IDEAS home Printed from https://ideas.repec.org/f/c/psc913.html
   My authors  Follow this author

Rafael Schmidt

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. Schmidt, Rafael & Schmieder, Christian, 2007. "Modelling dynamic portfolio risk using risk drivers of elliptical processes," Discussion Paper Series 2: Banking and Financial Studies 2007,07, Deutsche Bundesbank.

    Cited by:

    1. Hashorva, Enkelejd, 2009. "Asymptotics for Kotz Type III elliptical distributions," Statistics & Probability Letters, Elsevier, vol. 79(7), pages 927-935, April.
    2. Hashorva, Enkelejd, 2008. "Tail asymptotic results for elliptical distributions," Insurance: Mathematics and Economics, Elsevier, vol. 43(1), pages 158-164, August.
    3. Emiliano Valdez, 2011. "Comments on: Inference in multivariate Archimedean copula models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(2), pages 257-262, August.

Articles

  1. Jeremy Penzer & Friedrich Schmid & Rafael Schmidt, 2012. "Measuring large comovements in financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 12(7), pages 1037-1049, November.

    Cited by:

    1. Bing-Yue Liu & Qiang Ji & Ying Fan, 2017. "A new time-varying optimal copula model identifying the dependence across markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(3), pages 437-453, March.

  2. Grothe, Oliver & Schmidt, Rafael, 2010. "Scaling of Lévy–Student processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(7), pages 1455-1463.

    Cited by:

    1. Wang, Xiao-Tian & Li, Zhe & Zhuang, Le, 2017. "European option pricing under the Student’s t noise with jumps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 848-858.
    2. Till Massing, 2019. "What is the best Lévy model for stock indices? A comparative study with a view to time consistency," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(3), pages 277-344, September.
    3. Till Massing, 2018. "Simulation of Student–Lévy processes using series representations," Computational Statistics, Springer, vol. 33(4), pages 1649-1685, December.
    4. Vinogradov, Dmitry V., 2010. "Cumulant approach of arbitrary truncated Levy flight," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5794-5800.
    5. López Martín, María del Mar & García, Catalina García & García Pérez, José, 2012. "Treatment of kurtosis in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(5), pages 2032-2045.

  3. Schmidt, Rafael & Schmieder, Christian, 2009. "Modelling dynamic portfolio risk using risk drivers of elliptical processes," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 229-244, April.
    See citations under working paper version above.
  4. Bernhard Babel & Eckart Bomsdorf & Rafael Schmidt, 2008. "Forecasting German mortality using panel data procedures," Journal of Population Economics, Springer;European Society for Population Economics, vol. 21(3), pages 541-555, July.

    Cited by:

    1. Christian Dudel, 2009. "The Demographic Dilemma: Fertility, Female Labor Force Participation and Future Growth in Germany 2007-2060," SOEPpapers on Multidisciplinary Panel Data Research 158, DIW Berlin, The German Socio-Economic Panel (SOEP).
    2. Patrizio Vanella & Moritz Heß & Christina B. Wilke, 2020. "A probabilistic projection of beneficiaries of long-term care insurance in Germany by severity of disability," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(3), pages 943-974, June.
    3. Hendrik Hansen, 2013. "The forecasting performance of mortality models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(1), pages 11-31, January.
    4. Valentin Vogt & Jörg Althammer, 2016. "Linking Retirement Age to Life Expectancy in a Bismarckian System - The Case of Germany," National Institute of Economic and Social Research (NIESR) Discussion Papers 465, National Institute of Economic and Social Research.
    5. Jan Valentin Vogt, 2017. "Alternating Migration Flows and their Age-Structure Effects on the Long-Term Sustainability of the German Statutory Pension Insurance," EcoMod2017 10369, EcoMod.
    6. Eckart Bomsdorf, 2010. "Rückgang der Bevölkerung – Zunahme der Pflegefälle Divergierende Entwicklungen in Deutschland bis 2050," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 4(1), pages 3-18, June.
    7. Eckart Bomsdorf, 2010. "Life expectancy in Germany - a look into the future," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 63(22), pages 25-32, November.
    8. Hendrik Hansen & Peter Pflaumer, 2011. "Zur Prognose der Lebenserwartung in Deutschland: Ein Vergleich verschiedener Verfahren," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 5(3), pages 203-219, December.

  5. Friedrich Schmid & Rafael Schmidt, 2007. "Nonparametric inference on multivariate versions of Blomqvist’s beta and related measures of tail dependence," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 66(3), pages 323-354, November.

    Cited by:

    1. Joe, Harry & Li, Haijun & Nikoloulopoulos, Aristidis K., 2010. "Tail dependence functions and vine copulas," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 252-270, January.
    2. Gijbels, Irène & Kika, Vojtěch & Omelka, Marek, 2021. "On the specification of multivariate association measures and their behaviour with increasing dimension," Journal of Multivariate Analysis, Elsevier, vol. 182(C).
    3. Gaißer, Sandra & Ruppert, Martin & Schmid, Friedrich, 2010. "A multivariate version of Hoeffding's Phi-Square," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2571-2586, November.
    4. Salim Bouzebda, 2023. "On Weak Convergence of the Bootstrap Copula Empirical Process with Random Resample Size," Stats, MDPI, vol. 6(1), pages 1-16, February.
    5. Langworthy, Benjamin W. & Stephens, Rebecca L. & Gilmore, John H. & Fine, Jason P., 2021. "Canonical correlation analysis for elliptical copulas," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    6. Wermuth, Nanny & Marchetti, Giovanni M. & Zwiernik, Piotr, 2014. "Binary distributions of concentric rings," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 252-260.
    7. Hofert, Marius & Oldford, Wayne, 2018. "Visualizing dependence in high-dimensional data: An application to S&P 500 constituent data," Econometrics and Statistics, Elsevier, vol. 8(C), pages 161-183.
    8. Liebscher Eckhard, 2014. "Copula-based dependence measures," Dependence Modeling, De Gruyter, vol. 2(1), pages 1-16, October.
    9. Jean-François Quessy, 2021. "On nonparametric tests of multivariate meta-ellipticity," Statistical Papers, Springer, vol. 62(5), pages 2283-2310, October.
    10. Ćmiel, Bogdan & Ledwina, Teresa, 2020. "Validation of association," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 55-67.
    11. Hashorva, Enkelejd, 2009. "Asymptotics for Kotz Type III elliptical distributions," Statistics & Probability Letters, Elsevier, vol. 79(7), pages 927-935, April.
    12. Miriam Jaser & Aleksey Min, 2021. "On tests for symmetry and radial symmetry of bivariate copulas towards testing for ellipticity," Computational Statistics, Springer, vol. 36(3), pages 1-26, September.
    13. Mai, Jan-Frederik & Scherer, Matthias, 2009. "Lévy-frailty copulas," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1567-1585, August.
    14. Bücher Axel & Jaser Miriam & Min Aleksey, 2021. "Detecting departures from meta-ellipticity for multivariate stationary time series," Dependence Modeling, De Gruyter, vol. 9(1), pages 121-140, January.
    15. Genest, Christian & Segers, Johan, 2010. "On the covariance of the asymptotic empirical copula process," Journal of Multivariate Analysis, Elsevier, vol. 101(8), pages 1837-1845, September.
    16. Jaser Miriam & Min Aleksey & Haug Stephan, 2017. "A simple non-parametric goodness-of-fit test for elliptical copulas," Dependence Modeling, De Gruyter, vol. 5(1), pages 330-353, December.
    17. Ferreira Helena & Ferreira Marta, 2020. "Multivariate medial correlation with applications," Dependence Modeling, De Gruyter, vol. 8(1), pages 361-372, January.

  6. Schmid, Friedrich & Schmidt, Rafael, 2007. "Multivariate conditional versions of Spearman's rho and related measures of tail dependence," Journal of Multivariate Analysis, Elsevier, vol. 98(6), pages 1123-1140, July.

