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Alessio Sancetta

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First Name:Alessio
Middle Name:
Last Name:Sancetta
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RePEc Short-ID:psa66
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http://www.sancetta.googlepages.com/

Research output

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Jump to: Working papers Articles Editorship

Working papers

  1. Sancetta, A., 2007. "Nearest Neighbor Conditional Estimation for Harris Recurrent Markov Chains," Cambridge Working Papers in Economics 0735, Faculty of Economics, University of Cambridge.
  2. Sancetta, A., 2007. "Universality of Bayesian Predictions," Cambridge Working Papers in Economics 0755, Faculty of Economics, University of Cambridge.
  3. Sancetta, A., 2007. "Online Forecast Combination for Dependent Heterogeneous Data," Cambridge Working Papers in Economics 0718, Faculty of Economics, University of Cambridge.
  4. Sancetta, A., 2006. "Sample Covariance Shrinkage for High Dimensional Dependent Data," Cambridge Working Papers in Economics 0637, Faculty of Economics, University of Cambridge.
  5. Sancetta, A. & Nikanrova, A., 2005. "Forecasting and Prequential Validation for Time Varying Meta-Elliptical Distributions with a Study of Commodity Futures Prices," Cambridge Working Papers in Economics 0516, Faculty of Economics, University of Cambridge.
  6. Sancetta, A., 2005. "Copula Based Monte Carlo Integration in Financial Problems," Cambridge Working Papers in Economics 0506, Faculty of Economics, University of Cambridge.
  7. Sancetta, A., 2005. "Forecasting Distributions with Experts Advice," Cambridge Working Papers in Economics 0517, Faculty of Economics, University of Cambridge.
  8. Sancetta, A. & Satchell, S.E., 2004. "Cost of Capital and Regulator’s Preferences: Investigation into a new method of estimating regulatory bias," Cambridge Working Papers in Economics 0441, Faculty of Economics, University of Cambridge.
  9. Sancetta, A. & Satchell, S.E., 2003. "Changing Correlation and Portfolio Diversification Failure in the Presence of Large Market Losses," Cambridge Working Papers in Economics 0319, Faculty of Economics, University of Cambridge.
  10. Sancetta, A., 2003. "Nonparametric Estimation of Multivariate Distributions with Given Marginals," Cambridge Working Papers in Economics 0320, Faculty of Economics, University of Cambridge.
  11. A. Sancetta & Satchell, S.E., 2002. "New Test Statistics for Market Timing with Application to Emerging markets," Cambridge Working Papers in Economics 0222, Faculty of Economics, University of Cambridge.
  12. A. Sancetta & Satchell, S.E., 2001. "Bernstein Approximations to the Copula Function and Portfolio Optimization," Cambridge Working Papers in Economics 0105, Faculty of Economics, University of Cambridge.

Articles

  1. Sancetta, Alessio, 2013. "Weak conditions for shrinking multivariate nonparametric density estimators," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 285-300.
  2. Battey, Heather & Sancetta, Alessio, 2013. "Conditional estimation for dependent functional data," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 1-17.
  3. Alessio Sancetta, 2010. "Bootstrap model selection for possibly dependent and heterogeneous data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(3), pages 515-546, June.
  4. Sancetta, Alessio, 2010. "Recursive Forecast Combination For Dependent Heterogeneous Data," Econometric Theory, Cambridge University Press, vol. 26(2), pages 598-631, April.
  5. Sancetta Alessio & Nikandrova Arina, 2009. "Forecasting and Prequential Validation for Time Varying Meta-Elliptical Distributions," Journal of Time Series Econometrics, De Gruyter, vol. 1(2), pages 1-41, December.
  6. Sancetta, Alessio, 2009. "Nearest neighbor conditional estimation for Harris recurrent Markov chains," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2224-2236, November.
  7. Linton, Oliver & Sancetta, Alessio, 2009. "Consistent estimation of a general nonparametric regression function in time series," Journal of Econometrics, Elsevier, vol. 152(1), pages 70-78, September.
  8. Alessio Sancetta, 2009. "Strong law of large numbers for pairwise positive quadrant dependent random variables," Statistical Inference for Stochastic Processes, Springer, vol. 12(1), pages 55-64, February.
  9. Sancetta, Alessio, 2008. "Sample covariance shrinkage for high dimensional dependent data," Journal of Multivariate Analysis, Elsevier, vol. 99(5), pages 949-967, May.
  10. Alessio Sancetta & Steve E. Satchell, 2007. "Changing Correlation and Equity Portfolio Diversification Failure for Linear Factor Models during Market Declines," Applied Mathematical Finance, Taylor & Francis Journals, vol. 14(3), pages 227-242.
  11. Sancetta, Alessio, 2007. "Nonparametric estimation of distributions with given marginals via Bernstein-Kantorovich polynomials: L1 and pointwise convergence theory," Journal of Multivariate Analysis, Elsevier, vol. 98(7), pages 1376-1390, August.
  12. Sancetta, Alessio, 2007. "Online forecast combinations of distributions: Worst case bounds," Journal of Econometrics, Elsevier, vol. 141(2), pages 621-651, December.
  13. Sancetta, Alessio, 2005. "Distance between nonidentically weakly dependent random vectors and Gaussian random vectors under the bounded Lipschitz metric," Statistics & Probability Letters, Elsevier, vol. 75(3), pages 158-168, December.
  14. Alessio Sancetta & Stephen Satchell, 2005. "New test statistics for market timing with applications to emerging markets hedge funds," The European Journal of Finance, Taylor & Francis Journals, vol. 11(5), pages 419-443.
  15. Sancetta, Alessio & Satchell, Stephen, 2004. "The Bernstein Copula And Its Applications To Modeling And Approximations Of Multivariate Distributions," Econometric Theory, Cambridge University Press, vol. 20(3), pages 535-562, June.
  16. Alessio Sancetta & Steve Satchell, 2004. "Calculating hedge fund risk: the draw down and the maximum draw down," Applied Mathematical Finance, Taylor & Francis Journals, vol. 11(3), pages 259-282.
  17. Alessio Sancetta & Steve Satchell, 2002. "Molten lava meets market languor," Quantitative Finance, Taylor & Francis Journals, vol. 2(6), pages 405-405.

