IDEAS home Printed from https://ideas.repec.org/f/pgi259.html
   My authors  Follow this author

Paolo Giudici

Personal Details

First Name:Paolo
Middle Name:
Last Name:Giudici
Suffix:
RePEc Short-ID:pgi259
http://dem-web.unipv.it/employe/personale.php?id=62
Twitter: @stateconomist

Affiliation

Dipartimento di Scienze Economiche e Aziendali
Università degli Studi di Pavia

Pavia, Italy
http://economiaweb.unipv.it/

: +39/0382/506201
+39/0382/304226
Via S. Felice, 5 - 27100 Pavia
RePEc:edi:dppavit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Fatemeh Mojtahedi & Seyed Mojtaba Mojaverian & Daniel Felix Ahelegbey & Paolo Giudici, 2020. "Tail Risk Transmission: A Study of Iran Food Industry," DEM Working Papers Series 189, University of Pavia, Department of Economics and Management.
  2. Daniel Felix Ahelegbey & Paolo Giudici & Fatemeh Mojtahedi, 2020. "Tail Risk Measurement In Crypto-Asset Markets," DEM Working Papers Series 186, University of Pavia, Department of Economics and Management.
  3. Arianna Agosto & Paolo Giudici & Emanuela Raffinetti, 2020. "A rank graduation accuracy measure," DEM Working Papers Series 179, University of Pavia, Department of Economics and Management.
  4. Aldasoro, Inaki & Gambacorta, Leonardo & giudici, paolo & Leach, Thomas, 2020. "The drivers of cyber risk," CEPR Discussion Papers 14805, C.E.P.R. Discussion Papers.
  5. Daniel Felix Ahelegbey & Paolo Giudici, 2020. "Market Risk, Connectedness and Turbulence: A Comparison of 21st Century Financial Crises," DEM Working Papers Series 188, University of Pavia, Department of Economics and Management.
  6. Iñaki Aldasoro & Leonardo Gambacorta & Paolo Giudici & Thomas Leach, 2020. "Operational and cyber risks in the financial sector," BIS Working Papers 840, Bank for International Settlements.
  7. Arianna Agosto & Paolo Giudici, 2020. "A Poisson autoregressive model to understand COVID-19 contagion dynamics," DEM Working Papers Series 185, University of Pavia, Department of Economics and Management.
  8. Daniel Felix Ahelegbey & Paolo Giudici & Shatha Qamhieh Hashem, 2020. "Network VAR models to Measure Financial Contagion," DEM Working Papers Series 178, University of Pavia, Department of Economics and Management.
  9. Paolo Giudici & Thomas Leach & Paolo Pagnottoni, 2020. "Libra or Librae? Basket based stablecoins to mitigate foreign exchange volatility spillovers," DEM Working Papers Series 183, University of Pavia, Department of Economics and Management.
  10. Stefan Avdjiev & Paolo Giudici & Alessandro Spelta, 2019. "Measuring contagion risk in international banking," BIS Working Papers 796, Bank for International Settlements.
  11. Ahelegbey, Daniel Felix & Giudici, Paolo & Hadji-Misheva, Branka, 2019. "Factorial Network Models To Improve P2P Credit Risk Management," MPRA Paper 92633, University Library of Munich, Germany.
  12. Ahelegbey, Daniel Felix & Giudici, Paolo, 2019. "Tree Networks to Assess Financial Contagion," MPRA Paper 92632, University Library of Munich, Germany.
  13. Giudici, Paolo & Huang, Bihong & Spelta, Alessandro, 2018. "Trade Networks and Economic Fluctuations in Asia," ADBI Working Papers 832, Asian Development Bank Institute.
  14. Ahelegbey, Daniel Felix & Giudici, Paolo & Hadji-Misheva, Branka, 2018. "Latent Factor Models for Credit Scoring in P2P Systems," MPRA Paper 92636, University Library of Munich, Germany, revised 11 Oct 2018.
  15. Pejman Abedifar & Paolo Giudici & Shatha Hashem, 2017. "Heterogeneous Market Structure and Systemic Risk: Evidence from Dual Banking Systems," DEM Working Papers Series 134, University of Pavia, Department of Economics and Management.
  16. Paolo Giudici & Laura Parisi, 2016. "CoRisk: measuring systemic risk through default probability contagion," DEM Working Papers Series 116, University of Pavia, Department of Economics and Management.
  17. Paolo Giudici & Peter Sarlin & Alessandro Spelta, 2016. "The multivariate nature of systemic risk: direct and common exposures," DEM Working Papers Series 118, University of Pavia, Department of Economics and Management.
  18. Paolo Giudici & Laura Parisi, 2016. "Bail in or Bail out? The Atlante example from a systemic risk perspective," DEM Working Papers Series 124, University of Pavia, Department of Economics and Management.
  19. Paola Cerchiello & Paolo Giudici & Giancarlo Nicola, 2016. "Big data models of bank risk contagion," DEM Working Papers Series 117, University of Pavia, Department of Economics and Management.
  20. 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.
  21. Laura Parisi & Igor Gianfrancesco & Camillo Gilberto & Paolo Giudici, 2015. "Monetary transmission models for bank interest rates," DEM Working Papers Series 101, University of Pavia, Department of Economics and Management.
  22. Paolo Giudici & Shatha Hashem, 2015. "Systemic risk of Islamic Banks," DEM Working Papers Series 103, University of Pavia, Department of Economics and Management.
  23. Paolo Giudici & Laura Parisi, 2015. "Modeling Systemic Risk with Correlated Stochastic Processes," DEM Working Papers Series 110, University of Pavia, Department of Economics and Management.
  24. Paola Cerchiello & Paolo Giudici, 2014. "Conditional graphical models for systemic risk measurement," DEM Working Papers Series 087, University of Pavia, Department of Economics and Management.
  25. 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.
  26. Raffaella Calabrese & Johan A. Elkink & Paolo Giudici, 2014. "Measuring Bank Contagion in Europe Using Binary Spatial Regression Models," DEM Working Papers Series 096, University of Pavia, Department of Economics and Management.
  27. Daniel Felix Ahelegbey & Paolo Giudici, 2014. "Hierarchical Graphical Models, With Application to Systemic Risk," Working Papers 2014:01, Department of Economics, University of Venice "Ca' Foscari".
  28. Paola Cerchiello & Paolo Giudici, 2014. "Financial big data analysis for the estimation of systemic risks," DEM Working Papers Series 086, University of Pavia, Department of Economics and Management.
  29. Silvia Figini & Lijun Gao & Paolo Giudici, 2013. "Bayesian operational risk models," DEM Working Papers Series 047, University of Pavia, Department of Economics and Management.
  30. Silvia Figini & Paolo Giudici, 2013. "Credit risk predictions with Bayesian model averaging," DEM Working Papers Series 034, University of Pavia, Department of Economics and Management.
  31. Paolo Giudici & Alessandro Spelta, 2013. "Graphical network models for international financial flows," DEM Working Papers Series 052, University of Pavia, Department of Economics and Management.
  32. Paola Cerchiello & Paolo Giudici, 2013. "Bayesian Credit Ratings (new version)," DEM Working Papers Series 030, University of Pavia, Department of Economics and Management.
  33. Raffaella Calabrese & Paolo Giudici, 2013. "Estimating bank default with generalised extreme value models," DEM Working Papers Series 035, University of Pavia, Department of Economics and Management.
  34. Silvia Figini & Paolo Giudici, 2013. "Measuring risk with ordinal variables," DEM Working Papers Series 032, University of Pavia, Department of Economics and Management.
  35. Paola Cerchiello & Paolo Giudici, 2013. "H Index: A Statistical Proposal," DEM Working Papers Series 039, University of Pavia, Department of Economics and Management.