    Cited by:

    1. Ferreira, H., 2011. "Dependence between two multivariate extremes," Statistics & Probability Letters, Elsevier, vol. 81(5), pages 586-591, May.
    2. Koen Decancq, 2014. "Copula-based measurement of dependence between dimensions of well-being," Oxford Economic Papers, Oxford University Press, vol. 66(3), pages 681-701.
    3. Joe, Harry & Li, Haijun & Nikoloulopoulos, Aristidis K., 2010. "Tail dependence functions and vine copulas," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 252-270, January.
    4. Klein, Ingo & Tinkl, Fabian, 2011. "Some critical remarks on Zhang's gamma test for independence," Discussion Papers 87/2010, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    5. Gaißer, Sandra & Schmid, Friedrich, 2010. "On testing equality of pairwise rank correlations in a multivariate random vector," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2598-2615, November.
    6. Li, Haijun, 2009. "Orthant tail dependence of multivariate extreme value distributions," Journal of Multivariate Analysis, Elsevier, vol. 100(1), pages 243-256, January.
    7. Zhang, Yuanyuan & Chan, Stephen & Chu, Jeffrey & Nadarajah, Saralees, 2019. "Stylised facts for high frequency cryptocurrency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 598-612.
    8. Gaißer, Sandra & Ruppert, Martin & Schmid, Friedrich, 2010. "A multivariate version of Hoeffding's Phi-Square," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2571-2586, November.
    9. Fabrizio Durante & Roberta Pappadà & Nicola Torelli, 2014. "Clustering of financial time series in risky scenarios," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(4), pages 359-376, December.
    10. Matros, Philipp & Vilsmeier, Johannes, 2014. "The multivariate option iPoD framework: assessing systemic financial risk," Discussion Papers 20/2014, Deutsche Bundesbank.
    11. Philipp Matros & Johannes Vilsmeier, 2013. "The Multivariate Option iPoD Framework - Assessing Systemic Financial Risk," Working Papers 143, Bavarian Graduate Program in Economics (BGPE).
    12. Fuchs, Sebastian & Di Lascio, F. Marta L. & Durante, Fabrizio, 2021. "Dissimilarity functions for rank-invariant hierarchical clustering of continuous variables," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).
    13. Melanie Frick, 2012. "Measures of multivariate asymptotic dependence and their relation to spectral expansions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(6), pages 819-831, August.
    14. César Garcia-Gomez & Ana Pérez & Mercedes Prieto-Alaiz, 2022. "The evolution of poverty in the EU-28: a further look based on multivariate tail dependence," Working Papers 605, ECINEQ, Society for the Study of Economic Inequality.
    15. Bücher Axel, 2014. "A note on nonparametric estimation of bivariate tail dependence," Statistics & Risk Modeling, De Gruyter, vol. 31(2), pages 1-12, June.
    16. Nadarajah, Saralees, 2015. "Expansions for bivariate copulas," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 77-84.
    17. Su, Jianxi & Furman, Edward, 2017. "Multiple risk factor dependence structures: Copulas and related properties," Insurance: Mathematics and Economics, Elsevier, vol. 74(C), pages 109-121.
    18. Nurudeen A. Adegoke & Andrew Punnett & Marti J. Anderson, 2022. "Estimation of Multivariate Dependence Structures via Constrained Maximum Likelihood," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 240-260, June.
    19. Ferreira, Helena & Ferreira, Marta, 2012. "Tail dependence between order statistics," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 176-192.
    20. Pavel Krupskii & Harry Joe, 2015. "Tail-weighted measures of dependence," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 614-629, March.
    21. Ming Liu & Sumner la Croix, 2013. "A Cross-Country Index of Intellectual Property Rights in Pharmaceutical Innovations," Working Papers 201313, University of Hawaii at Manoa, Department of Economics.
    22. Chabi-Yo, Fousseni & Huggenberger, Markus & Weigert, Florian, 2022. "Multivariate crash risk," Journal of Financial Economics, Elsevier, vol. 145(1), pages 129-153.
    23. Furman, Edward & Kuznetsov, Alexey & Su, Jianxi & Zitikis, Ričardas, 2016. "Tail dependence of the Gaussian copula revisited," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 97-103.
    24. Fung, Thomas & Seneta, Eugene, 2011. "The bivariate normal copula function is regularly varying," Statistics & Probability Letters, Elsevier, vol. 81(11), pages 1670-1676, November.
    25. Fabrizio Durante & Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2022. "A Multivariate Dependence Analysis for Electricity Prices, Demand and Renewable Energy Sources," Papers 2201.01132, arXiv.org.
    26. Jianxi Su & Edward Furman, 2016. "Multiple risk factor dependence structures: Copulas and related properties," Papers 1610.02126, arXiv.org.
    27. Liu, Ming & La Croix, Sumner, 2015. "A cross-country index of intellectual property rights in pharmaceutical inventions," Research Policy, Elsevier, vol. 44(1), pages 206-216.
    28. Gregor Weiß, 2012. "Analysing contagion and bailout effects with copulae," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(1), pages 1-32, January.

  7. Schmid, Friedrich & Schmidt, Rafael, 2007. "Multivariate extensions of Spearman's rho and related statistics," Statistics & Probability Letters, Elsevier, vol. 77(4), pages 407-416, February.

    Cited by:

    1. Kateryna Tkach & Chiara Gigliarano, 2018. "Multidimensional poverty measurement: dependence between well-being dimensions using copula function," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 72(3), pages 89-100, July-Sept.
    2. Monica Billio & Lorenzo Frattarolo & Dominique Guegan, 2017. "Multivariate Reflection Symmetry of Copula Functions," Post-Print halshs-01592147, HAL.
    3. Daniel Berg & Jean‐François Quessy, 2009. "Local Power Analyses of Goodness‐of‐fit Tests for Copulas," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(3), pages 389-412, September.
    4. Gaißer, Sandra & Schmid, Friedrich, 2010. "On testing equality of pairwise rank correlations in a multivariate random vector," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2598-2615, November.
    5. Gijbels, Irène & Kika, Vojtěch & Omelka, Marek, 2021. "On the specification of multivariate association measures and their behaviour with increasing dimension," Journal of Multivariate Analysis, Elsevier, vol. 182(C).
    6. Lee, Woojoo & Ahn, Jae Youn, 2014. "On the multidimensional extension of countermonotonicity and its applications," Insurance: Mathematics and Economics, Elsevier, vol. 56(C), pages 68-79.
    7. Todd, Prono, 2009. "Simple, Skewness-Based GMM Estimation of the Semi-Strong GARCH(1,1) Model," MPRA Paper 30994, University Library of Munich, Germany, revised 30 Jul 2011.
    8. Pérez, Ana & Prieto-Alaiz, Mercedes, 2016. "A note on nonparametric estimation of copula-based multivariate extensions of Spearman’s rho," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 41-50.
    9. Gaißer, Sandra & Ruppert, Martin & Schmid, Friedrich, 2010. "A multivariate version of Hoeffding's Phi-Square," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2571-2586, November.
    10. Włodzimierz Wysocki, 2015. "Kendall's tau and Spearman's rho for n -dimensional Archimedean copulas and their asymptotic properties," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 27(4), pages 442-459, December.
    11. Salim Bouzebda, 2023. "On Weak Convergence of the Bootstrap Copula Empirical Process with Random Resample Size," Stats, MDPI, vol. 6(1), pages 1-16, February.
    12. Bücher, Axel & Volgushev, Stanislav, 2013. "Empirical and sequential empirical copula processes under serial dependence," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 61-70.
    13. César García‐Gómez & Ana Pérez & Mercedes Prieto‐Alaiz, 2021. "Copula‐based analysis of multivariate dependence patterns between dimensions of poverty in Europe," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(1), pages 165-195, March.
    14. Thomas Blumentritt & Oliver Grothe, 2013. "Ranking ranks: a ranking algorithm for bootstrapping from the empirical copula," Computational Statistics, Springer, vol. 28(2), pages 455-462, April.
    15. Jean-David Fermanian & Olivier Lopez, 2015. "Single-index copulae," Working Papers 2015-12, Center for Research in Economics and Statistics.
    16. García, Jesús E. & González-López, V.A. & Nelsen, R.B., 2013. "A new index to measure positive dependence in trivariate distributions," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 481-495.
    17. Liebscher Eckhard, 2014. "Copula-based dependence measures," Dependence Modeling, De Gruyter, vol. 2(1), pages 1-16, October.
    18. Blier-Wong, Christopher & Cossette, Hélène & Marceau, Etienne, 2022. "Stochastic representation of FGM copulas using multivariate Bernoulli random variables," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    19. Spandagos, Constantine & Baark, Erik & Ng, Tze Ling & Yarime, Masaru, 2021. "Social influence and economic intervention policies to save energy at home: Critical questions for the new decade and evidence from air-condition use," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    20. Fermanian, Jean-David & Lopez, Olivier, 2018. "Single-index copulas," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 27-55.
    21. Razin, Ronny & Levy, Gilat, 2020. "Combining forecasts in the presence of ambiguity over correlation structures," LSE Research Online Documents on Economics 104641, London School of Economics and Political Science, LSE Library.
    22. Grothe, Oliver & Schnieders, Julius & Segers, Johan, 2013. "Measuring Association and Dependence Between Random Vectors," LIDAM Discussion Papers ISBA 2013026, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    23. Langrené, Nicolas & Warin, Xavier, 2021. "Fast multivariate empirical cumulative distribution function with connection to kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 162(C).
    24. Grothe, Oliver & Schnieders, Julius & Segers, Johan, 2014. "Measuring association and dependence between random vectors," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 96-110.
    25. Grazian, Clara & Dalla Valle, Luciana & Liseo, Brunero, 2022. "Approximate Bayesian conditional copulas," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    26. Jae Youn Ahn, 2015. "Negative Dependence Concept in Copulas and the Marginal Free Herd Behavior Index," Papers 1503.03180, arXiv.org.
    27. Spandagos, Constantine & Yarime, Masaru & Baark, Erik & Ng, Tze Ling, 2020. "“Triple Target” policy framework to influence household energy behavior: Satisfy, strengthen, include," Applied Energy, Elsevier, vol. 269(C).
    28. Lingyue Zhang & Dawei Lu & Xiaoguang Wang, 2020. "Measuring and testing interdependence among random vectors based on Spearman’s $$\rho $$ ρ and Kendall’s $$\tau $$ τ," Computational Statistics, Springer, vol. 35(4), pages 1685-1713, December.
    29. Hao Ji & Hao Wang & Brunero Liseo, 2018. "Portfolio Diversification Strategy Via Tail‐Dependence Clustering and ARMA‐GARCH Vine Copula Approach," Australian Economic Papers, Wiley Blackwell, vol. 57(3), pages 265-283, September.
    30. Reeko Watanabe & Tsunemi Watanabe & Kyohei Wakui, 2021. "Acceptance of Main Power Generation Sources among Japan’s Undergraduate Students: The Roles of Knowledge, Experience, Trust, and Perceived Risk and Benefit," Sustainability, MDPI, vol. 13(22), pages 1, November.
    31. Wied, Dominik & Dehling, Herold & van Kampen, Maarten & Vogel, Daniel, 2014. "A fluctuation test for constant Spearman’s rho with nuisance-free limit distribution," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 723-736.
    32. Mangold, Benedikt, 2017. "A multivariate rank test of independence based on a multiparametric polynomial copula," FAU Discussion Papers in Economics 10/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, revised 2017.
    33. Martin Eling & Denis Toplek, 2009. "Modeling and Management of Nonlinear Dependencies–Copulas in Dynamic Financial Analysis," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 651-681, September.
    34. Ying Zhang & Chuancun Yin, 2014. "A new multivariate dependence measure based on comonotonicity," Papers 1410.7845, arXiv.org.
    35. Mhamed Mesfioui & Julien Trufin, 2022. "Bounds on Multivariate Kendall’s Tau and Spearman’s Rho for Zero-Inflated Continuous Variables and their Application to Insurance," Methodology and Computing in Applied Probability, Springer, vol. 24(2), pages 1051-1059, June.