Editorship

  1. Econometrics Journal, Royal Economic Society.

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.

Working papers

  1. Sancetta, A., 2007. "Nearest Neighbor Conditional Estimation for Harris Recurrent Markov Chains," Cambridge Working Papers in Economics 0735, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Linton, Oliver & Sancetta, Alessio, 2009. "Consistent estimation of a general nonparametric regression function in time series," Journal of Econometrics, Elsevier, vol. 152(1), pages 70-78, September.
    2. Battey, Heather & Sancetta, Alessio, 2013. "Conditional estimation for dependent functional data," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 1-17.
    3. Nengxiang Ling & Germán Aneiros & Philippe Vieu, 2020. "kNN estimation in functional partial linear modeling," Statistical Papers, Springer, vol. 61(1), pages 423-444, February.

  2. Sancetta, A., 2007. "Online Forecast Combination for Dependent Heterogeneous Data," Cambridge Working Papers in Economics 0718, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Assenmacher-Wesche, Katrin & Pesaran, M. Hashem, 2007. "Assessing Forecast Uncertainties in a VECX Model for Switzerland: An Exercise in Forecast Combination across Models and Observation Windows," IZA Discussion Papers 3071, Institute of Labor Economics (IZA).

  3. Sancetta, A., 2006. "Sample Covariance Shrinkage for High Dimensional Dependent Data," Cambridge Working Papers in Economics 0637, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Steland, Ansgar & von Sachs, Rainer, 2018. "Asymptotics for high-dimensional covariance matrices and quadratic forms with applications to the trace functional and shrinkage," Stochastic Processes and their Applications, Elsevier, vol. 128(8), pages 2816-2855.
    2. 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.
    3. Bernardini, Emmanuela & Cubadda, Gianluca, 2015. "Macroeconomic forecasting and structural analysis through regularized reduced-rank regression," International Journal of Forecasting, Elsevier, vol. 31(3), pages 682-691.
    4. Ansgar Steland, 2018. "Shrinkage for covariance estimation: asymptotics, confidence intervals, bounds and applications in sensor monitoring and finance," Statistical Papers, Springer, vol. 59(4), pages 1441-1462, December.
    5. Mark Fiecas & Jürgen Franke & Rainer von Sachs & Joseph Tadjuidje Kamgaing, 2017. "Shrinkage Estimation for Multivariate Hidden Markov Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 424-435, January.
    6. Gianluca Cubadda & Barbara Guardabascio, 2017. "Representation, Estimation and Forecasting of the Multivariate Index-Augmented Autoregressive Model," CEIS Research Paper 397, Tor Vergata University, CEIS, revised 13 Jul 2018.
    7. Steland, Ansgar, 2020. "Testing and estimating change-points in the covariance matrix of a high-dimensional time series," Journal of Multivariate Analysis, Elsevier, vol. 177(C).
    8. Sancetta, Alessio, 2013. "Weak conditions for shrinking multivariate nonparametric density estimators," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 285-300.
    9. Fiecas , Mark & Franke, Jurgen & von Sachs, Rainer & Tadjuidje , Joseph, 2012. "Shrinkage Estimation for Multivariate Hidden Markov Mixture Models," LIDAM Discussion Papers ISBA 2012016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    10. Monika Bours & Ansgar Steland, 2021. "Large‐sample approximations and change testing for high‐dimensional covariance matrices of multivariate linear time series and factor models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 610-654, June.
    11. Steland, Ansgar & von Sachs, Rainer, 2016. "Asymptotics for High–Dimensional Covariance Matrices and Quadratic Forms with Applications to the Trace Functional and Shrinkage," LIDAM Discussion Papers ISBA 2016038, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  4. Sancetta, A. & Satchell, S.E., 2004. "Cost of Capital and Regulator’s Preferences: Investigation into a new method of estimating regulatory bias," Cambridge Working Papers in Economics 0441, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.