Articles

  1. Ying Chen & Paolo Giudici & Branka Hadji Misheva & Simon Trimborn, 2020. "Lead Behaviour in Bitcoin Markets," Risks, MDPI, Open Access Journal, vol. 8(1), pages 1-14, January.
  2. Paolo Giudici & Paolo Pagnottoni, 2020. "Vector error correction models to measure connectedness of Bitcoin exchange markets," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(1), pages 95-109, January.
  3. Silvia Facchinetti & Paolo Giudici & Silvia Angela Osmetti, 2020. "Cyber risk measurement with ordinal data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 173-185, March.
  4. Agosto, Arianna & Ahelegbey, Daniel Felix & Giudici, Paolo, 2020. "Tree networks to assess financial contagion," Economic Modelling, Elsevier, vol. 85(C), pages 349-366.
  5. Giudici, Paolo & Huang, Bihong & Spelta, Alessandro, 2019. "Trade networks and economic fluctuations in Asian countries," Economic Systems, Elsevier, vol. 43(2), pages 1-1.
  6. Giudici, Paolo & Abu-Hashish, Iman, 2019. "What determines bitcoin exchange prices? A network VAR approach," Finance Research Letters, Elsevier, vol. 28(C), pages 309-318.
  7. Paolo Giudici & Paolo Pagnottoni, 2019. "High Frequency Price Change Spillovers in Bitcoin Markets," Risks, MDPI, Open Access Journal, vol. 7(4), pages 1-18, November.
  8. Ahelegbey, Daniel Felix & Giudici, Paolo & Hadji-Misheva, Branka, 2019. "Latent factor models for credit scoring in P2P systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 112-121.
  9. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, Open Access Journal, vol. 7(1), pages 1-25, January.
  10. Avdjiev, S. & Giudici, P. & Spelta, A., 2019. "Measuring contagion risk in international banking," Journal of Financial Stability, Elsevier, vol. 42(C), pages 36-51.
  11. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.
  12. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, Open Access Journal, vol. 6(3), pages 1-19, September.
  13. Paola Cerchiello & Paolo Giudici, 2017. "Categorical network models for systemic risk measurement," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(4), pages 1593-1609, July.
  14. Paolo Giudici & Laura Parisi, 2017. "Sovereign risk in the Euro area: a multivariate stochastic process approach," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1995-2008, December.
  15. Raffaella Calabrese & Johan A. Elkink & Paolo S. Giudici, 2017. "Measuring bank contagion in Europe using binary spatial regression models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(12), pages 1503-1511, December.
  16. Abedifar, Pejman & Giudici, Paolo & Hashem, Shatha Qamhieh, 2017. "Heterogeneous market structure and systemic risk: Evidence from dual banking systems," Journal of Financial Stability, Elsevier, vol. 33(C), pages 96-119.
  17. P. Giudici & A. Spelta, 2016. "Graphical Network Models for International Financial Flows," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 128-138, January.
  18. Raffaella Calabrese & Paolo Giudici, 2015. "Estimating bank default with generalised extreme value regression models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(11), pages 1783-1792, November.
  19. Paolo Giudici, 2015. "Scorecard models for operations management," International Journal of Data Science, Inderscience Enterprises Ltd, vol. 1(1), pages 96-101.
  20. Paola Cerchiello & Paolo Giudici, 2014. "On a statistical h index," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 299-312, May.
  21. Cerchiello, Paola & Giudici, Paolo, 2012. "On the distribution of functionals of discrete ordinal variables," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 2044-2049.
  22. Paola Cerchiello & Paolo Giudici, 2012. "Non parametric statistical models for on-line text classification," 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. 6(4), pages 277-288, December.
  23. J. Pardo, 2011. "Paolo Giudici and Silvia Figini: Applied data mining for business and industry (Second Edition)," Statistical Papers, Springer, vol. 52(3), pages 739-740, August.
  24. Giudici, P. & Raffinetti, E., 2011. "On the Gini measure decomposition," Statistics & Probability Letters, Elsevier, vol. 81(1), pages 133-139, January.
  25. Silvia Figini & Paolo Giudici & Pierpaolo Uberti, 2010. "A threshold based approach to merge data in financial risk management," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(11), pages 1815-1824.
  26. Silvia Figini & Paolo Giudici, 2009. "Statistical models for e-learning data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(2), pages 293-304, July.
  27. 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.
  28. Bonafede, C.E. & Giudici, P., 2007. "Bayesian Networks for enterprise risk assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 22-28.
  29. Cornalba, Chiara & Giudici, Paolo, 2004. "Statistical models for operational risk management," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 166-172.
  30. Eva-Maria Fronk & Paolo Giudici, 2004. "Markov Chain Monte Carlo model selection for DAG models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 13(3), pages 259-273, December.
  31. S. P. Brooks & P. Giudici & G. O. Roberts, 2003. "Efficient construction of reversible jump Markov chain Monte Carlo proposal distributions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 3-39, January.
  32. Christian P. Robert & Xiao‐Li Meng & Jesper Møller & Jeffrey S Rosenthal & C Jennison & M. A Hurn & F Al‐Awadhi & Peter McCullagh & Christophe Andrieu & Arnaud Doucet & Petros Dellaportas & Ioulia Pap, 2003. "Discussion on the paper by Brooks, Giudici and Roberts," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 39-55, January.
  33. Giudici, Paolo & Passerone, Gianluca, 2002. "Data mining of association structures to model consumer behaviour," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 533-541, February.
  34. Paolo Giudici, 2001. "Bayesian data mining, with application to benchmarking and credit scoring," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 17(1), pages 69-81, January.
  35. Paolo Giudici & Elena Stanghellini, 2001. "Bayesian inference for graphical factor analysis models," Psychometrika, Springer;The Psychometric Society, vol. 66(4), pages 577-591, December.
  36. Paolo Giudici & Wolfgang Polasek, 2001. "Editorial," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 17(1), pages 1-3, January.
  37. Paolo Giudici & Tobias Ryden & Pierre Vandekerkhove, 2000. "Likelihood-Ratio Tests for Hidden Markov Models," Biometrics, The International Biometric Society, vol. 56(3), pages 742-747, September.
  38. Maura Mezzetti & Paolo Giudici, 1999. "Monte Carlo methods for nonparametric survival model determination," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 8(1), pages 49-60, April.
  39. Paolo Giudici & Maura Mezzetti, 1998. "Nonparametric estimation of survival functions by means of partial exchangeability structures," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 7(1), pages 111-132, June.
  40. Paolo Giudici, 1998. "Markov chain Monte Carlo methods for probabilistic network model determination," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 7(2), pages 171-183, August.
  41. Paolo Giudici & Gloria Polinesi, 0. "Crypto price discovery through correlation networks," Annals of Operations Research, Springer, vol. 0, pages 1-15.
  42. Arianna Agosto & Paolo Giudici, 0. "COVID-19 contagion and digital finance," Digital Finance, Springer, vol. 0, pages 1-9.