  8. Schmidt, Rafael & Hrycej, Tomas & Stutzle, Eric, 2006. "Multivariate distribution models with generalized hyperbolic margins," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 2065-2096, April.

    Cited by:

    1. Marcel Wollschlager & Rudi Schafer, 2015. "Impact of non-stationarity on estimating and modeling empirical copulas of daily stock returns," Papers 1506.08054, arXiv.org.
    2. Alp, Tansel & Demetrescu, Matei, 2010. "Joint forecasts of Dow Jones stocks under general multivariate loss function," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2360-2371, November.
    3. Arismendi, Juan C. & Broda, Simon, 2017. "Multivariate elliptical truncated moments," Journal of Multivariate Analysis, Elsevier, vol. 157(C), pages 29-44.
    4. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility (Revised in May 2007, Handbook of Financial Time Series (Published in "Handbook of Financial Time Series" (eds T.G. Andersen, R.A. Davis, Jens-Peter Kreiss," CARF F-Series CARF-F-094, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    5. Fajardo, José & Farias, Aquiles, 2010. "Derivative pricing using multivariate affine generalized hyperbolic distributions," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1607-1617, July.
    6. Yannick Armenti & Stephane Crepey & Samuel Drapeau & Antonis Papapantoleon, 2015. "Multivariate Shortfall Risk Allocation and Systemic Risk," Papers 1507.05351, arXiv.org, revised Mar 2017.
    7. Dilip B. Madan, 2016. "Conic Portfolio Theory," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 1-42, May.
    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. Laradji, A., 2015. "Sums of totally positive functions of order 2 and applications," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 176-180.
    10. Almut E. D. Veraart & Luitgard A. M. Veraart, 2012. "Modelling electricity day–ahead prices by multivariate Lévy semistationary processes," CREATES Research Papers 2012-13, Department of Economics and Business Economics, Aarhus University.
    11. José Fajardo & Aquiles Farias, 2008. "Multivariate Affine Generalized Hyperbolic Distributions: An Empirical Investigation," IBMEC RJ Economics Discussion Papers 2008-01, Economics Research Group, IBMEC Business School - Rio de Janeiro.
    12. Wang, Chou-Wen & Liu, Kai & Li, Bin & Tan, Ken Seng, 2022. "Portfolio optimization under multivariate affine generalized hyperbolic distributions," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 49-66.
    13. Elisa Luciano & Patrizia Semeraro, 2007. "Generalized Normal Mean Variance Mixture and Subordinated Brownian Motion," ICER Working Papers - Applied Mathematics Series 42-2007, ICER - International Centre for Economic Research.
    14. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility," CIRJE F-Series CIRJE-F-488, CIRJE, Faculty of Economics, University of Tokyo.
    15. Eduarda T. C. Chagas & Marcelo Queiroz‐Oliveira & Osvaldo A. Rosso & Heitor S. Ramos & Cristopher G. S. Freitas & Alejandro C. Frery, 2022. "White Noise Test from Ordinal Patterns in the Entropy–Complexity Plane," International Statistical Review, International Statistical Institute, vol. 90(2), pages 374-396, August.
    16. Alexios Ghalanos & Eduardo Rossi & Giovanni Urga, 2015. "Independent Factor Autoregressive Conditional Density Model," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 594-616, May.
    17. Alexandre Petkovic, 2009. "Three essays on exotic option pricing, multivariate Lévy processes and linear aggregation of panel models," ULB Institutional Repository 2013/210357, ULB -- Universite Libre de Bruxelles.
    18. Wraith, Darren & Forbes, Florence, 2015. "Location and scale mixtures of Gaussians with flexible tail behaviour: Properties, inference and application to multivariate clustering," Computational Statistics & Data Analysis, Elsevier, vol. 90(C), pages 61-73.

  9. Rafael Schmidt & Ulrich Stadtmüller, 2006. "Non‐parametric Estimation of Tail Dependence," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(2), pages 307-335, June.

    Cited by:

    1. Erick Treviño Aguilar, 2020. "The interdependency structure in the Mexican stock exchange: A network approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-31, October.
    2. Elena Di Bernardino & Didier Rullière, 2017. "A note on upper-patched generators for Archimedean copulas," Post-Print hal-01347869, HAL.
    3. Jorge Antunes & Luis Alberiko Gil-Alana & Rossana Riccardi & Yong Tan & Peter Wanke, 2022. "Unveiling endogeneity and temporal dependence in energy prices and demand in Iberian countries: a stochastic hidden Markov model approach," Annals of Operations Research, Springer, vol. 313(1), pages 191-229, June.
    4. Chen Yang & Wenjun Jiang & Jiang Wu & Xin Liu & Zhichuan Li, 2018. "Clustering of financial instruments using jump tail dependence coefficient," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(3), pages 491-513, August.
    5. Georg Mainik & Ludger Rüschendorf, 2010. "On optimal portfolio diversification with respect to extreme risks," Finance and Stochastics, Springer, vol. 14(4), pages 593-623, December.
    6. Matkovskyy, Roman, 2019. "Centralized and decentralized bitcoin markets: Euro vs USD vs GBP," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 270-279.
    7. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    8. Kiriliouk, Anna & Lee, Jeongjin & Segers, Johan, 2023. "X-Vine Models for Multivariate Extremes," LIDAM Discussion Papers ISBA 2023038, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Claudia Klüppelberg & Gabriel Kuhn & Liang Peng, 2008. "Semi‐Parametric Models for the Multivariate Tail Dependence Function – the Asymptotically Dependent Case," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(4), pages 701-718, December.
    10. Travkin, A., 2015. "Estimating Pair-Copula Constructions Using Empirical Tail Dependence Functions: an Application to Russian Stock Market," Journal of the New Economic Association, New Economic Association, vol. 25(1), pages 39-55.
    11. Mühlnickel, Janina & Weiß, Gregor N.F., 2015. "Consolidation and systemic risk in the international insurance industry," Journal of Financial Stability, Elsevier, vol. 18(C), pages 187-202.
    12. 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).
    13. Li, Feng & Kang, Yanfei, 2018. "Improving forecasting performance using covariate-dependent copula models," International Journal of Forecasting, Elsevier, vol. 34(3), pages 456-476.
    14. Trabelsi, Nader, 2017. "Asymmetric tail dependence between oil price shocks and sectors of Saudi Arabia System," The Journal of Economic Asymmetries, Elsevier, vol. 16(C), pages 26-41.
    15. Karl Friedrich Siburg & Christopher Strothmann & Gregor Wei{ss}, 2022. "Comparing and quantifying tail dependence," Papers 2208.10319, arXiv.org.
    16. Daouia, Abdelaati & Padoan, Simone A. & Stupfler, Gilles, 2022. "Optimal weighted pooling for inference about the tail index and extreme quantiles," TSE Working Papers 22-1322, Toulouse School of Economics (TSE), revised 07 Jun 2023.
    17. Daouia, Abdelaati & Padoan, Simone A. & Stupfler, Gilles, 2023. "Extreme expectile estimation for short-tailed data, with an application to market risk assessment," TSE Working Papers 23-1414, Toulouse School of Economics (TSE).
    18. Kellner, Ralf & Rösch, Daniel, 2019. "A country specific point of view on international diversification," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.
    19. Lee, Seohyun, 2017. "Three essays on uncertainty: real and financial effects of uncertainty shocks," MPRA Paper 83617, University Library of Munich, Germany.
    20. 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).
    21. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2017. "The kidnapping of Europe: High-order moments' transmission between developed and emerging markets," Emerging Markets Review, Elsevier, vol. 31(C), pages 96-115.
    22. Gardes, Laurent & Girard, Stéphane, 2015. "Nonparametric estimation of the conditional tail copula," Journal of Multivariate Analysis, Elsevier, vol. 137(C), pages 1-16.
    23. Yannick Hoga, 2023. "The Estimation Risk in Extreme Systemic Risk Forecasts," Papers 2304.10349, arXiv.org.
    24. Jalan, Akanksha & Matkovskyy, Roman & Yarovaya, Larisa, 2021. "“Shiny” crypto assets: A systemic look at gold-backed cryptocurrencies during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 78(C).
    25. Khader Khadraoui & Pierre Ribereau, 2019. "Bayesian Inference with M-splines on Spectral Measure of Bivariate Extremes," Methodology and Computing in Applied Probability, Springer, vol. 21(3), pages 765-788, September.
    26. Yuri Salazar & Wing Ng, 2015. "Nonparametric estimation of general multivariate tail dependence and applications to financial time series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(1), pages 121-158, March.
    27. Zhang, Qingzhao & Li, Deyuan & Wang, Hansheng, 2013. "A note on tail dependence regression," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 163-172.
    28. H. E.T. Holgersson & Peter S. Karlsson & Rashid Mansoor, 2012. "Estimating mean-standard deviation ratios of financial data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(3), pages 657-671, August.
    29. de Haan, Laurens & Neves, Cláudia & Peng, Liang, 2008. "Parametric tail copula estimation and model testing," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1260-1275, July.
    30. Avramidis, Panagiotis & Pasiouras, Fotios, 2015. "Calculating systemic risk capital: A factor model approach," Journal of Financial Stability, Elsevier, vol. 16(C), pages 138-150.
    31. Weiß, Gregor N.F. & Neumann, Sascha & Bostandzic, Denefa, 2014. "Systemic risk and bank consolidation: International evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 165-181.
    32. 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).
    33. Benjamin Hippert & André Uhde & Sascha Tobias Wengerek, 2019. "Determinants of CDS trading on major banks," Working Papers Dissertations 51, Paderborn University, Faculty of Business Administration and Economics.
    34. Marta Ferreira & Helena Ferreira, 2012. "On extremal dependence: some contributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 566-583, September.
    35. César Garcia-Gomez & Ana Pérez & Mercedes Prieto-Alaiz, 2022. "The evolution of poverty in the EU-28: a further look based on multivariate tail dependence," Working Papers 605, ECINEQ, Society for the Study of Economic Inequality.
    36. Bücher Axel, 2014. "A note on nonparametric estimation of bivariate tail dependence," Statistics & Risk Modeling, De Gruyter, vol. 31(2), pages 1-12, June.
    37. Bormann, Carsten & Schienle, Melanie, 2019. "Detecting structural differences in tail dependence of financial time series," Working Paper Series in Economics 122, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    38. Einmahl, John & Segers, Johan, 2020. "Empirical Tail Copulas for Functional Data," Discussion Paper 2020-004, Tilburg University, Center for Economic Research.
    39. Juan Fernández Sánchez & Manuel Úbeda-Flores, 2014. "Semi-polynomial copulas," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 129-140, March.
    40. Gregory, Alastair, 2019. "A streaming algorithm for bivariate empirical copulas," Computational Statistics & Data Analysis, Elsevier, vol. 135(C), pages 56-69.
    41. Segers, Johan, 2012. "Max-Stable Models For Multivariate Extremes," LIDAM Discussion Papers ISBA 2012011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    42. Choroś-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2013. "Valuation of collateralized debt obligations with hierarchical Archimedean copulae," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 42-62.
    43. Musmeci, Nicoló & Nicosia, Vincenzo & Aste, Tomaso & Di Matteo, Tiziana & Latora, Vito, 2017. "The multiplex dependency structure of financial markets," LSE Research Online Documents on Economics 85337, London School of Economics and Political Science, LSE Library.
    44. Supper, Hendrik & Irresberger, Felix & Weiß, Gregor, 2020. "A comparison of tail dependence estimators," European Journal of Operational Research, Elsevier, vol. 284(2), pages 728-742.
    45. Wu, Ximing, 2010. "Exponential Series Estimator of multivariate densities," Journal of Econometrics, Elsevier, vol. 156(2), pages 354-366, June.
    46. Li, Haijun & Wu, Peiling, 2013. "Extremal dependence of copulas: A tail density approach," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 99-111.
    47. Peter Grundke, 2019. "Ranking consistency of systemic risk measures: a simulation-based analysis in a banking network model," Review of Quantitative Finance and Accounting, Springer, vol. 52(4), pages 953-990, May.
    48. Ferreira, Helena & Ferreira, Marta, 2012. "Tail dependence between order statistics," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 176-192.
    49. Helena Ferreira & Marta Ferreira, 2021. "Tail dependence and smoothness of time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 198-210, March.
    50. Ranoua Bouchouicha, 2010. "Dépendance entre risques extrêmes : Application aux Hedge Funds," Working Papers 1013, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    51. Abootaleb Shirvani & Dimitri Volchenkov, 2019. "A Regulated Market Under Sanctions: On Tail Dependence Between Oil, Gold, and Tehran Stock Exchange Index," Papers 1911.01826, arXiv.org.
    52. Schmid, Friedrich & Schmidt, Rafael, 2007. "Multivariate conditional versions of Spearman's rho and related measures of tail dependence," Journal of Multivariate Analysis, Elsevier, vol. 98(6), pages 1123-1140, July.
    53. Marta Ferreira & Helena Ferreira, 2013. "Extremes of multivariate ARMAX processes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(4), pages 606-627, November.
    54. Hua, Lei & Joe, Harry, 2014. "Strength of tail dependence based on conditional tail expectation," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 143-159.
    55. Jäschke, Stefan, 2014. "Estimation of risk measures in energy portfolios using modern copula techniques," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 359-376.
    56. Guglielmo Maria Caporale & Mario Cerrato & Xuan Zhang, 2016. "Analysing the Determinants of Credit Risk for General Insurance Firms in the UK," Discussion Papers of DIW Berlin 1591, DIW Berlin, German Institute for Economic Research.
    57. Roman Matkovskyy, 2019. "Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries," Post-Print hal-02332090, HAL.
    58. Ghosh, Santu & Ayyala, Deepak Nag & Hellebuyck, Rafael, 2021. "Two-sample high dimensional mean test based on prepivots," Computational Statistics & Data Analysis, Elsevier, vol. 163(C).
    59. Mikael Escobar-Bach & Yuri Goegebeur & Armelle Guillou & Alexandre You, 2017. "Bias-corrected and robust estimation of the bivariate stable tail dependence function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 284-307, June.
    60. Siburg, Karl Friedrich & Stoimenov, Pavel & Weiß, Gregor N.F., 2015. "Forecasting portfolio-Value-at-Risk with nonparametric lower tail dependence estimates," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 129-140.
    61. Li, Deyuan & Peng, Liang, 2009. "Goodness-of-fit test for tail copulas modeled by elliptical copulas," Statistics & Probability Letters, Elsevier, vol. 79(8), pages 1097-1104, April.
    62. Clément Dombry & Michael Falk & Maximilian Zott, 2019. "On Functional Records and Champions," Journal of Theoretical Probability, Springer, vol. 32(3), pages 1252-1277, September.
    63. Elena Di Bernardino & Didier Rullière, 2016. "On tail dependence coefficients of transformed multivariate Archimedean copulas," Post-Print hal-00992707, HAL.
    64. Michael Falk & Gilles Stupfler, 2021. "The Min-characteristic Function: Characterizing Distributions by Their Min-linear Projections," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 254-282, February.
    65. Ji, Liuyan & Tan, Ken Seng & Yang, Fan, 2021. "Tail dependence and heavy tailedness in extreme risks," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 282-293.
    66. Fischer, Matthias J. & Dörflinger, Marco, 2006. "A note on a non-parametric tail dependence estimator," Discussion Papers 76/2006, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    67. Rootzén, Holger & Segers, Johan & Wadsworth, Jennifer L., 2018. "Multivariate generalized Pareto distributions: Parametrizations, representations, and properties," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 117-131.
    68. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2018. "Asset allocation: new evidence through network approaches," Papers 1810.09825, arXiv.org.
    69. Aguilar, Mike & Hill, Jonathan B., 2015. "Robust score and portmanteau tests of volatility spillover," Journal of Econometrics, Elsevier, vol. 184(1), pages 37-61.
    70. Yuri Salazar Flores & Adán Díaz-Hernández, 2022. "The General Tail Dependence Function in the Marshall-Olkin and Other Parametric Copula Models with an Application to Financial Time Series," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(1), pages 146-187, May.
    71. Adlane Haffar & Éric Le Fur, 2022. "Dependence structure of CAT bonds and portfolio diversification: a copula-GARCH approach," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 297-309, July.
    72. Shyamalkumar, Nariankadu D. & Tao, Siyang, 2022. "t-copula from the viewpoint of tail dependence matrices," Journal of Multivariate Analysis, Elsevier, vol. 191(C).
    73. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2021. "Asset allocation: new evidence through network approaches," Annals of Operations Research, Springer, vol. 299(1), pages 61-80, April.
    74. Górecki, Jan & Hofert, Marius & Okhrin, Ostap, 2021. "Outer power transformations of hierarchical Archimedean copulas: Construction, sampling and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
    75. Hu, Shuang & Peng, Zuoxiang & Segers, Johan, 2022. "Modelling multivariate extreme value distributions via Markov trees," LIDAM Discussion Papers ISBA 2022021, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    76. Víctor M. Adame-García & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, "undated". "Portfolios in the Ibex 35 index: Alternative methods to the traditional framework, a comparative with the naive diversification in a pre- and post- crisis context," Documentos de Trabajo del ICAE 2015-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Jun 2015.
    77. Beck, Nicholas & Di Bernardino, Elena & Mailhot, Mélina, 2021. "Semi-parametric estimation of multivariate extreme expectiles," Journal of Multivariate Analysis, Elsevier, vol. 184(C).
    78. Herrera, R. & Eichler, S., 2011. "Extreme dependence with asymmetric thresholds: Evidence for the European Monetary Union," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2916-2930, November.
    79. Bücher, Axel & Volgushev, Stanislav & Zou, Nan, 2019. "On second order conditions in the multivariate block maxima and peak over threshold method," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 604-619.
    80. Chen, Zhongfei & Wanke, Peter & Antunes, Jorge Junio Moreira & Zhang, Ning, 2017. "Chinese airline efficiency under CO2 emissions and flight delays: A stochastic network DEA model," Energy Economics, Elsevier, vol. 68(C), pages 89-108.
    81. Rootzen, Holger & Segers, Johan & Wadsworth, Jennifer, 2017. "Multivariate generalized Pareto distributions: parametrizations, representations, and properties," LIDAM Discussion Papers ISBA 2017016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    82. Raza, Hamid & Wu, Weiou, 2018. "Quantile dependence between the stock, bond and foreign exchange markets – Evidence from the UK," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 286-296.
    83. Nikoloulopoulos, Aristidis K. & Joe, Harry & Li, Haijun, 2012. "Vine copulas with asymmetric tail dependence and applications to financial return data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3659-3673.
    84. Münnix, Michael C. & Schäfer, Rudi, 2011. "A copula approach on the dynamics of statistical dependencies in the US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4251-4259.
    85. Weiß, Gregor N.F. & Bostandzic, Denefa & Neumann, Sascha, 2014. "What factors drive systemic risk during international financial crises?," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 78-96.
    86. Víctor Adame-García & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2017. "“Resolution of optimization problems and construction of efficient portfolios: An application to the Euro Stoxx 50 index"," IREA Working Papers 201702, University of Barcelona, Research Institute of Applied Economics, revised Feb 2017.
    87. Selma Chaker & Nour Meddahi, 2013. "CoMargin," Staff Working Papers 13-47, Bank of Canada.
    88. Yuri Salazar Flores & Adán Díaz-Hernández, 2021. "Counterdiagonal/nonpositive tail dependence in Vine copula constructions: application to portfolio management," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 375-407, June.
    89. Bucher, Axel & Jaschke, Stefan & Wied, Dominik, 2013. "Nonparametric tests for constant tail dependence with an application to energy and finance," LIDAM Discussion Papers ISBA 2013033, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  10. Frahm, Gabriel & Junker, Markus & Schmidt, Rafael, 2005. "Estimating the tail-dependence coefficient: Properties and pitfalls," Insurance: Mathematics and Economics, Elsevier, vol. 37(1), pages 80-100, August.

