. "Bitcoin’s bubbly behaviors: does it resemble other financial bubbles of the past?," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    110. Jennifer Jhun & Patricia Palacios & James Owen Weatherall, 2017. "Market Crashes as Critical Phenomena? Explanation, Idealization, and Universality in Econophysics," Papers 1704.02392, arXiv.org.
    111. Bikramaditya Ghosh & Spyros Papathanasiou & Vandita Dar & Konstantinos Gravas, 2022. "Bubble in Carbon Credits during COVID-19: Financial Instability or Positive Impact (“Minsky” or “Social”)?," JRFM, MDPI, vol. 15(8), pages 1-16, August.
    112. Ardila-Alvarez, Diego & Forro, Zalan & Sornette, Didier, 2021. "The acceleration effect and Gamma factor in asset pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    113. Fry, J. M., 2010. "Gaussian and non-Gaussian models for financial bubbles via econophysics," MPRA Paper 27307, University Library of Munich, Germany.
    114. Eder Lucio Fonseca & Fernando F. Ferreira & Paulsamy Muruganandam & Hilda A. Cerdeira, 2012. "Identifying financial crises in real time," Papers 1204.3136, arXiv.org, revised Nov 2012.
    115. Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
    116. Wei-Xing Zhou & Didier Sornette, 2005. "Fundamental Factors versus Herding in the 2000-2005 US Stock Market and Prediction," Papers physics/0505079, arXiv.org.
    117. Kong, Xiaolin & Ma, Chaoqun & Ren, Yi-Shuai & Baltas, Konstantinos & Narayan, Seema, 2024. "A comparative analysis of the price explosiveness in Bitcoin and forked coins," Finance Research Letters, Elsevier, vol. 61(C).
    118. Kristoffer Pons Bertelsen, 2019. "Comparing Tests for Identification of Bubbles," CREATES Research Papers 2019-16, Department of Economics and Business Economics, Aarhus University.
    119. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    120. J. V. Andersen & D Sornette, 2003. "Fearless versus Fearful Speculative Financial Bubbles," Papers cond-mat/0311089, arXiv.org.
    121. John M. Fry, 2009. "Statistical modelling of financial crashes: Rapid growth, illusion of certainty and contagion," EERI Research Paper Series EERI_RP_2009_10, Economics and Econometrics Research Institute (EERI), Brussels.
    122. Misha Perepelitsa, 2021. "Psychological dimension of adaptive trading in cryptocurrency markets," Papers 2109.12166, arXiv.org.
    123. Wanfeng Yan & Ryan Woodard & Didier Sornette, 2010. "Leverage Bubble," Papers 1011.0458, arXiv.org, revised Nov 2010.
    124. Renee van Eyden & Rangan Gupta & Xin Sheng & Joshua Nielsen, 2023. "Predicting Multi-Scale Positive and Negative Stock Market Bubbles in a Panel of G7 Countries: The Role of Oil Price Uncertainty," Working Papers 202332, University of Pretoria, Department of Economics.
    125. David Gabauer & Rangan Gupta & Sayar Karmakar & Joshua Nielsen, 2022. "Stock Market Bubbles and the Forecastability of Gold Returns (and Volatility)," Working Papers 202228, University of Pretoria, Department of Economics.
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    See citations under working paper version above.
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    Cited by:

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    2. IKEDA Shin Suke, 2017. "Illiquidity in the Japan Electric Power Exchange," Discussion papers 17122, Research Institute of Economy, Trade and Industry (RIETI).
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    4. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2008. "A multivariate integer count hurdle model: theory and application to exchange rate dynamics," Studies in Empirical Economics, in: Luc Bauwens & Winfried Pohlmeier & David Veredas (ed.), High Frequency Financial Econometrics, pages 31-48, Springer.
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    6. Kramer, Walter & Runde, Ralf, 1997. "Chaos and the compass rose," Economics Letters, Elsevier, vol. 54(2), pages 113-118, February.
    7. Amilon, Henrik, 2003. "GARCH estimation and discrete stock prices: an application to low-priced Australian stocks," Economics Letters, Elsevier, vol. 81(2), pages 215-222, November.
    8. George D. Cashman & David M. Harrison & Hainan Sheng, 2021. "Option Trading and REIT Returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 49(1), pages 332-389, March.
    9. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2011. "An inflated multivariate integer count hurdle model: an application to bid and ask quote dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(4), pages 669-707, June.
    10. Ledoit, Olivier & Wolf, Michael, 2000. "A well conditioned estimator for large dimensional covariance matrices," DES - Working Papers. Statistics and Econometrics. WS 10087, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Small Michael & Tse Chi K., 2003. "Determinism in Financial Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(3), pages 1-31, October.
    12. Wang, Eliza & Hudson, Robert & Keasey, Kevin, 2000. "Tick size and the compass rose: further insights," Economics Letters, Elsevier, vol. 68(2), pages 119-125, August.
    13. Ikeda, Shin S., 2019. "Illiquidity in the Japan electric power exchange," Journal of Commodity Markets, Elsevier, vol. 14(C), pages 16-39.
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    16. Shin S. Ikeda, 2015. "Illiquidity in the Japanese Day-Ahead Electricity Market," GRIPS Discussion Papers 15-04, National Graduate Institute for Policy Studies.
    17. Wang, Huaiqing & Wang, Chen, 2002. "Visibility of the compass rose in financial asset returns: A quantitative study," Journal of Banking & Finance, Elsevier, vol. 26(6), pages 1099-1111, June.
    18. An-Sing Chen, 1997. "The square compass rose: the evidence from Taiwan," Journal of Multinational Financial Management, Elsevier, vol. 7(2), pages 127-144, June.
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    21. Ng, Wing Lon, 2006. "Overreaction and multiple tail dependence at the high-frequency level: The copula rose," SFB 649 Discussion Papers 2006-086, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    22. Lanius, Vivian & Gather, Ursula, 2010. "Robust online signal extraction from multivariate time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 966-975, April.
    23. Lanius, Vivian & Gather, Ursula, 2007. "Robust online signal extraction from multivariate time series," Technical Reports 2007,38, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    24. Shin S. Ikeda, 2013. "An Empirical Market Microstructure Analysis of the Implied Spread Cost in the Japanese Day-Ahead Electricity Market," GRIPS Discussion Papers 12-22, National Graduate Institute for Policy Studies.
    25. Henrik Amilon, 2002. "A Score Test for Discreteness in GARCH Models," Research Paper Series 76, Quantitative Finance Research Centre, University of Technology, Sydney.

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