Chapters

  1. Daniel Felix Ahelegbey & Paolo Giudici, 2014. "Bayesian Selection of Systemic Risk Networks," Advances in Econometrics, in: Ivan Jeliazkov & Dale J. Poirier (ed.), Bayesian Model Comparison, volume 34, pages 117-153, Emerald Publishing Ltd.

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.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Arianna Agosto & Paolo Giudici, 2020. "A Poisson autoregressive model to understand COVID-19 contagion dynamics," DEM Working Papers Series 185, University of Pavia, Department of Economics and Management.

    Mentioned in:

    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Health policy
    2. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19

Working papers

  1. Stefan Avdjiev & Paolo Giudici & Alessandro Spelta, 2019. "Measuring contagion risk in international banking," BIS Working Papers 796, Bank for International Settlements.

    Cited by:

    1. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, Open Access Journal, vol. 7(1), pages 1-25, January.
    2. Daniel Felix Ahelegbey & Paolo Giudici & Shatha Qamhieh Hashem, 2020. "Network VAR models to Measure Financial Contagion," DEM Working Papers Series 178, University of Pavia, Department of Economics and Management.

  2. Ahelegbey, Daniel Felix & Giudici, Paolo & Hadji-Misheva, Branka, 2018. "Latent Factor Models for Credit Scoring in P2P Systems," MPRA Paper 92636, University Library of Munich, Germany, revised 11 Oct 2018.

    Cited by:

    1. Ahelegbey, Daniel Felix & Giudici, Paolo & Hadji-Misheva, Branka, 2019. "Factorial Network Models To Improve P2P Credit Risk Management," MPRA Paper 92633, University Library of Munich, Germany.

  3. Pejman Abedifar & Paolo Giudici & Shatha Hashem, 2017. "Heterogeneous Market Structure and Systemic Risk: Evidence from Dual Banking Systems," DEM Working Papers Series 134, University of Pavia, Department of Economics and Management.

    Cited by:

    1. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.
    2. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, Open Access Journal, vol. 6(3), pages 1-19, September.
    3. Belkhir, Mohamed & Grira, Jocelyn & Hassan, M. Kabir & Soumaré, Issouf, 2019. "Islamic banks and political risk: International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 74(C), pages 39-55.
    4. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, Open Access Journal, vol. 7(1), pages 1-25, January.

  4. Paolo Giudici & Laura Parisi, 2016. "CoRisk: measuring systemic risk through default probability contagion," DEM Working Papers Series 116, University of Pavia, Department of Economics and Management.

    Cited by:

    1. Paolo Giudici & Laura Parisi, 2016. "Bail in or Bail out? The Atlante example from a systemic risk perspective," DEM Working Papers Series 124, University of Pavia, Department of Economics and Management.

  5. Paolo Giudici & Laura Parisi, 2016. "Bail in or Bail out? The Atlante example from a systemic risk perspective," DEM Working Papers Series 124, University of Pavia, Department of Economics and Management.

    Cited by:

    1. Nicholas Coleman & Andromachi Georgosouli & Tara Rice, 2018. "Measuring the Implementation of the FSB Key Attributes of Effective Resolution Regimes for Financial Institutions in the European Union," International Finance Discussion Papers 1238, Board of Governors of the Federal Reserve System (U.S.), revised Nov 2018.

  6. Paola Cerchiello & Paolo Giudici & Giancarlo Nicola, 2016. "Big data models of bank risk contagion," DEM Working Papers Series 117, University of Pavia, Department of Economics and Management.

    Cited by:

    1. Matteo Accornero & Mirko Moscatelli, 2018. "Listening to the buzz: social media sentiment and retail depositors' trust," Temi di discussione (Economic working papers) 1165, Bank of Italy, Economic Research and International Relations Area.

  7. Laura Parisi & Igor Gianfrancesco & Camillo Gilberto & Paolo Giudici, 2015. "Monetary transmission models for bank interest rates," DEM Working Papers Series 101, University of Pavia, Department of Economics and Management.

    Cited by:

    1. Paolo Giudici & Laura Parisi, 2015. "Dynamic models for monetary transmission," DEM Working Papers Series 106, University of Pavia, Department of Economics and Management.

