IDEAS home Printed from https://ideas.repec.org/f/pda322.html
   My authors  Follow this author

Luciana Dalla Valle

Personal Details

First Name:Luciana
Middle Name:
Last Name:Dalla Valle
Suffix:
RePEc Short-ID:pda322
[This author has chosen not to make the email address public]
Terminal Degree:2002 Business School; University of Plymouth (from RePEc Genealogy)

Affiliation

Plymouth University

http://www.plymouth.ac.uk/
UK, Plymouth

Research output

as
Jump to: Working papers Articles

Working papers

  1. Luciana Dalla Valle & Fabrizio Leisen & Luca Rossini, 2016. "Bayesian Nonparametric Conditional Copula Estimation of Twin Data," Working Papers 2016:08, Department of Economics, University of Venice "Ca' Foscari".
  2. Luciana Dalla Valle & Maria Elena De Giuli & Claudia Tarantola & Claudio Manelli, 2014. "Default Probability Estimation via Pair Copula Constructions," Papers 1405.1309, arXiv.org, revised Aug 2015.
  3. Giovanna NICOLINI & Luciana DALLA VALLE, 2009. "Overview about bias in customer satisfaction surveys and focus on self-selection error," Departmental Working Papers 2009-052, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  4. Giovanna Nicolini & Luciana Dalla Valle, 2009. "Overview about bias in Customer Satisfaction Surveys and focus on self-selection error," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1094, Universitá degli Studi di Milano.
  5. Luciana Dalla Valle & Giovanna Nicolini, 2008. "Statistical Analysis of the Country Selection for Italian SMEs," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1081, Universitá degli Studi di Milano.

Articles

  1. Kreuzer, Alexander & Dalla Valle, Luciana & Czado, Claudia, 2023. "Bayesian multivariate nonlinear state space copula models," Computational Statistics & Data Analysis, Elsevier, vol. 188(C).
  2. Grazian, Clara & Dalla Valle, Luciana & Liseo, Brunero, 2022. "Approximate Bayesian conditional copulas," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
  3. Alexander Kreuzer & Luciana Dalla Valle & Claudia Czado, 2022. "A Bayesian non‐linear state space copula model for air pollution in Beijing," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 613-638, June.
  4. Tahani S. Alotaibi & Luciana Dalla Valle & Matthew J. Craven, 2022. "The Worst Case GARCH-Copula CVaR Approach for Portfolio Optimisation: Evidence from Financial Markets," JRFM, MDPI, vol. 15(10), pages 1-14, October.
  5. Luciana Dalla Valle & Fabrizio Leisen & Luca Rossini & Weixuan Zhu, 2020. "Bayesian analysis of immigration in Europe with generalized logistic regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(3), pages 424-438, February.
  6. Robert A. Jane & David J. Simmonds & Ben P. Gouldby & Jonathan D. Simm & Luciana Dalla Valle & Alison C. Raby, 2018. "Exploring the Potential for Multivariate Fragility Representations to Alter Flood Risk Estimates," Risk Analysis, John Wiley & Sons, vol. 38(9), pages 1847-1870, September.
  7. Julian Stander & Luciana Dalla Valle & Mario Cortina-Borja, 2018. "A Bayesian Survival Analysis of a Historical Dataset: How Long Do Popes Live?," The American Statistician, Taylor & Francis Journals, vol. 72(4), pages 368-375, October.
  8. Luciana Dalla Valle & Fabrizio Leisen & Luca Rossini, 2018. "Bayesian non‐parametric conditional copula estimation of twin data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 523-548, April.
  9. Dalla Valle, Luciana & De Giuli, Maria Elena & Tarantola, Claudia & Manelli, Claudio, 2016. "Default probability estimation via pair copula constructions," European Journal of Operational Research, Elsevier, vol. 249(1), pages 298-311.
  10. Dalla Valle Luciana, 2016. "The Use of Official Statistics in Self-Selection Bias Modeling," Journal of Official Statistics, Sciendo, vol. 32(4), pages 887-905, December.
  11. Antonio Majocchi & Luciana Dalla Valle & Alfredo D'Angelo, 2015. "Internationalisation, cultural distance and country characteristics: a Bayesian analysis of SMEs financial performance," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 16(2), pages 307-324, April.
  12. Luciana Dalla Valle, 2012. "Erratum to: Bayesian Copulae Distributions, with Application to Operational Risk Management," Methodology and Computing in Applied Probability, Springer, vol. 14(4), pages 1121-1121, December.
  13. Luciana Dalla Valle, 2009. "Bayesian Copulae Distributions, with Application to Operational Risk Management," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 95-115, March.
  14. Dalla Valle, L. & Giudici, P., 2008. "A Bayesian approach to estimate the marginal loss distributions in operational risk management," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3107-3127, February.

