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Mauro Bernardi

Personal Details

First Name:Mauro
Middle Name:
Last Name:Bernardi
Suffix:
RePEc Short-ID:pbe788
[This author has chosen not to make the email address public]
Via del Castro Laurenziano, 9 00161 Rome ITALY

Affiliation

Dipartimento di Metodi e modelli per l'economia, il territorio e la finanza (MEMOTEF)
Facoltà di Economia
"Sapienza" Università di Roma

Roma, Italy
http://www.memotef.uniroma1.it/

:


RePEc:edi:dmrosit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. M. Bernardi & L. Petrella, 2014. "Interconnected risk contributions: an heavy-tail approach to analyse US financial sectors," Papers 1401.6408, arXiv.org, revised Apr 2014.
  2. Mauro Bernardi & Ghislaine Gayraud & Lea Petrella, 2013. "Bayesian inference for CoVaR," Papers 1306.2834, arXiv.org, revised Nov 2013.
  3. Bernardi, Mauro & Maruotti, Antonello & Lea, Petrella, 2012. "Skew mixture models for loss distributions: a Bayesian approach," MPRA Paper 39826, University Library of Munich, Germany.
  4. Bernardi, Mauro, 2012. "Risk measures for Skew Normal mixtures," MPRA Paper 39828, University Library of Munich, Germany.
  5. Bernardi, Mauro & Della Corte, Giuseppe & Proietti, Tommaso, 2008. "Extracting the Cyclical Component in Hours Worked: a Bayesian Approach," MPRA Paper 8967, University Library of Munich, Germany.

Articles

  1. Bernardi, Mauro, 2013. "Risk measures for skew normal mixtures," Statistics & Probability Letters, Elsevier, vol. 83(8), pages 1819-1824.
  2. Filippo Belloc & Mauro Bernardi & Antonello Maruotti & Lea Petrella, 2013. "A dynamic hurdle model for zeroinflated panel count data," Applied Economics Letters, Taylor & Francis Journals, vol. 20(9), pages 837-841, June.
  3. Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2012. "Skew mixture models for loss distributions: A Bayesian approach," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 617-623.
  4. Bernardi Mauro & Della Corte Giuseppe & Proietti Tommaso, 2011. "Extracting the Cyclical Component in Hours Worked," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-28, May.

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. M. Bernardi & L. Petrella, 2014. "Interconnected risk contributions: an heavy-tail approach to analyse US financial sectors," Papers 1401.6408, arXiv.org, revised Apr 2014.

    Cited by:

    1. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.

  2. Mauro Bernardi & Ghislaine Gayraud & Lea Petrella, 2013. "Bayesian inference for CoVaR," Papers 1306.2834, arXiv.org, revised Nov 2013.

    Cited by:

    1. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    2. Gabriela Anghelache & Dumitru-Cristian Oanea, 2014. "Main Romanian Commercial Banks’ Systemic Risk during Financial Crisis: a CoVar Approach," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 6(2), pages 069-080, December.

  3. Bernardi, Mauro & Maruotti, Antonello & Lea, Petrella, 2012. "Skew mixture models for loss distributions: a Bayesian approach," MPRA Paper 39826, University Library of Munich, Germany.

    Cited by:

    1. Valeria Bignozzi & Claudio Macci & Lea Petrella, 2017. "Large deviations for risk measures in finite mixture models," Papers 1710.03252, arXiv.org, revised Feb 2018.
    2. Bernardi, Mauro, 2013. "Risk measures for skew normal mixtures," Statistics & Probability Letters, Elsevier, vol. 83(8), pages 1819-1824.
    3. Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2017. "Multiple risk measures for multivariate dynamic heavy–tailed models," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 1-32.
    4. Peng, Zuoxiang & Li, Chunqiao & Nadarajah, Saralees, 2016. "Extremal properties of the skew-t distribution," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 10-19.
    5. Abu Bakar, S.A. & Hamzah, N.A. & Maghsoudi, M. & Nadarajah, S., 2015. "Modeling loss data using composite models," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 146-154.
    6. Loperfido, Nicola, 2014. "A note on the fourth cumulant of a finite mixture distribution," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 386-394.
    7. Mauro Bernardi & Ghislaine Gayraud & Lea Petrella, 2013. "Bayesian inference for CoVaR," Papers 1306.2834, arXiv.org, revised Nov 2013.
    8. Tarpey, Thaddeus & Loperfido, Nicola, 2015. "Self-consistency and a generalized principal subspace theorem," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 27-37.
    9. Farias, Rafael B.A. & Montoril, Michel H. & Andrade, José A.A., 2016. "Bayesian inference for extreme quantiles of heavy tailed distributions," Statistics & Probability Letters, Elsevier, vol. 113(C), pages 103-107.
    10. Bhati, Deepesh & Ravi, Sreenivasan, 2018. "On generalized log-Moyal distribution: A new heavy tailed size distribution," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 247-259.