  5. Sancetta, A., 2003. "Nonparametric Estimation of Multivariate Distributions with Given Marginals," Cambridge Working Papers in Economics 0320, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Matthew Hurd & Mark Salmon & Christoph Schleicher, 2007. "Using copulas to construct bivariate foreign exchange distributions with an application to the sterling exchange rate index," Bank of England working papers 334, Bank of England.
    2. Hall, Peter & Neumeyer, Natalie, 2005. "Estimating a bivariate density when there are extra data on one or both components," Technical Reports 2005,28, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

  6. A. Sancetta & Satchell, S.E., 2001. "Bernstein Approximations to the Copula Function and Portfolio Optimization," Cambridge Working Papers in Economics 0105, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Szego, Giorgio, 2002. "Measures of risk," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1253-1272, July.
    2. Sancetta, A., 2005. "Copula Based Monte Carlo Integration in Financial Problems," Cambridge Working Papers in Economics 0506, Faculty of Economics, University of Cambridge.
    3. Fortin, Ines & Kuzmics, Christoph, 2002. "Tail-Dependence in Stock-Return Pairs," Economics Series 126, Institute for Advanced Studies.
    4. Alessio Sancetta & Steve E. Satchell, 2007. "Changing Correlation and Equity Portfolio Diversification Failure for Linear Factor Models during Market Declines," Applied Mathematical Finance, Taylor & Francis Journals, vol. 14(3), pages 227-242.
    5. Paula V. Tofoli & Flavio A. Ziegelmann & Osvaldo Candido, 2017. "A Comparison Study of Copula Models for Europea Financial Index Returns," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(10), pages 155-178, October.
    6. Romera, Rosario & Molanes, Elisa M., 2008. "Copulas in finance and insurance," DES - Working Papers. Statistics and Econometrics. WS ws086321, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Chadwick, Meltem Gulenay, 2019. "Dependence of the “Fragile Five” and “Troubled Ten” emerging market financial systems on US monetary policy and monetary policy uncertainty," Research in International Business and Finance, Elsevier, vol. 49(C), pages 251-268.

Articles

  1. Sancetta, Alessio, 2010. "Recursive Forecast Combination For Dependent Heterogeneous Data," Econometric Theory, Cambridge University Press, vol. 26(2), pages 598-631, April.

    Cited by:

    1. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    2. Gang Cheng & Sicong Wang & Yuhong Yang, 2015. "Forecast Combination under Heavy-Tailed Errors," Econometrics, MDPI, vol. 3(4), pages 1-28, November.
    3. Wei, Xiaoqiao & Yang, Yuhong, 2012. "Robust forecast combinations," Journal of Econometrics, Elsevier, vol. 166(2), pages 224-236.
    4. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    5. Yongchen Zhao, 2021. "The robustness of forecast combination in unstable environments: a Monte Carlo study of advanced algorithms," Empirical Economics, Springer, vol. 61(1), pages 173-199, July.
    6. Matsypura, Dmytro & Thompson, Ryan & Vasnev, Andrey L., 2018. "Optimal selection of expert forecasts with integer programming," Omega, Elsevier, vol. 78(C), pages 165-175.
    7. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Sep 2016.

  2. Sancetta Alessio & Nikandrova Arina, 2009. "Forecasting and Prequential Validation for Time Varying Meta-Elliptical Distributions," Journal of Time Series Econometrics, De Gruyter, vol. 1(2), pages 1-41, December.

    Cited by:

    1. Derumigny, A. & Fermanian, J.-D., 2022. "Identifiability and estimation of meta-elliptical copula generators," Journal of Multivariate Analysis, Elsevier, vol. 190(C).

  3. Sancetta, Alessio, 2009. "Nearest neighbor conditional estimation for Harris recurrent Markov chains," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2224-2236, November.
    See citations under working paper version above.
  4. Linton, Oliver & Sancetta, Alessio, 2009. "Consistent estimation of a general nonparametric regression function in time series," Journal of Econometrics, Elsevier, vol. 152(1), pages 70-78, September.

