IDEAS home Printed from https://ideas.repec.org/f/pli706.html
   My authors  Follow this author

Daniël Linders
(Daniel Linders)

Personal Details

First Name:Daniel
Middle Name:
Last Name:Linders
Suffix:
RePEc Short-ID:pli706
[This author has chosen not to make the email address public]
http://www.herdbehaviorindex.com

Affiliation

Faculteit Economie en Bedrijfswetenschappen
KU Leuven

Leuven, Belgium
https://feb.kuleuven.ac.be/
RePEc:edi:fekulbe (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Daniël Linders & Fan Yang, 2016. "Aggregating risks with partial dependence information," Working Papers Department of Accountancy, Finance and Insurance (AFI), Leuven 544634, KU Leuven, Faculty of Economics and Business (FEB), Department of Accountancy, Finance and Insurance (AFI), Leuven.
  2. Daniël Linders & Jan Dhaene & Wim Schoutens, 2015. "Option prices and model-free measurement of implied herd behavior in stock markets," Working Papers Department of Accountancy, Finance and Insurance (AFI), Leuven 485228, KU Leuven, Faculty of Economics and Business (FEB), Department of Accountancy, Finance and Insurance (AFI), Leuven.

Articles

  1. Florence Guillaume & Daniël Linders, 2015. "Stochastic modelling of herd behaviour indices," Quantitative Finance, Taylor & Francis Journals, vol. 15(12), pages 1963-1977, December.
  2. Dhaene, Jan & Linders, Daniël & Schoutens, Wim & Vyncke, David, 2012. "The Herd Behavior Index: A new measure for the implied degree of co-movement in stock markets," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 357-370.
  3. Goovaerts, Marc & Linders, Daniël & Van Weert, Koen & Tank, Fatih, 2012. "On the interplay between distortion, mean value and Haezendonck–Goovaerts risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 51(1), pages 10-18.

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. Daniël Linders & Jan Dhaene & Wim Schoutens, 2015. "Option prices and model-free measurement of implied herd behavior in stock markets," Working Papers Department of Accountancy, Finance and Insurance (AFI), Leuven 485228, KU Leuven, Faculty of Economics and Business (FEB), Department of Accountancy, Finance and Insurance (AFI), Leuven.

    Cited by:

    1. Lee Woojoo & Ahn Jae Youn, 2017. "Measuring herd behavior: properties and pitfalls," Dependence Modeling, De Gruyter, vol. 5(1), pages 316-329, December.

Articles

  1. Florence Guillaume & Daniël Linders, 2015. "Stochastic modelling of herd behaviour indices," Quantitative Finance, Taylor & Francis Journals, vol. 15(12), pages 1963-1977, December.

    Cited by:

    1. Escobar, Marcos & Fang, Lin, 2020. "Stochastic volatility models for the implied correlation index," Finance Research Letters, Elsevier, vol. 35(C).

  2. Dhaene, Jan & Linders, Daniël & Schoutens, Wim & Vyncke, David, 2012. "The Herd Behavior Index: A new measure for the implied degree of co-movement in stock markets," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 357-370.

    Cited by:

    1. Mohamed Es-Sanoun & Jude Gohou & Mounir Benboubker, 2023. "Testing of Herd Behavior In african Stock Markets During COVID-19 Pandemic [Essai de vérification du comportement mimétique dans les marchés boursiers africains au cours de la crise de covid-19]," Post-Print hal-04144289, HAL.
    2. 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.
    3. Bernard, Carole & Jiang, Xiao & Wang, Ruodu, 2014. "Risk aggregation with dependence uncertainty," Insurance: Mathematics and Economics, Elsevier, vol. 54(C), pages 93-108.
    4. Li, Tong & Chen, Hui & Liu, Wei & Yu, Guang & Yu, Yongtian, 2023. "Understanding the role of social media sentiment in identifying irrational herding behavior in the stock market," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 163-179.
    5. Park, Beum-Jo & Kim, Myung-Joong, 2017. "A Dynamic Measure of Intentional Herd Behavior in Financial Markets," MPRA Paper 82025, University Library of Munich, Germany.
    6. Rodríguez, Jhan & Bárdossy, András, 2015. "Entropy measure for the quantification of upper quantile interdependence in multivariate distributions," Journal of Multivariate Analysis, Elsevier, vol. 140(C), pages 317-324.
    7. Roberto Daluiso & Massimo Morini, 2017. "Hedging efficiently under correlation," Quantitative Finance, Taylor & Francis Journals, vol. 17(10), pages 1535-1547, October.
    8. Cheung, K.C. & Chong, W.F. & Yam, S.C.P., 2015. "The optimal insurance under disappointment theories," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 77-90.
    9. Puput Tri Komalasari & Marwan Asri & Bernardinus M. Purwanto & Bowo Setiyono, 2022. "Herding behaviour in the capital market: What do we know and what is next?," Management Review Quarterly, Springer, vol. 72(3), pages 745-787, September.
    10. Cheung, Ka Chun & Lo, Ambrose, 2013. "General lower bounds on convex functionals of aggregate sums," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 884-896.
    11. Mainik Georg & Schaanning Eric, 2014. "On dependence consistency of CoVaRand some other systemic risk measures," Statistics & Risk Modeling, De Gruyter, vol. 31(1), pages 49-77, March.
    12. Daniël Linders & Jan Dhaene & Wim Schoutens, 2015. "Option prices and model-free measurement of implied herd behavior in stock markets," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(02), pages 1-35.
    13. Lee Woojoo & Ahn Jae Youn, 2017. "Measuring herd behavior: properties and pitfalls," Dependence Modeling, De Gruyter, vol. 5(1), pages 316-329, December.
    14. Huang, Chuangxia & Cai, Yaqian & Yang, Xiaoguang & Deng, Yanchen & Yang, Xin, 2023. "Laplacian-energy-like measure: Does it improve the Cross-Sectional Absolute Deviation herding model?," Economic Modelling, Elsevier, vol. 127(C).
    15. Ching-Hsue Cheng & Ssu-Hsiang Wang, 2015. "A quarterly time-series classifier based on a reduced-dimension generated rules method for identifying financial distress," Quantitative Finance, Taylor & Francis Journals, vol. 15(12), pages 1979-1994, December.
    16. Wang, Ze & Gao, Xiangyun & An, Haizhong & Tang, Renwu & Sun, Qingru, 2020. "Identifying influential energy stocks based on spillover network," International Review of Financial Analysis, Elsevier, vol. 68(C).
    17. Jae Youn Ahn, 2015. "Negative Dependence Concept in Copulas and the Marginal Free Herd Behavior Index," Papers 1503.03180, arXiv.org.
    18. Escobar, Marcos & Fang, Lin, 2020. "Stochastic volatility models for the implied correlation index," Finance Research Letters, Elsevier, vol. 35(C).
    19. Changki Kim & Yangho Choi & Woojoo Lee & Jae Youn Ahn, 2013. "Analyzing Herd Behavior in Global Stock Markets: An Intercontinental Comparison," Papers 1308.3966, arXiv.org.
    20. Chaoubi, Ihsan & Cossette, Hélène & Gadoury, Simon-Pierre & Marceau, Etienne, 2020. "On sums of two counter-monotonic risks," Insurance: Mathematics and Economics, Elsevier, vol. 92(C), pages 47-60.
    21. Samanthi, Ranadeera Gamage Madhuka & Wei, Wei & Brazauskas, Vytaras, 2016. "Ordering Gini indexes of multivariate elliptical risks," Insurance: Mathematics and Economics, Elsevier, vol. 68(C), pages 84-91.
    22. Aleksy Leeuwenkamp & Wentao Hu, 2023. "New general dependence measures: construction, estimation and application to high-frequency stock returns," Papers 2309.00025, arXiv.org.

  3. Goovaerts, Marc & Linders, Daniël & Van Weert, Koen & Tank, Fatih, 2012. "On the interplay between distortion, mean value and Haezendonck–Goovaerts risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 51(1), pages 10-18.