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. Luciana Dalla Valle & Fabrizio Leisen & Luca Rossini, 2016. "Bayesian Nonparametric Conditional Copula Estimation of Twin Data," Working Papers 2016:08, Department of Economics, University of Venice "Ca' Foscari".

    Cited by:

    1. Arbel, Julyan & Crispino, Marta & Girard, Stéphane, 2019. "Dependence properties and Bayesian inference for asymmetric multivariate copulas," Journal of Multivariate Analysis, Elsevier, vol. 174(C).
    2. Grazian, Clara & Dalla Valle, Luciana & Liseo, Brunero, 2022. "Approximate Bayesian conditional copulas," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    3. Huihui Lin & N. Rao Chaganty, 2021. "Multivariate distributions of correlated binary variables generated by pair-copulas," Journal of Statistical Distributions and Applications, Springer, vol. 8(1), pages 1-14, December.
    4. Maximilian Coblenz & Simon Holz & Hans‐Jörg Bauer & Oliver Grothe & Rainer Koch, 2020. "Modelling fuel injector spray characteristics in jet engines by using vine copulas," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 863-886, August.
    5. Levi, Evgeny & Craiu, Radu V., 2018. "Bayesian inference for conditional copulas using Gaussian Process single index models," Computational Statistics & Data Analysis, Elsevier, vol. 122(C), pages 115-134.

  2. Luciana Dalla Valle & Maria Elena De Giuli & Claudia Tarantola & Claudio Manelli, 2014. "Default Probability Estimation via Pair Copula Constructions," Papers 1405.1309, arXiv.org, revised Aug 2015.

    Cited by:

    1. Fantazzini, Dean, 2022. "Crypto Coins and Credit Risk: Modelling and Forecasting their Probability of Death," MPRA Paper 113744, University Library of Munich, Germany.
    2. Ghufran Ahmad & Muhammad Suhail Rizwan & Dawood Ashraf, 2021. "Systemic risk and macroeconomic forecasting: A globally applicable copula‐based approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1420-1443, December.
    3. Masahiko Egami & Rusudan Kevkhishvili, 2016. "An Analysis of Simultaneous Company Defaults Using a Shot Noise Process," Discussion papers e-16-001, Graduate School of Economics , Kyoto University.
    4. Bassetti, Federico & De Giuli, Maria Elena & Nicolino, Enrica & Tarantola, Claudia, 2018. "Multivariate dependence analysis via tree copula models: An application to one-year forward energy contracts," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1107-1121.
    5. E. Allevi & L. Boffino & M. E. Giuli & G. Oggioni, 2019. "Analysis of long-term natural gas contracts with vine copulas in optimization portfolio problems," Annals of Operations Research, Springer, vol. 274(1), pages 1-37, March.
    6. Dean Fantazzini & Stephan Zimin, 2020. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 19-69, March.
    7. Tahani S. Alotaibi & Luciana Dalla Valle & Matthew J. Craven, 2022. "The Worst Case GARCH-Copula CVaR Approach for Portfolio Optimisation: Evidence from Financial Markets," JRFM, MDPI, vol. 15(10), pages 1-14, October.
    8. Kjersti Aas, 2016. "Pair-Copula Constructions for Financial Applications: A Review," Econometrics, MDPI, vol. 4(4), pages 1-15, October.
    9. Fantazzini, Dean, 2023. "Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models," MPRA Paper 117141, University Library of Munich, Germany.
    10. Muhammad Suhail Rizwan & Muhammad Moinuddin & Barbara L’Huillier & Dawood Ashraf, 2018. "Does a one-size-fits-all approach to financial regulations alleviate default risk? The case of dual banking systems," Journal of Regulatory Economics, Springer, vol. 53(1), pages 37-74, February.
    11. Egami, M. & Kevkhishvili, R., 2017. "An analysis of simultaneous company defaults using a shot noise process," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 135-161.