    Cited by:

    1. Seok Young Hong & Oliver Linton, 2016. "Asymptotic properties of a Nadaraya-Watson type estimator for regression functions of in?finite order," CeMMAP working papers CWP53/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Hong, Seok Young & Linton, Oliver, 2020. "Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff," Journal of Econometrics, Elsevier, vol. 219(2), pages 389-424.
    3. Degui Li & Zudi Lu & Oliver Linton, 2011. "Local Linear Fitting Under Near Epoch Dependence: Uniform consistency with Convergence Rates," Monash Econometrics and Business Statistics Working Papers 16/11, Monash University, Department of Econometrics and Business Statistics.
    4. Degui Li & Oliver Linton & Zudi Lu, 2012. "A flexible semiparametric model for time series," CeMMAP working papers CWP28/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Degui Li & Oliver Linton & Zudi Lu, 2010. "Loch Linear Fitting under Near Epoch Dependence: Uniform Consistency with Convergence Rate," STICERD - Econometrics Paper Series 549, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    6. Seok Young Hong & Oliver Linton, 2016. "Asymptotic properties of a Nadaraya-Watson type estimator for regression functions of in finite order," CeMMAP working papers 53/16, Institute for Fiscal Studies.
    7. Battey, Heather & Sancetta, Alessio, 2013. "Conditional estimation for dependent functional data," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 1-17.
    8. Li, Degui & Linton, Oliver & Lu, Zudi, 2015. "A flexible semiparametric forecasting model for time series," Journal of Econometrics, Elsevier, vol. 187(1), pages 345-357.

  5. Sancetta, Alessio, 2008. "Sample covariance shrinkage for high dimensional dependent data," Journal of Multivariate Analysis, Elsevier, vol. 99(5), pages 949-967, May.
    See citations under working paper version above.
  6. Alessio Sancetta & Steve E. Satchell, 2007. "Changing Correlation and Equity Portfolio Diversification Failure for Linear Factor Models during Market Declines," Applied Mathematical Finance, Taylor & Francis Journals, vol. 14(3), pages 227-242.

    Cited by:

    1. Kwon, Oh Kang & Satchell, Stephen, 2018. "The distribution of cross sectional momentum returns," Journal of Economic Dynamics and Control, Elsevier, vol. 94(C), pages 225-241.
    2. Christoffersen, Peter & Langlois, Hugues, 2013. "The Joint Dynamics of Equity Market Factors," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(5), pages 1371-1404, October.
    3. Dominik Wied & Matthias Arnold & Nicolai Bissantz & Daniel Ziggel, 2013. "Über die Anwendbarkeit eines neuen Fluktuationstests für Korrelationen auf Finanzzeitreihen," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 6(3), pages 87-103, March.
    4. Florian Stark & Sven Otto, 2020. "Testing and Dating Structural Changes in Copula-based Dependence Measures," Papers 2011.05036, arXiv.org.
    5. Ma, Rong & Zhang, Yin & Li, Honggang, 2017. "Traders’ behavioral coupling and market phase transition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 618-627.

  7. Sancetta, Alessio, 2007. "Nonparametric estimation of distributions with given marginals via Bernstein-Kantorovich polynomials: L1 and pointwise convergence theory," Journal of Multivariate Analysis, Elsevier, vol. 98(7), pages 1376-1390, August.

    Cited by:

    1. Ouimet, Frédéric, 2021. "Asymptotic properties of Bernstein estimators on the simplex," Journal of Multivariate Analysis, Elsevier, vol. 185(C).
    2. Alireza Ahmadabadi & Burcu Hudaverdi Ucer, 2017. "Bivariate nonparametric estimation of the Pickands dependence function using Bernstein copula with kernel regression approach," Computational Statistics, Springer, vol. 32(4), pages 1515-1532, December.
    3. Tavin, Bertrand, 2015. "Detection of arbitrage in a market with multi-asset derivatives and known risk-neutral marginals," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 158-178.

  8. Sancetta, Alessio, 2007. "Online forecast combinations of distributions: Worst case bounds," Journal of Econometrics, Elsevier, vol. 141(2), pages 621-651, December.

    Cited by:

    1. Wei, Xiaoqiao & Yang, Yuhong, 2012. "Robust forecast combinations," Journal of Econometrics, Elsevier, vol. 166(2), pages 224-236.
    2. Yongchen Zhao, 2021. "The robustness of forecast combination in unstable environments: a Monte Carlo study of advanced algorithms," Empirical Economics, Springer, vol. 61(1), pages 173-199, July.
    3. Sánchez, Ismael, 2008. "Adaptive combination of forecasts with application to wind energy," International Journal of Forecasting, Elsevier, vol. 24(4), pages 679-693.
    4. Sancetta, A., 2007. "Online Forecast Combination for Dependent Heterogeneous Data," Cambridge Working Papers in Economics 0718, Faculty of Economics, University of Cambridge.
    5. Guo, Nan & Wang, Fang & Yang, Jingping, 2017. "Remarks on composite Bernstein copula and its application to credit risk analysis," Insurance: Mathematics and Economics, Elsevier, vol. 77(C), pages 38-48.

  9. Alessio Sancetta & Stephen Satchell, 2005. "New test statistics for market timing with applications to emerging markets hedge funds," The European Journal of Finance, Taylor & Francis Journals, vol. 11(5), pages 419-443.

