Laurens de Haan

Personal Details

First Name:	Laurens
Middle Name:
Last Name:	de Haan
Suffix:
RePEc Short-ID:	pde531
	[This author has chosen not to make the email address public]

Affiliation

Departement Econometrie & Operations Research
School of Economics and Management
Universiteit van Tilburg

Tilburg, Netherlands
https://www.tilburguniversity.edu/about/schools/economics-and-management/organization/departments/eor
RePEc:edi:exkubnl (more details at EDIRC)

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. Jon Danielsson & Lerby Ergun & Laurens de Haan & Casper G. de Vries, 2019. "Tail Index Estimation: Quantile-Driven Threshold Selection," Staff Working Papers 19-28, Bank of Canada.
   • Danielsson, Jon & Ergun, Lerby M. & Haan, Laurens de & Vries, Casper G. de, 2016. "Tail index estimation: quantile driven threshold selection," LSE Research Online Documents on Economics 66193, London School of Economics and Political Science, LSE Library.

   Cited by:

   1. Małgorzata Just & Krzysztof Echaust, 2021. "An Optimal Tail Selection in Risk Measurement," Risks, MDPI, vol. 9(4), pages 1-16, April.
   2. Krzysztof Echaust & Małgorzata Just, 2020. "Value at Risk Estimation Using the GARCH-EVT Approach with Optimal Tail Selection," Mathematics, MDPI, vol. 8(1), pages 1-24, January.
   3. Tjeerd de Vries & Alexis Akira Toda, 2021. "Capital and Labor Income Pareto Exponents across Time and Space," LIS Working papers 794, LIS Cross-National Data Center in Luxembourg.
      • Tjeerd de Vries & Alexis Akira Toda, 2020. "Capital and Labor Income Pareto Exponents across Time and Space," Papers 2006.03441, arXiv.org, revised Jun 2021.
      • Tjeerd de Vries & Alexis Akira Toda, 2022. "Capital and Labor Income Pareto Exponents Across Time and Space," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(4), pages 1058-1078, December.
   4. Matthias Schnaubelt & Jonas Rende & Christopher Krauss, 2019. "Testing Stylized Facts of Bitcoin Limit Order Books," JRFM, MDPI, vol. 12(1), pages 1-30, February.
   5. Krzysztof Echaust & Małgorzata Just, 2021. "Tail Dependence between Crude Oil Volatility Index and WTI Oil Price Movements during the COVID-19 Pandemic," Energies, MDPI, vol. 14(14), pages 1-21, July.
   6. Jon Danielsson & Lerby Ergun & Casper G. de Vries, 2018. "Challenges in Implementing Worst-Case Analysis," Staff Working Papers 18-47, Bank of Canada.
   7. Hoga, Yannick, 2021. "The uncertainty in extreme risk forecasts from covariate-augmented volatility models," International Journal of Forecasting, Elsevier, vol. 37(2), pages 675-686.
   8. Lerby Ergun, 2019. "Extreme Downside Risk in Asset Returns," Staff Working Papers 19-46, Bank of Canada.
   9. Natalia Markovich & Maksim Ryzhov & Marijus Vaičiulis, 2022. "Tail Index Estimation of PageRanks in Evolving Random Graphs," Mathematics, MDPI, vol. 10(16), pages 1-26, August.
   10. Echaust, Krzysztof, 2021. "Asymmetric tail dependence between stock market returns and implied volatility," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
   11. Ergun, Lerby M., 2016. "Disaster and fortune risk in asset returns," LSE Research Online Documents on Economics 66194, London School of Economics and Political Science, LSE Library.

Articles

1. M. Ivette Gomes & Laurens De Haan & Lígia Henriques Rodrigues, 2008. "Tail index estimation for heavy‐tailed models: accommodation of bias in weighted log‐excesses," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(1), pages 31-52, February.