    Cited by:

    1. Dong-Dong Zhang & Deng-Hua Yan & Fan Lu & Yi-Cheng Wang & Jing Feng, 2015. "Copula-based risk assessment of drought in Yunnan province, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(3), pages 2199-2220, February.
    2. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2014. "Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas," SIRE Discussion Papers 2015-25, Scottish Institute for Research in Economics (SIRE).
    3. Ruenzi, Stefan & Ungeheuer, Michael & Weigert, Florian, 2020. "Joint extreme events in equity returns and liquidity and their cross-sectional pricing implications," CFR Working Papers 20-01, University of Cologne, Centre for Financial Research (CFR).
    4. Dominik Paprotny & Michalis I. Vousdoukas & Oswaldo Morales-Nápoles & Sebastiaan N. Jonkman & Luc Feyen, 2020. "Pan-European hydrodynamic models and their ability to identify compound floods," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 101(3), pages 933-957, April.
    5. Gijbels, Irène & Sznajder, Dominik, 2013. "Testing tail monotonicity by constrained copula estimation," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 338-351.
    6. Ziqiang Xing & Denghua Yan & Cheng Zhang & Gang Wang & Dongdong Zhang, 2015. "Spatial Characterization and Bivariate Frequency Analysis of Precipitation and Runoff in the Upper Huai River Basin, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(9), pages 3291-3304, July.
    7. Ruenzi, Stefan & Ungeheuer, Michael & Weigert, Florian, 2013. "Extreme Downside Liquidity Risk," Working Papers on Finance 1326, University of St. Gallen, School of Finance, revised Jul 2015.
    8. Matkovskyy, Roman, 2019. "Centralized and decentralized bitcoin markets: Euro vs USD vs GBP," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 270-279.
    9. Sun, Mingyang & Cremer, Jochen & Strbac, Goran, 2018. "A novel data-driven scenario generation framework for transmission expansion planning with high renewable energy penetration," Applied Energy, Elsevier, vol. 228(C), pages 546-555.
    10. Faias, José Afonso, 2023. "Predicting the equity risk premium using the smooth cross-sectional tail risk: The importance of correlation," Journal of Financial Markets, Elsevier, vol. 63(C).
    11. Fabrizio Durante & Roberta Pappadà & Nicola Torelli, 2015. "Clustering of time series via non-parametric tail dependence estimation," Statistical Papers, Springer, vol. 56(3), pages 701-721, August.
    12. Trabelsi, Nader, 2017. "Asymmetric tail dependence between oil price shocks and sectors of Saudi Arabia System," The Journal of Economic Asymmetries, Elsevier, vol. 16(C), pages 26-41.
    13. Curtis B. Storlie & Brian J. Reich & William N. Rust & Lawrence O. Ticknor & Amanda M. Bonnie & Andrew J. Montoya & Sarah E. Michalak, 2017. "Spatiotemporal Modeling of Node Temperatures in Supercomputers," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 92-108, January.
    14. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2017. "Relation between higher order comoments and dependence structure of equity portfolio," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 101-120.
    15. Lehtomaa, Jaakko & Resnick, Sidney I., 2020. "Asymptotic independence and support detection techniques for heavy-tailed multivariate data," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 262-277.
    16. M. Barkhagen & S. García & J. Gondzio & J. Kalcsics & J. Kroeske & S. Sabanis & A. Staal, 2023. "Optimising portfolio diversification and dimensionality," Journal of Global Optimization, Springer, vol. 85(1), pages 185-234, January.
    17. Mendes, Beatriz Vaz de Melo & Arslan, Olcay, 2006. "Multivariate Skew Distributions Based on the GT-Copula," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 26(2), November.
    18. Shahid Latif & Slobodan P. Simonovic, 2023. "Trivariate Probabilistic Assessments of the Compound Flooding Events Using the 3-D Fully Nested Archimedean (FNA) Copula in the Semiparametric Distribution Setting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(4), pages 1641-1693, March.
    19. Udichibarna Bose & Ronald MacDonald & Serafeim Tsoukas, 2014. "The role of education in equity portfolios during the recent financial crisis," Working Papers 2014_17, Business School - Economics, University of Glasgow.
    20. Chabi-Yo, Fousseni & Ruenzi, Stefan & Weigert, Florian, 2013. "Crash Sensitivity and the Cross-Section of Expected Stock Returns," Working Papers on Finance 1324, University of St. Gallen, School of Finance, revised Feb 2016.
    21. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," SIRE Discussion Papers 2015-78, Scottish Institute for Research in Economics (SIRE).
    22. Dominique Guegan & Matteo Iacopini, 2018. "Nonparametric forecasting of multivariate probability density functions," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01821815, HAL.
    23. Negi, Digvijay S., 2018. "Tail-dependent Rainfall Risk and Demand for Index based Crop Insurance," 2018 Annual Meeting, August 5-7, Washington, D.C. 274481, Agricultural and Applied Economics Association.
    24. Jalan, Akanksha & Matkovskyy, Roman & Yarovaya, Larisa, 2021. "“Shiny” crypto assets: A systemic look at gold-backed cryptocurrencies during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 78(C).
    25. Yuri Salazar & Wing Ng, 2015. "Nonparametric estimation of general multivariate tail dependence and applications to financial time series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(1), pages 121-158, March.
    26. Zhang, Qingzhao & Li, Deyuan & Wang, Hansheng, 2013. "A note on tail dependence regression," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 163-172.
    27. Mohamad Haytham Klaho & Hamid R. Safavi & Mohammad H. Golmohammadi & Maamoun Alkntar, 2022. "Comparison between bivariate and trivariate flood frequency analysis using the Archimedean copula functions, a case study of the Karun River in Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(2), pages 1589-1610, June.
    28. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula," Working Papers 2015_15, Business School - Economics, University of Glasgow.
    29. Zhang, Ming-Heng, 2008. "Modelling total tail dependence along diagonals," Insurance: Mathematics and Economics, Elsevier, vol. 42(1), pages 73-80, February.
    30. Tim Bedford & Alireza Daneshkhah & Kevin J. Wilson, 2016. "Approximate Uncertainty Modeling in Risk Analysis with Vine Copulas," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 792-815, April.
    31. Bax, Karoline & Sahin, Özge & Czado, Claudia & Paterlini, Sandra, 2023. "ESG, risk, and (tail) dependence," International Review of Financial Analysis, Elsevier, vol. 87(C).
    32. Benjamin Hippert & André Uhde & Sascha Tobias Wengerek, 2019. "Determinants of CDS trading on major banks," Working Papers Dissertations 51, Paderborn University, Faculty of Business Administration and Economics.
    33. Huang, Huichou & MacDonald, Ronald & Zhao, Yang, 2012. "Global Currency Misalignments, Crash Sensitivity, and Downside Insurance Costs," MPRA Paper 53745, University Library of Munich, Germany, revised 18 Nov 2013.
    34. Marta Ferreira & Helena Ferreira, 2012. "On extremal dependence: some contributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 566-583, September.
    35. César Garcia-Gomez & Ana Pérez & Mercedes Prieto-Alaiz, 2022. "The evolution of poverty in the EU-28: a further look based on multivariate tail dependence," Working Papers 605, ECINEQ, Society for the Study of Economic Inequality.
    36. Grobys, Klaus, 2023. "Correlation versus co-fractality: Evidence from foreign-exchange-rate variances," International Review of Financial Analysis, Elsevier, vol. 86(C).
    37. Longxia Qian & Yong Zhao & Jianhong Yang & Hanlin Li & Hongrui Wang & ChengZu Bai, 2022. "A New Estimation Method for Copula Parameters for Multivariate Hydrological Frequency Analysis With Small Sample Sizes," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1141-1157, March.
    38. Bormann, Carsten & Schienle, Melanie, 2019. "Detecting structural differences in tail dependence of financial time series," Working Paper Series in Economics 122, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    39. Matthias Pelster & Johannes Vilsmeier, 2018. "The determinants of CDS spreads: evidence from the model space," Review of Derivatives Research, Springer, vol. 21(1), pages 63-118, April.
    40. DiTraglia, Francis J. & Gerlach, Jeffrey R., 2013. "Portfolio selection: An extreme value approach," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 305-323.
    41. Matthieu Garcin & Maxime L. D. Nicolas, 2021. "Nonparametric estimator of the tail dependence coefficient: balancing bias and variance," Papers 2111.11128, arXiv.org, revised Jul 2023.