  8. Paola Cerchiello & Paolo Giudici, 2014. "Conditional graphical models for systemic risk measurement," DEM Working Papers Series 087, University of Pavia, Department of Economics and Management.

    Cited by:

    1. Raffaella Calabrese & Johan A. Elkink & Paolo Giudici, 2014. "Measuring Bank Contagion in Europe Using Binary Spatial Regression Models," DEM Working Papers Series 096, University of Pavia, Department of Economics and Management.

  9. 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.

    Cited by:

    1. Paola Cerchiello & Giancarlo Nicola, 2017. "Assessing News Contagion in Finance," DEM Working Papers Series 139, University of Pavia, Department of Economics and Management.
    2. George Kapetanios & Fotis Papailias, 2018. "Big Data & Macroeconomic Nowcasting: Methodological Review," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-12, Economic Statistics Centre of Excellence (ESCoE).
    3. Paola Cerchiello & Paolo Giudici, 2014. "Financial big data analysis for the estimation of systemic risks," DEM Working Papers Series 086, University of Pavia, Department of Economics and Management.
    4. Paola Cerchiello & Giancarlo Nicola, 2018. "Assessing News Contagion in Finance," Econometrics, MDPI, Open Access Journal, vol. 6(1), pages 1-19, February.

  10. Raffaella Calabrese & Johan A. Elkink & Paolo Giudici, 2014. "Measuring Bank Contagion in Europe Using Binary Spatial Regression Models," DEM Working Papers Series 096, University of Pavia, Department of Economics and Management.

    Cited by:

    1. Matteo Foglia & Eliana Angelini, 2019. "The Time-Spatial Dimension of Eurozone Banking Systemic Risk," Risks, MDPI, Open Access Journal, vol. 7(3), pages 1-25, July.
    2. Manthoulis, Georgios & Doumpos, Michalis & Zopounidis, Constantin & Galariotis, Emilios, 2020. "An ordinal classification framework for bank failure prediction: Methodology and empirical evidence for US banks," European Journal of Operational Research, Elsevier, vol. 282(2), pages 786-801.

  11. Daniel Felix Ahelegbey & Paolo Giudici, 2014. "Hierarchical Graphical Models, With Application to Systemic Risk," Working Papers 2014:01, Department of Economics, University of Venice "Ca' Foscari".

    Cited by:

    1. Carota, Cinzia & Durio, Alessandra & Guerzoni, Marco, 2014. "An Application of Graphical Models to the Innobarometer Survey: A Map of Firms’ Innovative Behaviour," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201444, University of Turin.

  12. Silvia Figini & Lijun Gao & Paolo Giudici, 2013. "Bayesian operational risk models," DEM Working Papers Series 047, University of Pavia, Department of Economics and Management.

    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.

  13. Paolo Giudici & Alessandro Spelta, 2013. "Graphical network models for international financial flows," DEM Working Papers Series 052, University of Pavia, Department of Economics and Management.

    Cited by:

    1. Rui Faustino, 2016. "Portuguese National Accounts: a network approach," Working Papers Department of Economics 2016/18, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    2. Araújo, Tanya & Faustino, Rui, 2017. "The topology of inter-industry relations from the Portuguese national accounts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 236-248.
    3. Pejman Abedifar & Paolo Giudici & Shatha Hashem, 2017. "Heterogeneous Market Structure and Systemic Risk: Evidence from Dual Banking Systems," DEM Working Papers Series 134, University of Pavia, Department of Economics and Management.
    4. Giudici, Paolo & Abu-Hashish, Iman, 2019. "What determines bitcoin exchange prices? A network VAR approach," Finance Research Letters, Elsevier, vol. 28(C), pages 309-318.
    5. Erick Trevi~no Aguilar, 2020. "The interdependency structure in the Mexican stock exchange: A network approach," Papers 2004.06676, arXiv.org.
    6. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," International Journal of Forecasting, Elsevier, vol. 35(1), pages 25-44.
    7. Khai X. Chiong & Hyungsik Roger Moon, 2017. "Estimation of Graphical Models using the $L_{1,2}$ Norm," Papers 1709.10038, arXiv.org, revised Oct 2017.
    8. Paolo Giudici & Laura Parisi, 2016. "CoRisk: measuring systemic risk through default probability contagion," DEM Working Papers Series 116, University of Pavia, Department of Economics and Management.
    9. Paolo Giudici & Laura Parisi, 2017. "Sovereign risk in the Euro area: a multivariate stochastic process approach," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1995-2008, December.
    10. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.
    11. Chowdhury, Biplob & Dungey, Mardi & Kangogo, Moses & Sayeed, Mohammad Abu & Volkov, Vladimir, 2019. "The changing network of financial market linkages: The Asian experience," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 71-92.
    12. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, Open Access Journal, vol. 6(3), pages 1-19, September.
    13. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2018. "Asset allocation: new evidence through network approaches," Papers 1810.09825, arXiv.org.
    14. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2019. "Smart network based portfolios," Papers 1907.01274, arXiv.org.
    15. Paolo Giudici & Shatha Hashem, 2015. "Systemic risk of Islamic Banks," DEM Working Papers Series 103, University of Pavia, Department of Economics and Management.
    16. Roy Cerqueti & Gian Paolo Clemente & Rosanna Grassi, 2018. "Systemic risk assessment through high order clustering coefficient," Papers 1810.13250, arXiv.org.
    17. Ahelegbey, Daniel Felix & Giudici, Paolo & Hadji-Misheva, Branka, 2018. "Latent Factor Models for Credit Scoring in P2P Systems," MPRA Paper 92636, University Library of Munich, Germany, revised 11 Oct 2018.
    18. Yong Tang & Jason Jie Xiong & Zi-Yang Jia & Yi-Cheng Zhang, 2018. "Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets," Complexity, Hindawi, vol. 2018, pages 1-31, November.
    19. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, Open Access Journal, vol. 7(1), pages 1-25, January.
    20. Paolo Giudici & Laura Parisi, 2015. "Modeling Systemic Risk with Correlated Stochastic Processes," DEM Working Papers Series 110, University of Pavia, Department of Economics and Management.
    21. Frank Emmert-Streib & Aliyu Musa & Kestutis Baltakys & Juho Kanniainen & Shailesh Tripathi & Olli Yli-Harja & Herbert Jodlbauer & Matthias Dehmer, 2017. "Computational Analysis of the structural properties of Economic and Financial Networks," Papers 1710.04455, arXiv.org.
    22. Paolo Bartesaghi & Gian Paolo Clemente & Rosanna Grassi, 2020. "Communicability in the World Trade Network -- A new perspective for community detection," Papers 2001.06356, arXiv.org.
    23. Paola Cerchiello & Paolo Giudici, 2017. "Categorical network models for systemic risk measurement," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(4), pages 1593-1609, July.
    24. Daniel Felix Ahelegbey & Luis Carvalho & Eric D. Kolaczyk, 2020. "A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series," DEM Working Papers Series 181, University of Pavia, Department of Economics and Management.
    25. Paolo Giudici & Peter Sarlin & Alessandro Spelta, 2016. "The multivariate nature of systemic risk: direct and common exposures," DEM Working Papers Series 118, University of Pavia, Department of Economics and Management.