   Cited by:

   1. Cai, J., 2012. "Estimation concerning risk under extreme value conditions," Other publications TiSEM a92b089f-bc4c-41c2-b297-c, Tilburg University, School of Economics and Management.
   2. Fátima Brilhante, M. & Ivette Gomes, M. & Pestana, Dinis, 2013. "A simple generalisation of the Hill estimator," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 518-535.
   3. Wendy Shinyie & Noriszura Ismail & Abdul Jemain, 2014. "Semi-parametric Estimation Based on Second Order Parameter for Selecting Optimal Threshold of Extreme Rainfall Events," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3489-3514, September.
   4. Beirlant, Jan & Escobar-Bach, Mikael & Goegebeur, Yuri & Guillou, Armelle, 2016. "Bias-corrected estimation of stable tail dependence function," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 453-466.
   5. Gomes, M. Ivette & Pestana, Dinis & Caeiro, Frederico, 2009. "A note on the asymptotic variance at optimal levels of a bias-corrected Hill estimator," Statistics & Probability Letters, Elsevier, vol. 79(3), pages 295-303, February.
   6. Dierckx, Goedele & Goegebeur, Yuri & Guillou, Armelle, 2013. "An asymptotically unbiased minimum density power divergence estimator for the Pareto-tail index," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 70-86.
   7. Wager, Stefan, 2014. "Subsampling extremes: From block maxima to smooth tail estimation," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 335-353.
   8. Gomes, M. Ivette & Brilhante, M. Fátima & Caeiro, Frederico & Pestana, Dinis, 2015. "A new partially reduced-bias mean-of-order p class of extreme value index estimators," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 223-237.
   9. M. Ivette Gomes & Armelle Guillou, 2015. "Extreme Value Theory and Statistics of Univariate Extremes: A Review," International Statistical Review, International Statistical Institute, vol. 83(2), pages 263-292, August.
   10. Maarten R C van Oordt & Chen Zhou, 2019. "Estimating Systematic Risk under Extremely Adverse Market Conditions," Journal of Financial Econometrics, Oxford University Press, vol. 17(3), pages 432-461.
       • Maarten van Oordt & Chen Zhou, 2016. "Estimating Systematic Risk Under Extremely Adverse Market Conditions," Staff Working Papers 16-22, Bank of Canada.
   11. Ye, Wuyi & Jiang, Kunliang & Liu, Xiaoquan, 2021. "Financial contagion and the TIR-MIDAS model," Finance Research Letters, Elsevier, vol. 39(C).
   12. Gaoge Hu & Shesheng Gao & Yongmin Zhong & Chengfan Gu, 2014. "Random weighting estimation of stable exponent," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(4), pages 451-468, May.
   13. Enrico Biffis & Erik Chavez, 2014. "Tail Risk in Commercial Property Insurance," Risks, MDPI, vol. 2(4), pages 1-18, September.
   14. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
   15. Gomes, M. Ivette & Henriques-Rodrigues, Lígia, 2016. "Competitive estimation of the extreme value index," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 128-135.
   16. Minkah, Richard & de Wet, Tertius & Ghosh, Abhik, 2022. "Robust Extreme Quantile Estimation for Pareto-Type tails through an Exponential Regression Model," AfricArxiv hf7vk, Center for Open Science.
   17. Frederico Caeiro & M. Gomes, 2009. "Semi-parametric second-order reduced-bias high quantile estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(2), pages 392-413, August.
   18. 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.
   19. Laurens Haan & Cécile Mercadier & Chen Zhou, 2016. "Adapting extreme value statistics to financial time series: dealing with bias and serial dependence," Finance and Stochastics, Springer, vol. 20(2), pages 321-354, April.
   20. Tertius de Wet & Yuri Goegebeur & Armelle Guillou, 2012. "Weighted Moment Estimators for the Second Order Scale Parameter," Methodology and Computing in Applied Probability, Springer, vol. 14(3), pages 753-783, September.
   21. Yuri Goegebeur & Tertius de Wet, 2012. "Estimation of the third-order parameter in extreme value statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 330-354, June.
   22. Moosup Kim & Sangyeol Lee, 2016. "On the tail index inference for heavy-tailed GARCH-type innovations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(2), pages 237-267, April.
   23. Chavez-Demoulin, Valérie & Guillou, Armelle, 2018. "Extreme quantile estimation for β-mixing time series and applications," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 59-74.
   24. Araújo Santos, Paulo & Fraga Alves, Isabel & Hammoudeh, Shawkat, 2013. "High quantiles estimation with Quasi-PORT and DPOT: An application to value-at-risk for financial variables," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 487-496.
   25. Emanuele Taufer & Flavio Santi & Pier Luigi Novi Inverardi & Giuseppe Espa & Maria Michela Dickson, 2020. "Extreme Value Index Estimation by Means of an Inequality Curve," Mathematics, MDPI, vol. 8(10), pages 1-17, October.
   26. Moosup Kim & Sangyeol Lee, 2017. "Estimation of the tail exponent of multivariate regular variation," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(5), pages 945-968, October.