    42. L. Vergni & F. Todisco & F. Mannocchi, 2015. "Analysis of agricultural drought characteristics through a two-dimensional copula," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2819-2835, June.
    43. Dominique Guégan & Matteo Iacopini, 2018. "Nonparameteric forecasting of multivariate probability density functions," Documents de travail du Centre d'Economie de la Sorbonne 18012, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    44. Juan Fernández Sánchez & Manuel Úbeda-Flores, 2014. "Semi-polynomial copulas," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 129-140, March.
    45. Nelsen, Roger B. & Quesada-Molina, José Juan & Rodri­guez-Lallena, José Antonio & Úbeda-Flores, Manuel, 2008. "On the construction of copulas and quasi-copulas with given diagonal sections," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 473-483, April.
    46. Friedrich Schmid & Rafael Schmidt, 2007. "Nonparametric inference on multivariate versions of Blomqvist’s beta and related measures of tail dependence," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 66(3), pages 323-354, November.
    47. Matteo Iacopini & Dominique Guégan, 2018. "Nonparametric Forecasting of Multivariate Probability Density Functions," Working Papers 2018:15, Department of Economics, University of Venice "Ca' Foscari".
    48. Rhee, S. Ghon & Wu, Feng (Harry), 2020. "Conditional extreme risk, black swan hedging, and asset prices," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 412-435.
    49. A. P. Martins & J. R. Sebastião, 2019. "Methods for estimating the upcrossings index: improvements and comparison," Statistical Papers, Springer, vol. 60(4), pages 1317-1347, August.
    50. Pavel Krupskii & Harry Joe, 2015. "Tail-weighted measures of dependence," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 614-629, March.
    51. Helena Ferreira & Marta Ferreira, 2021. "Tail dependence and smoothness of time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 198-210, March.
    52. Schmid, Friedrich & Schmidt, Rafael, 2007. "Multivariate conditional versions of Spearman's rho and related measures of tail dependence," Journal of Multivariate Analysis, Elsevier, vol. 98(6), pages 1123-1140, July.
    53. M. Mehdi Bateni & Mario L. V. Martina & ·Marcello Arosio, 2022. "Multivariate return period for different types of flooding in city of Monza, Italy," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(1), pages 811-823, October.
    54. Jäschke, Stefan, 2014. "Estimation of risk measures in energy portfolios using modern copula techniques," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 359-376.
    55. Dobrić, Jadran & Frahm, Gabriel & Schmid, Friedrich, 2007. "Dependence of stock returns in bull and bear markets," Discussion Papers in Econometrics and Statistics 9/07, University of Cologne, Institute of Econometrics and Statistics.
    56. Dunxian She & Jun Xia, 2018. "Copulas-Based Drought Characteristics Analysis and Risk Assessment across the Loess Plateau of China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(2), pages 547-564, January.
    57. Tjøstheim, Dag & Hufthammer, Karl Ove, 2013. "Local Gaussian correlation: A new measure of dependence," Journal of Econometrics, Elsevier, vol. 172(1), pages 33-48.
    58. Roman Matkovskyy, 2019. "Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries," Post-Print hal-02332090, HAL.
    59. Wu, Weiou & Lau, Marco Chi Keung & Vigne, Samuel A., 2017. "Modelling asymmetric conditional dependence between Shanghai and Hong Kong stock markets," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1137-1149.
    60. Michael C. Munnix & Rudi Schafer, 2011. "A Copula Approach on the Dynamics of Statistical Dependencies in the US Stock Market," Papers 1102.1099, arXiv.org, revised Mar 2011.
    61. Sahu, Pritish Kumar & Bal, Debi Prasad & Kundu, Pradip, 2022. "Gold price and exchange rate in pre and during Covid-19 period in India: Modelling dependence using copulas," Resources Policy, Elsevier, vol. 79(C).
    62. Mike So & Alex Tse, 2009. "Dynamic Modeling of Tail Risk: Applications to China, Hong Kong and Other Asian Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 16(3), pages 183-210, September.
    63. Michaël Allouche & Mnacho Echenim & Emmanuel Gobet & Anne-Claire Maurice, 2023. "Statistical error bounds for weighted mean and median, with application to robust aggregation of cryptocurrency data," Working Papers hal-04017151, HAL.
    64. Elena Di Bernardino & Didier Rullière, 2016. "On tail dependence coefficients of transformed multivariate Archimedean copulas," Post-Print hal-00992707, HAL.
    65. Fischer, Matthias J. & Dörflinger, Marco, 2006. "A note on a non-parametric tail dependence estimator," Discussion Papers 76/2006, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    66. Y Hoga, 2018. "A structural break test for extremal dependence in β-mixing random vectors," Biometrika, Biometrika Trust, vol. 105(3), pages 627-643.
    67. Yue Peng & Wing Ng, 2012. "Analysing financial contagion and asymmetric market dependence with volatility indices via copulas," Annals of Finance, Springer, vol. 8(1), pages 49-74, February.
    68. Adlane Haffar & Éric Le Fur, 2022. "Dependence structure of CAT bonds and portfolio diversification: a copula-GARCH approach," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 297-309, July.
    69. Poulomi Ganguli & M. Reddy, 2012. "Risk Assessment of Droughts in Gujarat Using Bivariate Copulas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(11), pages 3301-3327, September.
    70. Shyamalkumar, Nariankadu D. & Tao, Siyang, 2022. "t-copula from the viewpoint of tail dependence matrices," Journal of Multivariate Analysis, Elsevier, vol. 191(C).
    71. Vergni, L. & Todisco, F. & Di Lena, B. & Mannocchi, F., 2020. "Bivariate analysis of drought duration and severity for irrigation planning," Agricultural Water Management, Elsevier, vol. 229(C).
    72. Víctor M. Adame-García & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, "undated". "Portfolios in the Ibex 35 index: Alternative methods to the traditional framework, a comparative with the naive diversification in a pre- and post- crisis context," Documentos de Trabajo del ICAE 2015-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Jun 2015.
    73. Manner, Hans & Segers, Johan, 2011. "Tails of correlation mixtures of elliptical copulas," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 153-160, January.
    74. Kun Xie & Yanfeng He & Jong-Suk Kim & Sun-Kwon Yoon & Jie Liu & Hua Chen & Jung Hwan Lee & Xiang Zhang & Chong-Yu Xu, 2023. "Assessment of the Joint Impact of Rainfall Characteristics on Urban Flooding and Resilience Using the Copula Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(4), pages 1765-1784, March.
    75. Echaust, Krzysztof, 2021. "Asymmetric tail dependence between stock market returns and implied volatility," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
    76. Raza, Hamid & Wu, Weiou, 2018. "Quantile dependence between the stock, bond and foreign exchange markets – Evidence from the UK," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 286-296.
    77. Münnix, Michael C. & Schäfer, Rudi, 2011. "A copula approach on the dynamics of statistical dependencies in the US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4251-4259.
    78. Pelster, Matthias & Vilsmeier, Johannes, 2016. "The determinants of CDS spreads: Evidence from the model space," Discussion Papers 43/2016, Deutsche Bundesbank.
    79. Víctor Adame-García & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2017. "“Resolution of optimization problems and construction of efficient portfolios: An application to the Euro Stoxx 50 index"," IREA Working Papers 201702, University of Barcelona, Research Institute of Applied Economics, revised Feb 2017.
    80. Dominique Guegan & Matteo Iacopini, 2018. "Nonparametric forecasting of multivariate probability density functions," Post-Print halshs-01821815, HAL.
    81. Lamneithem Hangshing & Parmendra P. Dabral, 2018. "Multivariate Frequency Analysis of Meteorological Drought Using Copula," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1741-1758, March.
    82. 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.
    83. Bucher, Axel & Jaschke, Stefan & Wied, Dominik, 2013. "Nonparametric tests for constant tail dependence with an application to energy and finance," LIDAM Discussion Papers ISBA 2013033, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  11. N. H. Bingham & Rudiger Kiesel & Rafael Schmidt, 2003. "A semi-parametric approach to risk management," Quantitative Finance, Taylor & Francis Journals, vol. 3(6), pages 426-441.