Articles

  1. Luciana Dalla Valle & Fabrizio Leisen & Luca Rossini & Weixuan Zhu, 2020. "Bayesian analysis of immigration in Europe with generalized logistic regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(3), pages 424-438, February.

    Cited by:

    1. Juan Carlos Martín & Alessandro Indelicato, 2022. "A DEA MCDM Approach Applied to ESS8 Dataset for Measuring Immigration and Refugees Citizens’ Openness," Journal of International Migration and Integration, Springer, vol. 23(4), pages 1941-1961, December.

  2. Robert A. Jane & David J. Simmonds & Ben P. Gouldby & Jonathan D. Simm & Luciana Dalla Valle & Alison C. Raby, 2018. "Exploring the Potential for Multivariate Fragility Representations to Alter Flood Risk Estimates," Risk Analysis, John Wiley & Sons, vol. 38(9), pages 1847-1870, September.

    Cited by:

    1. Li, Yaohan & Dong, You & Guo, Hongyuan, 2023. "Copula-based multivariate renewal model for life-cycle analysis of civil infrastructure considering multiple dependent deterioration processes," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    2. Chengguang Lai & Xiaohong Chen & Zhaoli Wang & Haijun Yu & Xiaoyan Bai, 2020. "Flood Risk Assessment and Regionalization from Past and Future Perspectives at Basin Scale," Risk Analysis, John Wiley & Sons, vol. 40(7), pages 1399-1417, July.

  3. Julian Stander & Luciana Dalla Valle & Mario Cortina-Borja, 2018. "A Bayesian Survival Analysis of a Historical Dataset: How Long Do Popes Live?," The American Statistician, Taylor & Francis Journals, vol. 72(4), pages 368-375, October.

    Cited by:

    1. Kosztyán, Zsolt T. & Jakab, Róbert & Novák, Gergely & Hegedűs, Csaba, 2020. "Survive IT! Survival analysis of IT project planning approaches," Operations Research Perspectives, Elsevier, vol. 7(C).

  4. Luciana Dalla Valle & Fabrizio Leisen & Luca Rossini, 2018. "Bayesian non‐parametric conditional copula estimation of twin data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 523-548, April.
    See citations under working paper version above.
  5. Dalla Valle, Luciana & De Giuli, Maria Elena & Tarantola, Claudia & Manelli, Claudio, 2016. "Default probability estimation via pair copula constructions," European Journal of Operational Research, Elsevier, vol. 249(1), pages 298-311.
    See citations under working paper version above.
  6. Dalla Valle Luciana, 2016. "The Use of Official Statistics in Self-Selection Bias Modeling," Journal of Official Statistics, Sciendo, vol. 32(4), pages 887-905, December.

    Cited by:

    1. Maciej Berȩsewicz & Dagmara Nikulin, 2021. "Estimation of the size of informal employment based on administrative records with non‐ignorable selection mechanism," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 667-690, June.
    2. Maciej Berk{e}sewicz & Dagmara Nikulin, 2019. "Estimation of the size of informal employment based on administrative records with non-ignorable selection mechanism," Papers 1906.10957, arXiv.org.