2. 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.

   Cited by:

   1. Einmahl, John H. J. & Krajina, Andrea & Segers, Johan, 2012. "An M-estimator for tail dependence in arbitrary dimensions," LIDAM Reprints ISBA 2012035, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • EINMAHL, John H.J. & KRAJINA, Andrea & Segers, Johan, 2011. "An M-Estimator For Tail Dependence In Arbitrary Dimensions," LIDAM Discussion Papers ISBA 2011005, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • Einmahl, J.H.J. & Krajina, A. & Segers, J., 2011. "An M-Estimator for Tail Dependence in Arbitrary Dimensions," Other publications TiSEM 27508aa0-9825-4d9e-b1f4-1, Tilburg University, School of Economics and Management.
      • Einmahl, J.H.J. & Krajina, A. & Segers, J., 2011. "An M-Estimator for Tail Dependence in Arbitrary Dimensions," Discussion Paper 2011-013, Tilburg University, Center for Economic Research.
      • Einmahl, J.H.J. & Krajina, A. & Segers, J., 2012. "An M-estimator for tail dependence in arbitrary dimensions," Other publications TiSEM 7d447c58-3e8f-4387-b36b-e, Tilburg University, School of Economics and Management.
   2. Carsten Bormann & Julia Schaumburg & Melanie Schienle, 2016. "Beyond Dimension two: A Test for Higher-Order Tail Risk," Journal of Financial Econometrics, Oxford University Press, vol. 14(3), pages 552-580.
      • Carsten Bormann & Melanie Schienle & Julia Schaumburg, 2014. "Beyond dimension two: A test for higher-order tail risk," SFB 649 Discussion Papers SFB649DP2014-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
      • Bormann, Carsten & Schaumburg, Julia & Schienle, Melanie, 2016. "Beyond dimension two: A test for higher-order tail risk," Working Paper Series in Economics 80, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
   3. 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).
   4. Gardes, Laurent & Girard, Stéphane, 2015. "Nonparametric estimation of the conditional tail copula," Journal of Multivariate Analysis, Elsevier, vol. 137(C), pages 1-16.
   5. 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.
   6. Einmahl, J.H.J. & Segers, J.J.J., 2009. "Maximum empirical likelihood estimation of the spectral measure of an extreme-value distribution," Other publications TiSEM ffef2e15-c4a8-471f-b730-1, Tilburg University, School of Economics and Management.
      • Einmahl, J.H.J. & Segers, J.J.J., 2008. "Maximum Empirical Likelihood Estimation of the Spectral Measure of an Extreme Value Distribution," Other publications TiSEM e9340b9a-fe69-4e77-8594-8, Tilburg University, School of Economics and Management.
      • Einmahl, J.H.J. & Segers, J.J.J., 2008. "Maximum Empirical Likelihood Estimation of the Spectral Measure of an Extreme Value Distribution," Discussion Paper 2008-42, Tilburg University, Center for Economic Research.
   7. Rootzen, Holger & Segers, Johan & Wadsworth, Jenny, 2016. "Multivariate peaks over thresholds models," LIDAM Discussion Papers ISBA 2016018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
   8. Bücher Axel, 2014. "A note on nonparametric estimation of bivariate tail dependence," Statistics & Risk Modeling, De Gruyter, vol. 31(2), pages 1-12, June.
   9. Einmahl, J.H.J. & Krajina, A. & Segers, J.J.J., 2007. "A Method of Moments Estimator of Tail Dependence," Discussion Paper 2007-80, Tilburg University, Center for Economic Research.
      • Einmahl, J.H.J. & Krajina, A. & Segers, J.J.J., 2007. "A Method of Moments Estimator of Tail Dependence," Other publications TiSEM 6ee60ab8-3c01-4bd9-aa5e-7, Tilburg University, School of Economics and Management.
      • Einmahl, J.H.J. & Krajina, A. & Segers, J.J.J., 2008. "A method of moments estimator of tail dependence," Other publications TiSEM 448fd556-b3e0-4fb0-bcb7-8, Tilburg University, School of Economics and Management.
   10. Benchaira, Souad & Meraghni, Djamel & Necir, Abdelhakim, 2015. "On the asymptotic normality of the extreme value index for right-truncated data," Statistics & Probability Letters, Elsevier, vol. 107(C), pages 378-384.
   11. Krajina, A., 2010. "An M-estimator of multivariate tail dependence," Other publications TiSEM 66518e07-db9a-4446-81be-c, Tilburg University, School of Economics and Management.
   12. Clément Dombry & Michael Falk & Maximilian Zott, 2019. "On Functional Records and Champions," Journal of Theoretical Probability, Springer, vol. 32(3), pages 1252-1277, September.
   13. Carsten Bormann & Melanie Schienle & Julia Schaumburg, 2014. "A Test for the Portion of Bivariate Dependence in Multivariate Tail Risk," Tinbergen Institute Discussion Papers 14-024/III, Tinbergen Institute, revised 23 Jun 2014.
   14. 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.