  14. Raffaella Calabrese & Paolo Giudici, 2013. "Estimating bank default with generalised extreme value models," DEM Working Papers Series 035, University of Pavia, Department of Economics and Management.

    Cited by:

    1. D. Bidzhoyan S. & Д. Биджоян С., 2018. "Модель Оценки Вероятности Отзыва Лицензии У Российского Банка // Model For Assessing The Probability Of Revocation Of A License From The Russian Bank," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(2), pages 26-37.
    2. Raffaella Calabrese & Johan A. Elkink & Paolo Giudici, 2014. "Measuring Bank Contagion in Europe Using Binary Spatial Regression Models," DEM Working Papers Series 096, University of Pavia, Department of Economics and Management.
    3. Prosper Senyo Koto, 2017. "Is Social Capital Important In Formal-Informal Sector Linkages?," Journal of Developmental Entrepreneurship (JDE), World Scientific Publishing Co. Pte. Ltd., vol. 22(02), pages 1-16, June.
    4. Raffaella Calabrese & Silvia Osmetti, 2014. "Modelling cross-border systemic risk in the European banking sector: a copula approach," Papers 1411.1348, arXiv.org.

  15. Silvia Figini & Paolo Giudici, 2013. "Measuring risk with ordinal variables," DEM Working Papers Series 032, University of Pavia, Department of Economics and Management.

    Cited by:

    1. Silvia Facchinetti & Paolo Giudici & Silvia Angela Osmetti, 2020. "Cyber risk measurement with ordinal data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 173-185, March.
    2. Clive Hunt & Ross Taplin, 2019. "Aggregation of Incidence and Intensity Risk Variables to Achieve Reconciliation," Risks, MDPI, Open Access Journal, vol. 7(4), pages 1-14, October.
    3. Lee, Byung Kwon & Zhou, Rong & de Souza, Robert & Park, Jaehun, 2016. "Data-driven risk measurement of firm-to-firm relationships in a supply chain," International Journal of Production Economics, Elsevier, vol. 180(C), pages 148-157.

Articles

  1. Giudici, Paolo & Huang, Bihong & Spelta, Alessandro, 2019. "Trade networks and economic fluctuations in Asian countries," Economic Systems, Elsevier, vol. 43(2), pages 1-1.

    Cited by:

    1. Wen-Jie Xie & Na Wei & Wei-Xing Zhou, 2020. "Evolving efficiency and robustness of global oil trade networks," Papers 2004.05325, arXiv.org.

  2. Giudici, Paolo & Abu-Hashish, Iman, 2019. "What determines bitcoin exchange prices? A network VAR approach," Finance Research Letters, Elsevier, vol. 28(C), pages 309-318.

    Cited by:

    1. Corbet, Shaen & Eraslan, Veysel & Lucey, Brian & Sensoy, Ahmet, 2019. "The effectiveness of technical trading rules in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 31(C), pages 32-37.
    2. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, Open Access Journal, vol. 6(3), pages 1-19, September.
    3. Xiong, Jinwu & Liu, Qing & Zhao, Lei, 2020. "A new method to verify Bitcoin bubbles: Based on the production cost," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    4. Roman Matkovskyy & Akanksha Jalan, 2019. "From financial markets to Bitcoin markets: A fresh look at the contagion effect," Post-Print hal-02131637, HAL.
    5. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    6. Al-Yahyaee, Khamis Hamed & Rehman, Mobeen Ur & Mensi, Walid & Al-Jarrah, Idries Mohammad Wanas, 2019. "Can uncertainty indices predict Bitcoin prices? A revisited analysis using partial and multivariate wavelet approaches," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 47-56.
    7. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "High frequency volatility co-movements in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 35-52.
    8. Tiwari, Aviral Kumar & Raheem, Ibrahim Dolapo & Kang, Sang Hoon, 2019. "Time-varying dynamic conditional correlation between stock and cryptocurrency markets using the copula-ADCC-EGARCH model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    9. Aurelio F. Bariviera & Ignasi Merediz-Sol`a, 2020. "Where do we stand in cryptocurrencies economic research? A survey based on hybrid analysis," Papers 2003.09723, arXiv.org.
    10. Alin Marius Andries & Elena Galasan, 2020. "Measuring Financial Contagion and Spillover Effects with a State-Dependent Sensitivity Value-at-Risk Model," Risks, MDPI, Open Access Journal, vol. 8(1), pages 1-20, January.
    11. Bedi, Prateek & Nashier, Tripti, 2020. "On the investment credentials of Bitcoin: A cross-currency perspective," Research in International Business and Finance, Elsevier, vol. 51(C).
    12. Panagiotidis, Theodore & Stengos, Thanasis & Vravosinos, Orestis, 2019. "The effects of markets, uncertainty and search intensity on bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 220-242.

  3. Paolo Giudici & Paolo Pagnottoni, 2019. "High Frequency Price Change Spillovers in Bitcoin Markets," Risks, MDPI, Open Access Journal, vol. 7(4), pages 1-18, November.