  7. Antonio Majocchi & Luciana Dalla Valle & Alfredo D'Angelo, 2015. "Internationalisation, cultural distance and country characteristics: a Bayesian analysis of SMEs financial performance," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 16(2), pages 307-324, April.

    Cited by:

    1. Morais, Flávio & Ferreira, João J., 2020. "SME internationalisation process: Key issues and contributions, existing gaps and the future research agenda," European Management Journal, Elsevier, vol. 38(1), pages 62-77.
    2. Simone Lazzini & Zeila Occhipinti & Angela Parenti & Roberto Verona, 2021. "Disentangling economic crisis effects from environmental regulation effects: Implications for sustainable development," Business Strategy and the Environment, Wiley Blackwell, vol. 30(5), pages 2332-2353, July.
    3. Gaganis, Chrysovalantis & Pasiouras, Fotios & Voulgari, Fotini, 2019. "Culture, business environment and SMEs' profitability: Evidence from European Countries," Economic Modelling, Elsevier, vol. 78(C), pages 275-292.
    4. D’Angelo, Alfredo & Buck, Trevor, 2019. "The earliness of exporting and creeping sclerosis? The moderating effects of firm age, size and centralization," International Business Review, Elsevier, vol. 28(3), pages 428-437.
    5. Monica Violeta Achim & Sorin Nicolae Borlea & Codruţa Mare, 2018. "Geocentric Behavior Dimension of the Organization’ Performance in the Context of Globalization," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 401-420, January.
    6. Mara Madaleno & Celeste Amorim Varum & Isabel Horta, 2018. "SMEs Performance and Internationalization: A Traditional Industry Approach," Annals of Economics and Finance, Society for AEF, vol. 19(2), pages 605-624, November.

  8. Luciana Dalla Valle, 2009. "Bayesian Copulae Distributions, with Application to Operational Risk Management," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 95-115, March.

    Cited by:

    1. Fantazzini, Dean, 2008. "Econometric Analysis of Financial Data in Risk Management (continuation). Section III: Managing Operational Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 11(3), pages 87-122.
    2. Pavel V. Shevchenko, 2010. "Implementing loss distribution approach for operational risk," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(3), pages 277-307, May.
    3. Shumin Ma & Zhiri Yuan & Qi Wu & Yiyan Huang & Xixu Hu & Cheuk Hang Leung & Dongdong Wang & Zhixiang Huang, 2023. "Deep into The Domain Shift: Transfer Learning through Dependence Regularization," Papers 2305.19499, arXiv.org.
    4. Philipp Arbenz, 2013. "Bayesian Copulae Distributions, with Application to Operational Risk Management—Some Comments," Methodology and Computing in Applied Probability, Springer, vol. 15(1), pages 105-108, March.
    5. Rada Dakovic & Claudia Czado, 2011. "Comparing point and interval estimates in the bivariate t-copula model with application to financial data," Statistical Papers, Springer, vol. 52(3), pages 709-731, August.
    6. Pavel V. Shevchenko, 2009. "Implementing Loss Distribution Approach for Operational Risk," Papers 0904.1805, arXiv.org, revised Jul 2009.
    7. Tahani S. Alotaibi & Luciana Dalla Valle & Matthew J. Craven, 2022. "The Worst Case GARCH-Copula CVaR Approach for Portfolio Optimisation: Evidence from Financial Markets," JRFM, MDPI, vol. 15(10), pages 1-14, October.
    8. Mohamed Habachi & Saâd Benbachir, 2020. "The Bayesian Approach to Capital Allocation at Operational Risk: A Combination of Statistical Data and Expert Opinion," IJFS, MDPI, vol. 8(1), pages 1-25, February.
    9. Juan Wu & Xue Wang & Stephen G. Walker, 2014. "Bayesian Nonparametric Inference for a Multivariate Copula Function," Methodology and Computing in Applied Probability, Springer, vol. 16(3), pages 747-763, September.
    10. Luca Regis, 2011. "A Bayesian copula model for stochastic claims reserving," Carlo Alberto Notebooks 227, Collegio Carlo Alberto.