3. Drees, Holger & de Haan, Laurens & Li, Deyuan, 2003. "On large deviation for extremes," Statistics & Probability Letters, Elsevier, vol. 64(1), pages 51-62, August.

   Cited by:

   1. Feng, Bo & Chen, Shouquan, 2015. "On large deviations of extremes under power normalization," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 27-35.
   2. 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.

4. de Haan, L. & Pereira, T. Themido, 1999. "Estimating the index of a stable distribution," Statistics & Probability Letters, Elsevier, vol. 41(1), pages 39-55, January.

   Cited by:

   1. J. Danielsson & L. de Haan & L. Peng & C.G. de Vries, 1997. "Using a Bootstrap Method to choose the Sample Fraction in Tail Index Estimation," Tinbergen Institute Discussion Papers 97-016/4, Tinbergen Institute.
      • Danielsson, J. & de Haan, L. & Peng, L. & de Vries, C. G., 2001. "Using a Bootstrap Method to Choose the Sample Fraction in Tail Index Estimation," Journal of Multivariate Analysis, Elsevier, vol. 76(2), pages 226-248, February.
      • Daníelsson, J. & de Haan, L.F.M. & Peng, L. & de Vries, C.G., 2000. "Using a bootstrap method to choose the sample fraction in tail index estimation," Econometric Institute Research Papers EI 2000-19/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
   2. Zhao, Zhibiao & Wu, Wei Biao, 2009. "Nonparametric inference of discretely sampled stable Lévy processes," Journal of Econometrics, Elsevier, vol. 153(1), pages 83-92, November.
   3. Igor Fedotenkov, 2020. "A Review of More than One Hundred Pareto-Tail Index Estimators," Statistica, Department of Statistics, University of Bologna, vol. 80(3), pages 245-299.
      • Fedotenkov, Igor, 2018. "A review of more than one hundred Pareto-tail index estimators," MPRA Paper 90072, University Library of Munich, Germany.
   4. Jon Danielsson & Lerby Ergun & Laurens de Haan & Casper G. de Vries, 2019. "Tail Index Estimation: Quantile-Driven Threshold Selection," Staff Working Papers 19-28, Bank of Canada.
      • Danielsson, Jon & Ergun, Lerby M. & Haan, Laurens de & Vries, Casper G. de, 2016. "Tail index estimation: quantile driven threshold selection," LSE Research Online Documents on Economics 66193, London School of Economics and Political Science, LSE Library.
   5. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
   6. Ayoub Ammy-Driss & Matthieu Garcin, 2021. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Working Papers hal-02903655, HAL.
   7. Ercan Balaban & Jamal Ouenniche & Danae Politou, 2005. "A note on return distribution of UK stock indices," Applied Economics Letters, Taylor & Francis Journals, vol. 12(9), pages 573-576.
   8. Ayoub Ammy-Driss & Matthieu Garcin, 2020. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Papers 2007.10727, arXiv.org, revised Nov 2021.
   9. Laurens F.M. de Haan & Liang Peng & H. Iglesias Pereira, 1997. "Approximation by Penultimate Stable Laws," Tinbergen Institute Discussion Papers 97-100/4, Tinbergen Institute.
   10. Jaap Geluk & Liang Peng & Casper G. de Vries, 1999. "Convolutions of Heavy Tailed Random Variables and Applications to Portfolio Diversification and MA(1) Time Series," Tinbergen Institute Discussion Papers 99-088/2, Tinbergen Institute.
   11. Gaoge Hu & Shesheng Gao & Yongmin Zhong & Chengfan Gu, 2014. "Random weighting estimation of stable exponent," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(4), pages 451-468, May.
   12. Geluk, J. L. & Peng, Liang, 2000. "An adaptive optimal estimate of the tail index for MA(l) time series," Statistics & Probability Letters, Elsevier, vol. 46(3), pages 217-227, February.
   13. Allen, Michael R. & Datta, Somnath, 1999. "Estimation of the index parameter for autoregressive data using the estimated innovations," Statistics & Probability Letters, Elsevier, vol. 41(3), pages 315-324, February.
   14. John Goddard & Enrico Onali, 2014. "Self-affinity in financial asset returns," Papers 1401.7170, arXiv.org.
       • Goddard, John & Onali, Enrico, 2012. "Self-affinity in financial asset returns," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 1-11.
   15. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
   16. Ma, Yaolan & Jiang, Yuexiang & Huang, Wei, 2018. "Empirical likelihood based inference for conditional Pareto-type tail index," Statistics & Probability Letters, Elsevier, vol. 134(C), pages 114-121.
   17. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
   18. Groenendijk, Patrick A. & Lucas, Andre & de Vries, Casper G., 1995. "A note on the relationship between GARCH and symmetric stable processes," Journal of Empirical Finance, Elsevier, vol. 2(3), pages 253-264, September.
   19. Brito, Margarida & Moreira Freitas, Ana Cristina, 2003. "Limiting behaviour of a geometric-type estimator for tail indices," Insurance: Mathematics and Economics, Elsevier, vol. 33(2), pages 211-226, October.
   20. Osman Doğan & Süleyman Taşpınar & Anil K. Bera, 2021. "Bayesian estimation of stochastic tail index from high-frequency financial data," Empirical Economics, Springer, vol. 61(5), pages 2685-2711, November.