    Cited by:

    1. Eling, Martin & Faust, Roger, 2010. "The performance of hedge funds and mutual funds in emerging markets," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1993-2009, August.
    2. Giannikis, Dimitrios & Vrontos, Ioannis D., 2011. "A Bayesian approach to detecting nonlinear risk exposures in hedge fund strategies," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1399-1414, June.
    3. Zhang, Jing & Zhang, Wei & Li, Youwei & Feng, Xu, 2021. "The Role of Hedge Funds in the Asset Pricing: Evidence from China," MPRA Paper 105377, University Library of Munich, Germany.

  10. Sancetta, Alessio & Satchell, Stephen, 2004. "The Bernstein Copula And Its Applications To Modeling And Approximations Of Multivariate Distributions," Econometric Theory, Cambridge University Press, vol. 20(3), pages 535-562, June.

    Cited by:

    1. Göran Kauermann & Christian Schellhase & David Ruppert, 2013. "Flexible Copula Density Estimation with Penalized Hierarchical B-splines," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(4), pages 685-705, December.
    2. Luciana Dalla Valle & Maria Elena De Giuli & Claudia Tarantola & Claudio Manelli, 2014. "Default Probability Estimation via Pair Copula Constructions," Papers 1405.1309, arXiv.org, revised Aug 2015.
    3. Masuhr Andreas & Trede Mark, 2020. "Bayesian estimation of generalized partition of unity copulas," Dependence Modeling, De Gruyter, vol. 8(1), pages 119-131, January.
    4. Ouimet, Frédéric, 2021. "Asymptotic properties of Bernstein estimators on the simplex," Journal of Multivariate Analysis, Elsevier, vol. 185(C).
    5. Taamouti, Abderrahim & Bouezmarni, Taoufik & El Ghouch, Anouar, 2014. "Nonparametric estimation and inference for conditional density based Granger causality measures," Journal of Econometrics, Elsevier, vol. 180(2), pages 251-264.
    6. Santiago Pereda Fernández, 2019. "Identification and estimation of triangular models with a binary treatment," Temi di discussione (Economic working papers) 1210, Bank of Italy, Economic Research and International Relations Area.
    7. Plischke, Elmar & Borgonovo, Emanuele, 2019. "Copula theory and probabilistic sensitivity analysis: Is there a connection?," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1046-1059.
    8. Dietmar Pfeifer & Olena Ragulina, 2020. "Adaptive Bernstein Copulas and Risk Management," Mathematics, MDPI, vol. 8(12), pages 1-22, December.
    9. Manuel Arellano & Stéphane Bonhomme, 2017. "Quantile Selection Models With an Application to Understanding Changes in Wage Inequality," Econometrica, Econometric Society, vol. 85, pages 1-28, January.
    10. Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear panel data methods for dynamic heterogeneous agent models," CeMMAP working papers 51/16, Institute for Fiscal Studies.
    11. Steven Abrams & Paul Janssen & Jan Swanepoel & Noël Veraverbeke, 2020. "Nonparametric estimation of the cross ratio function," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(3), pages 771-801, June.
    12. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2010. "Out-of-sample comparison of copula specifications in multivariate density forecasts," Post-Print hal-00732675, HAL.
    13. Matthew Hurd & Mark Salmon & Christoph Schleicher, 2007. "Using copulas to construct bivariate foreign exchange distributions with an application to the sterling exchange rate index," Bank of England working papers 334, Bank of England.
    14. Eric C. K. Cheung & Oscar Peralta & Jae-Kyung Woo, 2021. "Multivariate matrix-exponential affine mixtures and their applications in risk theory," Papers 2201.11122, arXiv.org.
    15. BOUEZMARNI, Taoufik & ROMBOUTS, Jeroen V.K., 2007. "Semiparametric multivariate density estimation for positive data using copulas," LIDAM Discussion Papers CORE 2007054, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Ackerer Damien & Vatter Thibault, 2017. "Dependent defaults and losses with factor copula models," Dependence Modeling, De Gruyter, vol. 5(1), pages 375-399, December.
    17. Hofert, Marius & Prasad, Avinash & Zhu, Mu, 2022. "Multivariate time-series modeling with generative neural networks," Econometrics and Statistics, Elsevier, vol. 23(C), pages 147-164.
    18. Kiriliouk, Anna & Segers, Johan & Tafakori, Laleh, 2017. "An estimator of the stable tail dependence function based on the empirical beta copula," LIDAM Discussion Papers ISBA 2017028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    19. Lu Lu & Sujit Ghosh, 2023. "Nonparametric Estimation of Multivariate Copula Using Empirical Bayes Methods," Mathematics, MDPI, vol. 11(20), pages 1-22, October.
    20. Bouezmarni, Taoufik & Rombouts, Jeroen V.K. & Taamouti, Abderrahim, 2010. "Asymptotic properties of the Bernstein density copula estimator for [alpha]-mixing data," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 1-10, January.
    21. Dou, Xiaoling & Kuriki, Satoshi & Lin, Gwo Dong & Richards, Donald, 2016. "EM algorithms for estimating the Bernstein copula," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 228-245.
    22. Dimitrova, Dimitrina S. & Kaishev, Vladimir K. & Penev, Spiridon I., 2008. "GeD spline estimation of multivariate Archimedean copulas," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3570-3582, March.
    23. Berghaus, Betina & Segers, Johan, 2018. "Weak convergence of the weighted empirical beta copula process," Journal of Multivariate Analysis, Elsevier, vol. 166(C), pages 266-281.
    24. Coqueret, Guillaume, 2014. "Second order risk aggregation with the Bernstein copula," Insurance: Mathematics and Economics, Elsevier, vol. 58(C), pages 150-158.
    25. Shahid Latif & Slobodan P. Simonovic, 2022. "Nonparametric Approach to Copula Estimation in Compounding The Joint Impact of Storm Surge and Rainfall Events in Coastal Flood Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5599-5632, November.
    26. Leonidas Tsiaras, 2010. "Dynamic Models of Exchange Rate Dependence Using Option Prices and Historical Returns," CREATES Research Papers 2010-35, Department of Economics and Business Economics, Aarhus University.