  9. Dalla Valle, L. & Giudici, P., 2008. "A Bayesian approach to estimate the marginal loss distributions in operational risk management," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3107-3127, February.

    Cited by:

    1. Paolo Giudici, 2015. "Scorecard models for operations management," International Journal of Data Science, Inderscience Enterprises Ltd, vol. 1(1), pages 96-101.
    2. Gambacorta, Leonardo & Aldasoro, Inaki & Giudici, Paolo & Leach, Thomas, 2020. "Operational and cyber risks in the financial sector," CEPR Discussion Papers 14418, C.E.P.R. Discussion Papers.
    3. Paola Cerchiello & Paolo Giudici, 2014. "How to measure the quality of financial tweets," DEM Working Papers Series 069, University of Pavia, Department of Economics and Management.
    4. E. Otranto, 2008. "Clustering Heteroskedastic Time Series by Model-Based Procedures," Working Paper CRENoS 200801, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    5. Silvia Figini & Lijun Gao & Paolo Giudici, 2013. "Bayesian operational risk models," DEM Working Papers Series 047, University of Pavia, Department of Economics and Management.
    6. Wang, Zongrun & Wang, Wuchao & Chen, Xiaohong & Jin, Yanbo & Zhou, Yanju, 2012. "Using BS-PSD-LDA approach to measure operational risk of Chinese commercial banks," Economic Modelling, Elsevier, vol. 29(6), pages 2095-2103.
    7. Fantazzini, Dean, 2008. "Econometric Analysis of Financial Data in Risk Management (continuation). Section III: Managing Operational Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 11(3), pages 87-122.
    8. Lu, Zhaoyang, 2011. "Modeling the yearly Value-at-Risk for operational risk in Chinese commercial banks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(4), pages 604-616.
    9. Lu Wei & Jianping Li & Xiaoqian Zhu, 2018. "Operational Loss Data Collection: A Literature Review," Annals of Data Science, Springer, vol. 5(3), pages 313-337, September.
    10. Francesca Greselin & Fabio Piacenza & Ričardas Zitikis, 2019. "Practice Oriented and Monte Carlo Based Estimation of the Value-at-Risk for Operational Risk Measurement," Risks, MDPI, vol. 7(2), pages 1-20, May.
    11. Xu, Chi & Zheng, Chunling & Wang, Donghua & Ji, Jingru & Wang, Nuan, 2019. "Double correlation model for operational risk: Evidence from Chinese commercial banks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 327-339.
    12. Luciana Dalla Valle, 2009. "Bayesian Copulae Distributions, with Application to Operational Risk Management," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 95-115, March.
    13. Ramírez-Cobo, Pepa & Carrizosa, Emilio & Lillo, Rosa E., 2021. "Analysis of an aggregate loss model in a Markov renewal regime," Applied Mathematics and Computation, Elsevier, vol. 396(C).
    14. Facchinetti, Silvia & Osmetti, Silvia Angela & Tarantola, Claudia, 2023. "Network models for cyber attacks evaluation," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    15. Mohamed Habachi & Saâd Benbachir, 2020. "The Bayesian Approach to Capital Allocation at Operational Risk: A Combination of Statistical Data and Expert Opinion," IJFS, MDPI, vol. 8(1), pages 1-25, February.
    16. Paola Cerchiello & Paolo Giudici, 2013. "H Index: A Statistical Proposal," DEM Working Papers Series 039, University of Pavia, Department of Economics and Management.
    17. Paola Cerchiello & Paolo Giudici, 2015. "A Bayesian h-index: how to measure research impact," DEM Working Papers Series 102, University of Pavia, Department of Economics and Management.
    18. Paola Cerchiello & Paolo Giudici, 2014. "On a statistical h index," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 299-312, May.

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 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (2) 2013-09-28 2016-04-09
  2. NEP-RMG: Risk Management (2) 2013-09-28 2014-05-09

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, Luciana Dalla Valle 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.