    Cited by:

    1. Jeroen V.K. Rombouts & Marno Verbeek, 2004. "Evaluating Portfolio Value-at-Risk using Semi-Parametric GARCH Models," Cahiers de recherche 04-14, HEC Montréal, Institut d'économie appliquée.
    2. Kim, Bara & Kim, Jeongsim, 2019. "Stochastic ordering of Gini indexes for multivariate elliptical risks," Insurance: Mathematics and Economics, Elsevier, vol. 88(C), pages 151-158.
    3. Yves Dominicy & Hiroaki Ogata & David Veredas, 2013. "Inference for vast dimensional elliptical distributions," Computational Statistics, Springer, vol. 28(4), pages 1853-1880, August.
    4. Kim, Joseph H.T. & Kim, So-Yeun, 2019. "Tail risk measures and risk allocation for the class of multivariate normal mean–variance mixture distributions," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 145-157.
    5. Scarf, Phil & Parma, Rishikesh & McHale, Ian, 2019. "On outcome uncertainty and scoring rates in sport: The case of international rugby union," European Journal of Operational Research, Elsevier, vol. 273(2), pages 721-730.
    6. Michael R. Metel & Traian A. Pirvu & Julian Wong, 2017. "Risk Management under Omega Measure," Risks, MDPI, vol. 5(2), pages 1-14, May.
    7. Hashorva, Enkelejd, 2005. "Extremes of asymptotically spherical and elliptical random vectors," Insurance: Mathematics and Economics, Elsevier, vol. 36(3), pages 285-302, June.
    8. Fry, J. M. & Masood, Omar, 2011. "Testable implications of economic revolutions: An application to historic data on European wages," MPRA Paper 32812, University Library of Munich, Germany.

  12. Rafael Schmidt, 2002. "Tail dependence for elliptically contoured distributions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 55(2), pages 301-327, May.