    27. Kiriliouk, Anna & Segers, Johan & Tafakori, Laleh, 2018. "An estimator of the stable tail dependence function based on the empirical beta copula," LIDAM Discussion Papers ISBA 2018029, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    28. Segers, Johan & Sibuya, Masaaki & Tsukahara, Hideatsu, 2017. "The empirical beta copula," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 35-51.
    29. Eddie Anderson & Artem Prokhorov & Yajing Zhu, 2020. "A Simple Estimator of Two‐Dimensional Copulas, with Applications," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1375-1412, December.
    30. Blier-Wong, Christopher & Cossette, Hélène & Marceau, Etienne, 2023. "Risk aggregation with FGM copulas," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 102-120.
    31. Charles Fontaine & Ron D. Frostig & Hernando Ombao, 2020. "Modeling dependence via copula of functionals of Fourier coefficients," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(4), pages 1125-1144, December.
    32. Junker, Robert R. & Griessenberger, Florian & Trutschnig, Wolfgang, 2021. "Estimating scale-invariant directed dependence of bivariate distributions," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
    33. Taoufik Bouezmarni & Jeroen Rombouts & Abderrahim Taamouti, 2009. "A Nonparametric Copula Based Test for Conditional Independence with Applications to Granger Causality," CIRANO Working Papers 2009s-28, CIRANO.
    34. Sebastian Kiwitt & Natalie Neumeyer, 2013. "A note on testing independence by a copula-based order selection approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(1), pages 62-82, March.
    35. Fouad Marri & Khouzeima Moutanabbir, 2021. "Risk aggregation and capital allocation using a new generalized Archimedean copula," Papers 2103.10989, arXiv.org.
    36. Nadarajah, Saralees, 2015. "Expansions for bivariate copulas," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 77-84.
    37. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2022. "Copula-based estimation of health concentration curves with an application to COVID-19," CIRANO Working Papers 2022s-07, CIRANO.
    38. Marri, Fouad & Moutanabbir, Khouzeima, 2022. "Risk aggregation and capital allocation using a new generalized Archimedean copula," Insurance: Mathematics and Economics, Elsevier, vol. 102(C), pages 75-90.
    39. Ćmiel, Bogdan & Ledwina, Teresa, 2020. "Validation of association," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 55-67.
    40. Baker, Rose, 2008. "An order-statistics-based method for constructing multivariate distributions with fixed marginals," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2312-2327, November.
    41. Berghaus, Betina & Segers, Johan, 2017. "Weak convergence of the weighted empirical beta copula process," LIDAM Discussion Papers ISBA 2017015, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    42. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    43. Santiago Pereda-Fernández, 2021. "Copula-Based Random Effects Models for Clustered Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 575-588, March.
    44. Wu, Ximing, 2010. "Exponential Series Estimator of multivariate densities," Journal of Econometrics, Elsevier, vol. 156(2), pages 354-366, June.
    45. Yichen Gao & Yu Zhang & Ximing Wu, 2015. "Penalized exponential series estimation of copula densities with an application to intergenerational dependence of body mass index," Empirical Economics, Springer, vol. 48(1), pages 61-81, February.
    46. Alireza Ahmadabadi & Burcu Hudaverdi Ucer, 2017. "Bivariate nonparametric estimation of the Pickands dependence function using Bernstein copula with kernel regression approach," Computational Statistics, Springer, vol. 32(4), pages 1515-1532, December.
    47. Nagler, Thomas & Czado, Claudia, 2016. "Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas," Journal of Multivariate Analysis, Elsevier, vol. 151(C), pages 69-89.
    48. Santiago Pereda-Fern'andez, 2024. "Fast Algorithms for Quantile Regression with Selection," Papers 2402.16693, arXiv.org.
    49. Durante, Fabrizio & Sánchez, Juan Fernández, 2012. "On the approximation of copulas via shuffles of Min," Statistics & Probability Letters, Elsevier, vol. 82(10), pages 1761-1767.
    50. Segers, Johan & Sibuya, Masaaki & Tsukahara, Hideatsu, 2016. "The Empirical Beta Copula," LIDAM Discussion Papers ISBA 2016032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    51. Hall, Peter & Neumeyer, Natalie, 2005. "Estimating a bivariate density when there are extra data on one or both components," Technical Reports 2005,28, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    52. Janssen, Paul & Swanepoel, Jan & Veraverbeke, Noël, 2017. "Smooth copula-based estimation of the conditional density function with a single covariate," Journal of Multivariate Analysis, Elsevier, vol. 159(C), pages 39-48.
    53. BOUEZMARNI, Taoufik & ROMBOUTS, Jeroen V.K. & TAAMOUTI, Abderrahim, 2008. "Asymptotic properties of the Bernstein density copula for dependent data," LIDAM Discussion Papers CORE 2008045, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    54. Damien Ackerer & Thibault Vatter, 2016. "Dependent Defaults and Losses with Factor Copula Models," Papers 1610.03050, arXiv.org, revised Jan 2018.
    55. Jens Stange & Taras Bodnar & Thorsten Dickhaus, 2015. "Uncertainty quantification for the family-wise error rate in multivariate copula models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(3), pages 281-310, July.
    56. Kenichiro Shiraya & Tomohisa Yamakami, 2023. "Constructing Copulas Using Corrected Hermite Polynomial Expansion for Estimating Cross Foreign Exchange Volatility," Papers 2301.10044, arXiv.org.
    57. Woo, Jae-Kyung & Cheung, Eric C.K., 2013. "A note on discounted compound renewal sums under dependency," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 170-179.
    58. Swanepoel, J.W.H. & Allison, J.S., 2013. "Some new results on the empirical copula estimator with applications," Statistics & Probability Letters, Elsevier, vol. 83(7), pages 1731-1739.