  4. Bernardi, Mauro, 2012. "Risk measures for Skew Normal mixtures," MPRA Paper 39828, University Library of Munich, Germany.

    Cited by:

    1. Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2017. "Multiple risk measures for multivariate dynamic heavy–tailed models," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 1-32.
    2. Bernardi Mauro & Roy Cerqueti & Arsen Palestini, 2016. "Allocation of risk capital in a cost cooperative game induced by a modified Expected Shortfall," Papers 1608.02365, arXiv.org.
    3. Markus Haas, 2012. "A Note on the Moments of the Skew-Normal Distribution," Economics Bulletin, AccessEcon, vol. 32(4), pages 3306-3312.
    4. Jiang, Chun-Fu & Peng, Hong-Yi & Yang, Yu-Kuan, 2016. "Tail variance of portfolio under generalized Laplace distribution," Applied Mathematics and Computation, Elsevier, vol. 282(C), pages 187-203.
    5. Mauro Bernardi & Ghislaine Gayraud & Lea Petrella, 2013. "Bayesian inference for CoVaR," Papers 1306.2834, arXiv.org, revised Nov 2013.
    6. Haas, Markus, 2016. "A note on optimal portfolios under regime-switching," Annual Conference 2016 (Augsburg): Demographic Change 145493, Verein für Socialpolitik / German Economic Association.
    7. Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2012. "Skew mixture models for loss distributions: A Bayesian approach," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 617-623.

  5. Bernardi, Mauro & Della Corte, Giuseppe & Proietti, Tommaso, 2008. "Extracting the Cyclical Component in Hours Worked: a Bayesian Approach," MPRA Paper 8967, University Library of Munich, Germany.

    Cited by:

    1. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2012. "Persistence and Cycles in US Hours Worked," Discussion Papers of DIW Berlin 1200, DIW Berlin, German Institute for Economic Research.

Articles

  1. Bernardi, Mauro, 2013. "Risk measures for skew normal mixtures," Statistics & Probability Letters, Elsevier, vol. 83(8), pages 1819-1824.
    See citations under working paper version above.
  2. Filippo Belloc & Mauro Bernardi & Antonello Maruotti & Lea Petrella, 2013. "A dynamic hurdle model for zeroinflated panel count data," Applied Economics Letters, Taylor & Francis Journals, vol. 20(9), pages 837-841, June.

    Cited by:

    1. Ting Wang & Jiancang Zhuang & Kazushige Obara & Hiroshi Tsuruoka, 2017. "Hidden Markov modelling of sparse time series from non-volcanic tremor observations," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 691-715, August.

  3. Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2012. "Skew mixture models for loss distributions: A Bayesian approach," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 617-623.
    See citations under working paper version above.
  4. Bernardi Mauro & Della Corte Giuseppe & Proietti Tommaso, 2011. "Extracting the Cyclical Component in Hours Worked," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-28, May.

    Cited by:

    1. Marczak, Martyna & Proietti, Tommaso & Grassi, Stefano, 2018. "A data-cleaning augmented Kalman filter for robust estimation of state space models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 107-123.

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 5 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-RMG: Risk Management (4) 2012-07-14 2012-07-14 2013-06-16 2014-02-02
  2. NEP-ECM: Econometrics (3) 2012-07-14 2012-07-14 2013-06-16
  3. NEP-BAN: Banking (2) 2012-07-14 2013-06-16
  4. NEP-FMK: Financial Markets (1) 2014-02-02
  5. NEP-IAS: Insurance Economics (1) 2014-02-02
  6. NEP-MAC: Macroeconomics (1) 2008-06-13
  7. NEP-ORE: Operations Research (1) 2008-06-13

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