    Cited by:

    1. Ferreira, H., 2011. "Dependence between two multivariate extremes," Statistics & Probability Letters, Elsevier, vol. 81(5), pages 586-591, May.
    2. Mahmoud Hamada & Emiliano A. Valdez, 2008. "CAPM and Option Pricing With Elliptically Contoured Distributions," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 75(2), pages 387-409, June.
    3. Joe, Harry & Li, Haijun & Nikoloulopoulos, Aristidis K., 2010. "Tail dependence functions and vine copulas," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 252-270, January.
    4. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Econometrics Working Papers Archive 2016_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    5. Kurowicka, Dorota & van Horssen, Wim T., 2015. "On an interaction function for copulas," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 127-142.
    6. Li, Haijun, 2009. "Orthant tail dependence of multivariate extreme value distributions," Journal of Multivariate Analysis, Elsevier, vol. 100(1), pages 243-256, January.
    7. Trabelsi, Nader, 2017. "Asymmetric tail dependence between oil price shocks and sectors of Saudi Arabia System," The Journal of Economic Asymmetries, Elsevier, vol. 16(C), pages 26-41.
    8. Mendes, Beatriz Vaz de Melo & Arslan, Olcay, 2006. "Multivariate Skew Distributions Based on the GT-Copula," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 26(2), November.
    9. Fung, Thomas & Seneta, Eugene, 2010. "Tail dependence for two skew t distributions," Statistics & Probability Letters, Elsevier, vol. 80(9-10), pages 784-791, May.
    10. Huard, David & Evin, Guillaume & Favre, Anne-Catherine, 2006. "Bayesian copula selection," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 809-822, November.
    11. Hua, Lei & Joe, Harry, 2012. "Tail comonotonicity: Properties, constructions, and asymptotic additivity of risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 492-503.
    12. Packham, Natalie & Kalkbrener, Michael & Overbeck, Ludger, 2014. "Default probabilities and default correlations under stress," Frankfurt School - Working Paper Series 211, Frankfurt School of Finance and Management.
    13. Melanie Frick, 2012. "Measures of multivariate asymptotic dependence and their relation to spectral expansions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(6), pages 819-831, August.
    14. Haijun Li, 2008. "Tail Dependence Comparison of Survival Marshall–Olkin Copulas," Methodology and Computing in Applied Probability, Springer, vol. 10(1), pages 39-54, March.
    15. Nan Chen & Paul Glasserman & Behzad Nouri & Markus Pelger, 2013. "CoCos, Bail-In, and Tail Risk," Working Papers 13-04, Office of Financial Research, US Department of the Treasury.
    16. Packham, Natalie & Kalkbrener, Michael & Overbeck, Ludger, 2018. "Default probabilities and default correlations under stress," IRTG 1792 Discussion Papers 2018-037, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    17. Frahm, Gabriel & Junker, Markus & Szimayer, Alexander, 2003. "Elliptical copulas: applicability and limitations," Statistics & Probability Letters, Elsevier, vol. 63(3), pages 275-286, July.
    18. Fabrizio Cipollini & Giampiero M. Gallo, 2009. "Automated Variable Selection in Vector Multiplicative Error Models," Econometrics Working Papers Archive wp2009_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    19. Bormann, Carsten & Schienle, Melanie, 2019. "Detecting structural differences in tail dependence of financial time series," Working Paper Series in Economics 122, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    20. Mendes, Beatriz V.M. & Leal, Ricardo P.C. & Carvalhal-da-Silva, Andre, 2007. "Clustering in emerging equity markets," Emerging Markets Review, Elsevier, vol. 8(3), pages 194-205, September.
    21. Nelsen, Roger B. & Quesada-Molina, José Juan & Rodri­guez-Lallena, José Antonio & Úbeda-Flores, Manuel, 2008. "On the construction of copulas and quasi-copulas with given diagonal sections," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 473-483, April.
    22. Schmidt, Rafael & Schmieder, Christian, 2007. "Modelling dynamic portfolio risk using risk drivers of elliptical processes," Discussion Paper Series 2: Banking and Financial Studies 2007,07, Deutsche Bundesbank.
    23. Frahm, Gabriel & Jaekel, Uwe, 2007. "Tyler's M-estimator, random matrix theory, and generalized elliptical distributions with applications to finance," Discussion Papers in Econometrics and Statistics 2/07, University of Cologne, Institute of Econometrics and Statistics.
    24. Kexin Li & Jianxu Liu & Yuting Xue & Sanzidur Rahman & Songsak Sriboonchitta, 2022. "Consequences of Ignoring Dependent Error Components and Heterogeneity in a Stochastic Frontier Model: An Application to Rice Producers in Northern Thailand," Agriculture, MDPI, vol. 12(8), pages 1-17, July.
    25. Ferreira, Helena & Ferreira, Marta, 2012. "Tail dependence between order statistics," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 176-192.
    26. Szabolcs Majoros & Andr'as Zempl'eni, 2018. "Multivariate stable distributions and their applications for modelling cryptocurrency-returns," Papers 1810.09521, arXiv.org.
    27. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula–Based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics, MDPI, vol. 5(2), pages 1-24, April.
    28. Schmidt, Rafael & Hrycej, Tomas & Stutzle, Eric, 2006. "Multivariate distribution models with generalized hyperbolic margins," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 2065-2096, April.
    29. Schmid, Friedrich & Schmidt, Rafael, 2007. "Multivariate conditional versions of Spearman's rho and related measures of tail dependence," Journal of Multivariate Analysis, Elsevier, vol. 98(6), pages 1123-1140, July.
    30. Hua, Lei & Joe, Harry, 2014. "Strength of tail dependence based on conditional tail expectation," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 143-159.
    31. Ghosh, Santu & Ayyala, Deepak Nag & Hellebuyck, Rafael, 2021. "Two-sample high dimensional mean test based on prepivots," Computational Statistics & Data Analysis, Elsevier, vol. 163(C).
    32. Joe, Harry & Li, Haijun, 2019. "Tail densities of skew-elliptical distributions," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 421-435.
    33. John Nolan, 2013. "Multivariate elliptically contoured stable distributions: theory and estimation," Computational Statistics, Springer, vol. 28(5), pages 2067-2089, October.
    34. Cerqueti, Roy & Lupi, Claudio, 2015. "Total positivity for a class of non-exchangeable copulas," Economics & Statistics Discussion Papers esdp15077, University of Molise, Department of Economics.
    35. Yves Dominicy & Pauliina Ilmonen & David Veredas, 2017. "Multivariate Hill Estimators," International Statistical Review, International Statistical Institute, vol. 85(1), pages 108-142, April.
    36. Koike, Takaaki & Hofert, Marius, 2021. "Modality for scenario analysis and maximum likelihood allocation," Insurance: Mathematics and Economics, Elsevier, vol. 97(C), pages 24-43.
    37. Takaaki Koike & Marius Hofert, 2020. "Modality for Scenario Analysis and Maximum Likelihood Allocation," Papers 2005.02950, arXiv.org, revised Nov 2020.
    38. Thomas Fung & Eugene Seneta, 2010. "Modelling and Estimation for Bivariate Financial Returns," International Statistical Review, International Statistical Institute, vol. 78(1), pages 117-133, April.
    39. Fantazzini, Dean, 2011. "Analysis of multidimensional probability distributions with copula functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 22(2), pages 98-134.
    40. Chan, Yin & Li, Haijun, 2008. "Tail dependence for multivariate t -copulas and its monotonicity," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 763-770, April.
    41. Jianhua Lin & Xiaohu Li, 2014. "Multivariate Generalized Marshall–Olkin Distributions and Copulas," Methodology and Computing in Applied Probability, Springer, vol. 16(1), pages 53-78, March.
    42. Kliber, Agata & Płuciennik, Piotr, 2017. "Euro or not? Vulnerability of Czech and Slovak economies to regional and international turmoil," Economic Modelling, Elsevier, vol. 60(C), pages 313-323.
    43. Frahm, Gabriel, 2006. "On the extremal dependence coefficient of multivariate distributions," Statistics & Probability Letters, Elsevier, vol. 76(14), pages 1470-1481, August.
    44. Takaaki Koike & Mihoko Minami, 2017. "Estimation of Risk Contributions with MCMC," Papers 1702.03098, arXiv.org, revised Jan 2019.
    45. Manner, Hans & Segers, Johan, 2011. "Tails of correlation mixtures of elliptical copulas," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 153-160, January.
    46. Ray-Bing Chen & Meihui Guo & Wolfgang Härdle & Shih-Feng Huang, 2008. "Independent Component Analysis Via Copula Techniques," SFB 649 Discussion Papers SFB649DP2008-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    47. Frahm, Gabriel & Junker, Markus & Schmidt, Rafael, 2005. "Estimating the tail-dependence coefficient: Properties and pitfalls," Insurance: Mathematics and Economics, Elsevier, vol. 37(1), pages 80-100, August.
    48. Hua, Lei, 2017. "On a bivariate copula with both upper and lower full-range tail dependence," Insurance: Mathematics and Economics, Elsevier, vol. 73(C), pages 94-104.
    49. Peter Albrecht, 2011. "Zur Theorie des Value at Risk-minimalen Hedges," Schmalenbach Journal of Business Research, Springer, vol. 63(1), pages 2-18, February.

Chapters

    Sorry, no citations of chapters recorded.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.