    Cited by:

    1. Arianna Agosto & Alessia Cafferata, 2020. "Financial Bubbles: A Study of Co-Explosivity in the Cryptocurrency Market," Risks, MDPI, Open Access Journal, vol. 8(2), pages 1-14, April.
    2. Ying Chen & Paolo Giudici & Branka Hadji Misheva & Simon Trimborn, 2020. "Lead Behaviour in Bitcoin Markets," Risks, MDPI, Open Access Journal, vol. 8(1), pages 1-14, January.
    3. Marina Resta & Paolo Pagnottoni & Maria Elena De Giuli, 2020. "Technical Analysis on the Bitcoin Market: Trading Opportunities or Investors’ Pitfall?," Risks, MDPI, Open Access Journal, vol. 8(2), pages 1-15, May.

  4. Ahelegbey, Daniel Felix & Giudici, Paolo & Hadji-Misheva, Branka, 2019. "Latent factor models for credit scoring in P2P systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 112-121.
    See citations under working paper version above.
  5. Avdjiev, S. & Giudici, P. & Spelta, A., 2019. "Measuring contagion risk in international banking," Journal of Financial Stability, Elsevier, vol. 42(C), pages 36-51.
    See citations under working paper version above.
  6. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.

    Cited by:

    1. Li-Fei Huang, 2018. "Using App Inventor to provide the amortization schedule and the sinking fund schedule," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(04), pages 1-9, December.
    2. Ao Yu & Zhuoqiang Jia & Weike Zhang & Ke Deng & Francisco Herrera, 2020. "A Dynamic Credit Index System for TSMEs in China Using the Delphi and Analytic Hierarchy Process (AHP) Methods," Sustainability, MDPI, Open Access Journal, vol. 12(5), pages 1-21, February.

  7. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, Open Access Journal, vol. 6(3), pages 1-19, September.

    Cited by:

    1. Colin Ellis, 2020. "Are Corporate Bond Defaults Contagious across Sectors?," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 8(1), pages 1-17, January.
    2. Olena Kostylenko & Helena Sofia Rodrigues & Delfim F. M. Torres, 2019. "The spread of a financial virus through Europe and beyond," Papers 1901.07241, arXiv.org.
    3. Matteo Foglia & Eliana Angelini, 2019. "The Time-Spatial Dimension of Eurozone Banking Systemic Risk," Risks, MDPI, Open Access Journal, vol. 7(3), pages 1-25, July.
    4. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, Open Access Journal, vol. 7(1), pages 1-25, January.
    5. Alin Marius Andries & Elena Galasan, 2020. "Measuring Financial Contagion and Spillover Effects with a State-Dependent Sensitivity Value-at-Risk Model," Risks, MDPI, Open Access Journal, vol. 8(1), pages 1-20, January.

  8. Paolo Giudici & Laura Parisi, 2017. "Sovereign risk in the Euro area: a multivariate stochastic process approach," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1995-2008, December.

    Cited by:

    1. Giudici, Paolo & Abu-Hashish, Iman, 2019. "What determines bitcoin exchange prices? A network VAR approach," Finance Research Letters, Elsevier, vol. 28(C), pages 309-318.
    2. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.
    3. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, Open Access Journal, vol. 6(3), pages 1-19, September.
    4. Ahelegbey, Daniel Felix & Giudici, Paolo & Hadji-Misheva, Branka, 2018. "Latent Factor Models for Credit Scoring in P2P Systems," MPRA Paper 92636, University Library of Munich, Germany, revised 11 Oct 2018.

  9. Raffaella Calabrese & Johan A. Elkink & Paolo S. Giudici, 2017. "Measuring bank contagion in Europe using binary spatial regression models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(12), pages 1503-1511, December.
    See citations under working paper version above.
  10. Abedifar, Pejman & Giudici, Paolo & Hashem, Shatha Qamhieh, 2017. "Heterogeneous market structure and systemic risk: Evidence from dual banking systems," Journal of Financial Stability, Elsevier, vol. 33(C), pages 96-119.
    See citations under working paper version above.
  11. P. Giudici & A. Spelta, 2016. "Graphical Network Models for International Financial Flows," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 128-138, January.
    See citations under working paper version above.
  12. Raffaella Calabrese & Paolo Giudici, 2015. "Estimating bank default with generalised extreme value regression models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(11), pages 1783-1792, November.

    Cited by:

    1. Alessandra Amendola & Francesco Giordano & Maria Lucia Parrella & Marialuisa Restaino, 2017. "Variable selection in high‐dimensional regression: a nonparametric procedure for business failure prediction," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 33(4), pages 355-368, August.
    2. Avdjiev, S. & Giudici, P. & Spelta, A., 2019. "Measuring contagion risk in international banking," Journal of Financial Stability, Elsevier, vol. 42(C), pages 36-51.
    3. Calabrese, Raffaella & Degl’Innocenti, Marta & Osmetti, Silvia Angela, 2017. "The effectiveness of TARP-CPP on the US banking industry: A new copula-based approach," European Journal of Operational Research, Elsevier, vol. 256(3), pages 1029-1037.
    4. Raffaella Calabrese & Johan A. Elkink & Paolo Giudici, 2014. "Measuring Bank Contagion in Europe Using Binary Spatial Regression Models," DEM Working Papers Series 096, University of Pavia, Department of Economics and Management.
    5. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.
    6. Silvia Facchinetti & Paolo Giudici & Silvia Angela Osmetti, 2020. "Cyber risk measurement with ordinal data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 173-185, March.
    7. Papanikolaou, Nikolaos I., 2018. "To be bailed out or to be left to fail? A dynamic competing risks hazard analysis," Journal of Financial Stability, Elsevier, vol. 34(C), pages 61-85.
    8. Forgione, Antonio Fabio & Migliardo, Carlo, 2018. "Forecasting distress in cooperative banks: The role of asset quality," International Journal of Forecasting, Elsevier, vol. 34(4), pages 678-695.
    9. Dan Cheng & Pasquale Cirillo, 2019. "An Urn-Based Nonparametric Modeling of the Dependence between PD and LGD with an Application to Mortgages," Risks, MDPI, Open Access Journal, vol. 7(3), pages 1-21, July.
    10. Ahelegbey, Daniel Felix & Giudici, Paolo & Hadji-Misheva, Branka, 2018. "Latent Factor Models for Credit Scoring in P2P Systems," MPRA Paper 92636, University Library of Munich, Germany, revised 11 Oct 2018.
    11. Calabrese, Raffaella & Osmetti, Silvia Angela, 2019. "A new approach to measure systemic risk: A bivariate copula model for dependent censored data," European Journal of Operational Research, Elsevier, vol. 279(3), pages 1053-1064.
    12. Manthoulis, Georgios & Doumpos, Michalis & Zopounidis, Constantin & Galariotis, Emilios, 2020. "An ordinal classification framework for bank failure prediction: Methodology and empirical evidence for US banks," European Journal of Operational Research, Elsevier, vol. 282(2), pages 786-801.
    13. Veni Arakelian & Shatha Qamhieh Hashem, 2020. "The Leaders, the Laggers, and the “Vulnerables”," Risks, MDPI, Open Access Journal, vol. 8(1), pages 1-32, March.
    14. Paolo Giudici & Paolo Pagnottoni, 2019. "High Frequency Price Change Spillovers in Bitcoin Markets," Risks, MDPI, Open Access Journal, vol. 7(4), pages 1-18, November.