    Cited by:

    1. Jaume Belles‐Sampera & Montserrat Guillén & Miguel Santolino, 2014. "Beyond Value‐at‐Risk: GlueVaR Distortion Risk Measures," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 121-134, January.
    2. Niushan Gao & Cosimo Munari & Foivos Xanthos, 2019. "Stability properties of Haezendonck-Goovaerts premium principles," Papers 1909.10735, arXiv.org, revised Aug 2020.
    3. Jaume Belles-Sampera & José M. Merigó & Montserrat Guillén & Miguel Santolino, 2012. "The connection between distortion risk measures and ordered weighted averaging operators," IREA Working Papers 201201, University of Barcelona, Research Institute of Applied Economics, revised Jan 2012.
    4. Alois Pichler, 2013. "Premiums And Reserves, Adjusted By Distortions," Papers 1304.0490, arXiv.org.
    5. Xun, Li & Zhou, Yangzhi & Zhou, Yong, 2019. "A generalization of Expected Shortfall based capital allocation," Statistics & Probability Letters, Elsevier, vol. 146(C), pages 193-199.
    6. Liu, Qing & Peng, Liang & Wang, Xing, 2017. "Haezendonck–Goovaerts risk measure with a heavy tailed loss," Insurance: Mathematics and Economics, Elsevier, vol. 76(C), pages 28-47.
    7. Cheung, Ka Chun & Lo, Ambrose, 2013. "General lower bounds on convex functionals of aggregate sums," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 884-896.
    8. Jaume Belles-Sampera & Montserrat Guillén & Miguel Santolino, 2013. "“Beyond Value-at-Risk: GlueVaR Distortion Risk Measures”," IREA Working Papers 201302, University of Barcelona, Research Institute of Applied Economics, revised Feb 2013.
    9. Mao, Tiantian & Hu, Taizhong, 2012. "Second-order properties of the Haezendonck–Goovaerts risk measure for extreme risks," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 333-343.
    10. Belles-Sampera, Jaume & Guillen, Montserrat & Santolino, Miguel, 2016. "What attitudes to risk underlie distortion risk measure choices?," Insurance: Mathematics and Economics, Elsevier, vol. 68(C), pages 101-109.
    11. Asimit, Alexandru V. & Badescu, Alexandru M. & Verdonck, Tim, 2013. "Optimal risk transfer under quantile-based risk measurers," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 252-265.
    12. Jaume Belles-Sampera & Montserrat Guillén & Miguel Santolino, 2015. "What attitudes to risk underlie distortion risk measure choices?," Working Papers 2015-05, Universitat de Barcelona, UB Riskcenter.
    13. Asimit, Alexandru V. & Badescu, Alexandru M. & Cheung, Ka Chun, 2013. "Optimal reinsurance in the presence of counterparty default risk," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 690-697.
    14. Bellini, Fabio & Klar, Bernhard & Müller, Alfred & Rosazza Gianin, Emanuela, 2014. "Generalized quantiles as risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 54(C), pages 41-48.
    15. Tang, Qihe & Yang, Fan, 2014. "Extreme value analysis of the Haezendonck–Goovaerts risk measure with a general Young function," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 311-320.
    16. Gao, Niushan & Munari, Cosimo & Xanthos, Foivos, 2020. "Stability properties of Haezendonck–Goovaerts premium principles," Insurance: Mathematics and Economics, Elsevier, vol. 94(C), pages 94-99.
    17. Wang, Xing & Peng, Liang, 2016. "Inference for intermediate Haezendonck–Goovaerts risk measure," Insurance: Mathematics and Economics, Elsevier, vol. 68(C), pages 231-240.
    18. Asimit, Alexandru V. & Chi, Yichun & Hu, Junlei, 2015. "Optimal non-life reinsurance under Solvency II Regime," Insurance: Mathematics and Economics, Elsevier, vol. 65(C), pages 227-237.
    19. Guillén, Montserrat & Sarabia, José María & Prieto, Faustino, 2013. "Simple risk measure calculations for sums of positive random variables," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 273-280.
    20. Bellini, Fabio & Rosazza Gianin, Emanuela, 2012. "Haezendonck–Goovaerts risk measures and Orlicz quantiles," Insurance: Mathematics and Economics, Elsevier, vol. 51(1), pages 107-114.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 2 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-CFN: Corporate Finance (1) 2015-04-25
  2. NEP-GER: German Papers (1) 2016-07-16

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Daniel Linders
(Daniel Linders) should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.