    59. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2023. "Copula-based estimation of health inequality measures with an application to COVID-19," University of East Anglia School of Economics Working Paper Series 2023-01, School of Economics, University of East Anglia, Norwich, UK..
    60. Bouezmarni, Taoufik & El Ghouch, Anouar & Taamouti, Abderrahim, 2013. "Bernstein estimator for unbounded copula densities," LIDAM Reprints ISBA 2013047, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    61. Tavin, Bertrand, 2015. "Detection of arbitrage in a market with multi-asset derivatives and known risk-neutral marginals," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 158-178.
    62. Dietmar Pfeifer & Doreen Strassburger & Joerg Philipps, 2020. "Modelling and simulation of dependence structures in nonlife insurance with Bernstein copulas," Papers 2010.15709, arXiv.org.
    63. Shiraya, Kenichiro & Yamakami, Tomohisa, 2024. "Constructing copulas using corrected Hermite polynomial expansion for estimating cross foreign exchange volatility," European Journal of Operational Research, Elsevier, vol. 314(3), pages 1195-1214.
    64. Janssen, Paul & Swanepoel, Jan & Veraverbeke, Noël, 2014. "A note on the asymptotic behavior of the Bernstein estimator of the copula density," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 480-487.
    65. Masuhr Andreas & Trede Mark, 2020. "Bayesian estimation of generalized partition of unity copulas," Dependence Modeling, De Gruyter, vol. 8(1), pages 119-131, January.
    66. Bouezmarni, Taoufik & El Ghouch, Anouar, 2012. "Nonparametric estimation and inference for Granger causality measures," UC3M Working papers. Economics 14150, Universidad Carlos III de Madrid. Departamento de Economía.
    67. Fouad Marri & Khouzeima Moutanabbir, 2021. "Risk aggregation and capital allocation using a new generalized Archimedean copula," Working Papers hal-03169291, HAL.
    68. Durante, Fabrizio & Fernández Sánchez, Juan & Sempi, Carlo, 2013. "Multivariate patchwork copulas: A unified approach with applications to partial comonotonicity," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 897-905.
    69. Masayuki Hirukawa & Irina Murtazashvili & Artem Prokhorov, 2022. "Uniform convergence rates for nonparametric estimators smoothed by the beta kernel," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1353-1382, September.
    70. Martin Burda & Artem Prokhorov, 2012. "Copula Based Factorization in Bayesian Multivariate Infinite Mixture Models," Working Papers 12012, Concordia University, Department of Economics.
    71. Kojadinovic, Ivan & Stemikovskaya, Kristina, 2019. "Subsampling (weighted smooth) empirical copula processes," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 704-723.
    72. Bouezmarni, Taoufik & El Ghouch, Anouar & Taamouti, Abderrahim, 2011. "Bernstein Estimator for Unbounded Density Copula," LIDAM Discussion Papers ISBA 2011027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    73. Romera, Rosario & Molanes, Elisa M., 2008. "Copulas in finance and insurance," DES - Working Papers. Statistics and Econometrics. WS ws086321, Universidad Carlos III de Madrid. Departamento de Estadística.
    74. Dietmar Pfeifer & Olena Ragulina, 2020. "Adaptive Bernstein Copulas and Risk Management," Papers 2011.00909, arXiv.org, revised Mar 2021.
    75. Mirza Nazmul Hasan & Roel Braekers, 2022. "Modelling the association in bivariate survival data by using a Bernstein copula," Computational Statistics, Springer, vol. 37(2), pages 781-815, April.
    76. Serge B. Provost & Yishan Zang, 2024. "Nonparametric Copula Density Estimation Methodologies," Mathematics, MDPI, vol. 12(3), pages 1-35, January.
    77. Guo, Nan & Wang, Fang & Yang, Jingping, 2017. "Remarks on composite Bernstein copula and its application to credit risk analysis," Insurance: Mathematics and Economics, Elsevier, vol. 77(C), pages 38-48.
    78. Nagler Thomas & Schellhase Christian & Czado Claudia, 2017. "Nonparametric estimation of simplified vine copula models: comparison of methods," Dependence Modeling, De Gruyter, vol. 5(1), pages 99-120, January.
    79. Qu, Leming & Yin, Wotao, 2012. "Copula density estimation by total variation penalized likelihood with linear equality constraints," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 384-398.
    80. Chadwick, Meltem Gulenay, 2019. "Dependence of the “Fragile Five” and “Troubled Ten” emerging market financial systems on US monetary policy and monetary policy uncertainty," Research in International Business and Finance, Elsevier, vol. 49(C), pages 251-268.
    81. Amjad, Muhammad & Akbar, Muhammad & Ullah, Hamd, 2022. "A copula-based approach for creating an index of micronutrient intakes at household level in Pakistan," Economics & Human Biology, Elsevier, vol. 46(C).
    82. Diers, Dorothea & Eling, Martin & Marek, Sebastian D., 2012. "Dependence modeling in non-life insurance using the Bernstein copula," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 430-436.
    83. Cheung, Eric C.K. & Peralta, Oscar & Woo, Jae-Kyung, 2022. "Multivariate matrix-exponential affine mixtures and their applications in risk theory," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 364-389.
    84. Sancetta, Alessio, 2007. "Nonparametric estimation of distributions with given marginals via Bernstein-Kantorovich polynomials: L1 and pointwise convergence theory," Journal of Multivariate Analysis, Elsevier, vol. 98(7), pages 1376-1390, August.
    85. Fan, Yanqin & Shi, Xuetao & Tao, Jing, 2023. "Partial identification and inference in moment models with incomplete data," Journal of Econometrics, Elsevier, vol. 235(2), pages 418-443.
    86. Oh, Rosy & Jeong, Himchan & Ahn, Jae Youn & Valdez, Emiliano A., 2021. "A multi-year microlevel collective risk model," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 309-328.
    87. Hansjörg Albrecher & Mogens Bladt & Jorge Yslas, 2022. "Fitting inhomogeneous phase‐type distributions to data: the univariate and the multivariate case," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(1), pages 44-77, March.
    88. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    89. Gregor Wei{ss} & Marcus Scheffer, 2012. "Smooth Nonparametric Bernstein Vine Copulas," Papers 1210.2043, arXiv.org.