  13. Paola Cerchiello & Paolo Giudici, 2014. "On a statistical h index," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 299-312, May.

    Cited by:

    1. Mutz, Rüdiger & Daniel, Hans-Dieter, 2018. "The bibliometric quotient (BQ), or how to measure a researcher’s performance capacity: A Bayesian Poisson Rasch model," Journal of Informetrics, Elsevier, vol. 12(4), pages 1282-1295.

  14. Cerchiello, Paola & Giudici, Paolo, 2012. "On the distribution of functionals of discrete ordinal variables," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 2044-2049.

    Cited by:

    1. 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.
    2. Paola Cerchiello & Paolo Giudici, 2013. "Bayesian Credit Ratings (new version)," DEM Working Papers Series 030, University of Pavia, Department of Economics and Management.
    3. Paola Cerchiello & Paolo Giudici, 2013. "H Index: A Statistical Proposal," DEM Working Papers Series 039, University of Pavia, Department of Economics and Management.
    4. Paola Cerchiello & Paolo Giudici, 2014. "On a statistical h index," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 299-312, May.
    5. Donata Marasini & Piero Quatto, 2014. "A characterization of linear satisfaction measures," METRON, Springer;Sapienza Università di Roma, vol. 72(1), pages 17-23, April.
    6. 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.

  15. Silvia Figini & Paolo Giudici & Pierpaolo Uberti, 2010. "A threshold based approach to merge data in financial risk management," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(11), pages 1815-1824.

    Cited by:

    1. Silvia FIGINI & Ron S. KENETT & Silvia SALINI, 2010. "Integrating operational and financial risk assessments," Departmental Working Papers 2010-02, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    2. Tyrone Lin & Chia-Chi Lee & Yu-Chuan Kuan, 2013. "The optimal operational risk capital requirement by applying the advanced measurement approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(1), pages 85-101, January.
    3. 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.

  16. 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. Aldasoro, Inaki & Gambacorta, Leonardo & giudici, paolo & Leach, Thomas, 2020. "Operational and cyber risks in the financial sector," CEPR Discussion Papers 14418, C.E.P.R. Discussion Papers.
    2. 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.
    3. Fantazzini, Dean, 2008. "Econometric Analysis of Financial Data in Risk Management (continuation). Section III: Managing Operational Risk," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 11(3), pages 87-122.
    4. Paola Cerchiello & Paolo Giudici, 2013. "H Index: A Statistical Proposal," DEM Working Papers Series 039, University of Pavia, Department of Economics and Management.
    5. Paola Cerchiello & Paolo Giudici, 2014. "On a statistical h index," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 299-312, May.
    6. Paolo Giudici, 2015. "Scorecard models for operations management," International Journal of Data Science, Inderscience Enterprises Ltd, vol. 1(1), pages 96-101.
    7. 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.
    8. Silvia Figini & Lijun Gao & Paolo Giudici, 2013. "Bayesian operational risk models," DEM Working Papers Series 047, University of Pavia, Department of Economics and Management.
    9. 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.
    10. 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.
    11. 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, Open Access Journal, vol. 7(2), pages 1-20, May.
    12. 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.
    13. 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.

  17. Bonafede, C.E. & Giudici, P., 2007. "Bayesian Networks for enterprise risk assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 22-28.

    Cited by:

    1. Mkrtchyan, L. & Podofillini, L. & Dang, V.N., 2015. "Bayesian belief networks for human reliability analysis: A review of applications and gaps," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 1-16.
    2. Silvia Figini & Lijun Gao & Paolo Giudici, 2013. "Bayesian operational risk models," DEM Working Papers Series 047, University of Pavia, Department of Economics and Management.
    3. E. Cene & F. Karaman, 2015. "Analysing organic food buyers' perceptions with Bayesian networks: a case study in Turkey," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1572-1590, July.

  18. Cornalba, Chiara & Giudici, Paolo, 2004. "Statistical models for operational risk management," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 166-172.

    Cited by:

    1. 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.
    2. Marco Bardoscia & Roberto Bellotti, 2012. "A Dynamical Approach to Operational Risk Measurement," Papers 1202.2532, arXiv.org.
    3. Paola Cerchiello & Paolo Giudici, 2013. "Bayesian Credit Ratings (new version)," DEM Working Papers Series 030, University of Pavia, Department of Economics and Management.
    4. Sinemis Zengin & Serhat Yuksel, 2016. "A Comparison of the Views of Internal Controllers/Auditors and Branch/Call Center Personnel of the Banks for Operational Risk: A Case for Turkish Banking Sector," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 5(4), pages 10-29, July.
    5. Paolo Giudici, 2015. "Scorecard models for operations management," International Journal of Data Science, Inderscience Enterprises Ltd, vol. 1(1), pages 96-101.
    6. Silvia Figini & Lijun Gao & Paolo Giudici, 2013. "Bayesian operational risk models," DEM Working Papers Series 047, University of Pavia, Department of Economics and Management.
    7. 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.
    8. Mizgier, Kamil J. & Hora, Manpreet & Wagner, Stephan M. & Jüttner, Matthias P., 2015. "Managing operational disruptions through capital adequacy and process improvement," European Journal of Operational Research, Elsevier, vol. 245(1), pages 320-332.
    9. 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.
    10. Paola Cerchiello & Paolo Giudici, 2012. "Bayesian Credit Rating Assessment," DEM Working Papers Series 019, University of Pavia, Department of Economics and Management.
    11. Borunda, Mónica & Jaramillo, O.A. & Reyes, Alberto & Ibargüengoytia, Pablo H., 2016. "Bayesian networks in renewable energy systems: A bibliographical survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 32-45.