5. de Haan, L. & Peng, L., 1997. "Rates of Convergence for Bivariate Extremes," Journal of Multivariate Analysis, Elsevier, vol. 61(2), pages 195-230, May.

   Cited by:

   1. Falk, Michael & Reiss, Rolf Dieter, 2002. "A characterization of the rate of convergence in bivariate extreme value models," Statistics & Probability Letters, Elsevier, vol. 59(4), pages 341-351, October.
   2. Laurens F.M. de Haan & Liang Peng & T.T. Pereira, 1997. "A Bootstrap-based Method to Achieve Optimality in Estimating the Extreme-value Index," Tinbergen Institute Discussion Papers 97-099/4, Tinbergen Institute.
   3. Falk, Michael & Reiss, Rolf-Dieter, 2005. "On Pickands coordinates in arbitrary dimensions," Journal of Multivariate Analysis, Elsevier, vol. 92(2), pages 426-453, February.
   4. Ulrich Horst & Wei Xu, 2024. "Functional Limit Theorems for Hawkes Processes," Papers 2401.11495, arXiv.org.
   5. Geluk, J. & de Haan, L. & Resnick, S. & Starica, C., 1997. "Second-order regular variation, convolution and the central limit theorem," Stochastic Processes and their Applications, Elsevier, vol. 69(2), pages 139-159, September.

6. de Haan, L. & Omey, E. & Resnick, S., 1984. "Domains of attraction and regular variation in IRd," Journal of Multivariate Analysis, Elsevier, vol. 14(1), pages 17-33, February.

   Cited by:

   1. Omey, Edward & Vesilo, R., 2009. "Random Sums of Random Variables and Vectors," Working Papers 2009/09, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
   2. Yun, Seokhoon, 1997. "On Domains of Attraction of Multivariate Extreme Value Distributions under Absolute Continuity," Journal of Multivariate Analysis, Elsevier, vol. 63(2), pages 277-295, November.
   3. Peng, Liang, 2002. "Asymptotic expansions of densities of sums of random vectors without third moment," Statistics & Probability Letters, Elsevier, vol. 58(2), pages 167-174, June.
   4. Vysotsky, Vladislav, 2010. "On the probability that integrated random walks stay positive," Stochastic Processes and their Applications, Elsevier, vol. 120(7), pages 1178-1193, July.
   5. Mallor, F. & Omey, E. & Santos, J., 2007. "Multivariate weighted renewal functions," Journal of Multivariate Analysis, Elsevier, vol. 98(1), pages 30-39, January.
   6. Tiandong Wang & Sidney I. Resnick, 2018. "Multivariate Regular Variation of Discrete Mass Functions with Applications to Preferential Attachment Networks," Methodology and Computing in Applied Probability, Springer, vol. 20(3), pages 1029-1042, September.

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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 1 paper 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 (1) 2019-08-12

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