  11. Alessio Sancetta & Steve Satchell, 2004. "Calculating hedge fund risk: the draw down and the maximum draw down," Applied Mathematical Finance, Taylor & Francis Journals, vol. 11(3), pages 259-282.

    Cited by:

    1. 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.
    2. Sager, Michael & Taylor, Mark P., 2014. "Generating currency trading rules from the term structure of forward foreign exchange premia," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 230-250.
    3. J-H Steffi Yang, 2004. "The Markovian Dynamics of "Smart Money"," Econometric Society 2004 Far Eastern Meetings 797, Econometric Society.

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NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 11 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (8) 2002-10-08 2003-04-04 2005-02-01 2005-05-07 2006-05-20 2007-04-28 2007-08-14 2007-11-24. Author is listed
  2. NEP-FIN: Finance (3) 2001-06-14 2003-03-25 2005-02-01
  3. NEP-FOR: Forecasting (3) 2007-04-28 2007-08-14 2007-11-24
  4. NEP-ETS: Econometric Time Series (2) 2007-04-28 2007-11-24
  5. NEP-FMK: Financial Markets (2) 2002-10-08 2003-03-25
  6. NEP-ACC: Accounting and Auditing (1) 2004-07-26
  7. NEP-CBA: Central Banking (1) 2007-11-24
  8. NEP-CMP: Computational Economics (1) 2005-02-01
  9. NEP-REG: Regulation (1) 2004-07-26
  10. NEP-RMG: Risk Management (1) 2002-10-08

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