  19. Eva-Maria Fronk & Paolo Giudici, 2004. "Markov Chain Monte Carlo model selection for DAG models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 13(3), pages 259-273, December.

    Cited by:

    1. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2012. "Bayesian Graphical Models for Structural Vector Autoregressive Processes," Working Papers 2012:36, Department of Economics, University of Venice "Ca' Foscari".
    2. Helen Armstrong & Christopher K. Carter & Kevin K. F. Wong & Robert Kohn, 2007. "Bayesian Covariance Matrix Estimation using a Mixture of Decomposable Graphical Models," Discussion Papers 2007-13, School of Economics, The University of New South Wales.
    3. B Baesens & C Mues & D Martens & J Vanthienen, 2009. "50 years of data mining and OR: upcoming trends and challenges," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 16-23, May.
    4. Roberto Casarin & Daniel Felix Ahelegbey & Monica Billio, 2014. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Working Papers 2014:29, Department of Economics, University of Venice "Ca' Foscari".
    5. Elie Bouri & Rangan Gupta & Seyedmehdi Hosseini & Chi Keung Marco Lau, 2017. "Does Global Fear Predict Fear in BRICS Stock Markets? Evidence from a Bayesian Graphical VAR Model," Working Papers 201704, University of Pretoria, Department of Economics.

  20. S. P. Brooks & P. Giudici & G. O. Roberts, 2003. "Efficient construction of reversible jump Markov chain Monte Carlo proposal distributions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 3-39, January.

    Cited by:

    1. Rongwei Fu & Dipak K. Dey & Kent E. Holsinger, 2011. "A Beta-Mixture Model for Assessing Genetic Population Structure," Biometrics, The International Biometric Society, vol. 67(3), pages 1073-1082, September.
    2. David I. Hastie & Peter J. Green, 2012. "Model choice using reversible jump Markov chain Monte Carlo," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(3), pages 309-338, August.
    3. Gagnon, Philippe & Bédard, Mylène & Desgagné, Alain, 2019. "Weak convergence and optimal tuning of the reversible jump algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 161(C), pages 32-51.
    4. Ho, Remus K.W. & Hu, Inchi, 2008. "Flexible modelling of random effects in linear mixed models--A Bayesian approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1347-1361, January.
    5. D. Fouskakis & I. Ntzoufras & D. Draper, 2009. "Population‐based reversible jump Markov chain Monte Carlo methods for Bayesian variable selection and evaluation under cost limit restrictions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(3), pages 383-403, July.
    6. Sridhar Narayanan, 2013. "Bayesian estimation of discrete games of complete information," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 39-81, March.
    7. Meyer-Gohde, Alexander & Neuhoff, Daniel, 2018. "Generalized exogenous processes in DSGE: A Bayesian approach," IMFS Working Paper Series 125, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    8. Alzahrani, Naif & Neal, Peter & Spencer, Simon E.F. & McKinley, Trevelyan J. & Touloupou, Panayiota, 2018. "Model selection for time series of count data," Computational Statistics & Data Analysis, Elsevier, vol. 122(C), pages 33-44.
    9. Pandolfi, Silvia & Bartolucci, Francesco & Friel, Nial, 2014. "A generalized multiple-try version of the Reversible Jump algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 298-314.
    10. Azari Soufiani, Hossein & Diao, Hansheng & Lai, Zhenyu & Parkes, David C., 2013. "Generalized Random Utility Models with Multiple Types," Scholarly Articles 12363923, Harvard University Department of Economics.
    11. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.
    12. Griffin, Jim & Steel, Mark F.J., 2008. "Bayesian inference with stochastic volatility models using continuous superpositions of non-Gaussian Ornstein-Uhlenbeck processes," MPRA Paper 11071, University Library of Munich, Germany.
    13. Sridhar Narayanan, 2013. "Bayesian estimation of discrete games of complete information," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 39-81, March.
    14. Overstall, Antony M. & King, Ruth, 2014. "conting: An R Package for Bayesian Analysis of Complete and Incomplete Contingency Tables," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i07).
    15. Helen Armstrong & Christopher K. Carter & Kevin K. F. Wong & Robert Kohn, 2007. "Bayesian Covariance Matrix Estimation using a Mixture of Decomposable Graphical Models," Discussion Papers 2007-13, School of Economics, The University of New South Wales.
    16. Oedekoven, C.S. & King, R. & Buckland, S.T. & Mackenzie, M.L. & Evans, K.O. & Burger, L.W., 2016. "Using hierarchical centering to facilitate a reversible jump MCMC algorithm for random effects models," Computational Statistics & Data Analysis, Elsevier, vol. 98(C), pages 79-90.
    17. Oscar M Rueda & Ramón Díaz-Uriarte, 2007. "Flexible and Accurate Detection of Genomic Copy-Number Changes from aCGH," PLOS Computational Biology, Public Library of Science, vol. 3(6), pages 1-8, June.
    18. Tsung-I Lin & Hsiu Ho & Pao Shen, 2009. "Computationally efficient learning of multivariate t mixture models with missing information," Computational Statistics, Springer, vol. 24(3), pages 375-392, August.
    19. Víctor Enciso‐Mora & Peter Neal & T. Subba Rao, 2009. "Efficient order selection algorithms for integer‐valued ARMA processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 1-18, January.
    20. Liqun Wang & James Fu, 2007. "A practical sampling approach for a Bayesian mixture model with unknown number of components," Statistical Papers, Springer, vol. 48(4), pages 631-653, October.
    21. Kobayashi, Genya, 2014. "A transdimensional approximate Bayesian computation using the pseudo-marginal approach for model choice," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 167-183.
    22. N. Friel & A. N. Pettitt, 2008. "Marginal likelihood estimation via power posteriors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(3), pages 589-607, July.
    23. Bouranis, Lampros & Friel, Nial & Maire, Florian, 2018. "Model comparison for Gibbs random fields using noisy reversible jump Markov chain Monte Carlo," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 221-241.
    24. Yinghui Wei & Peter Neal & Sandra Telfer & Mike Begon, 2012. "Statistical analysis of an endemic disease from a capture--recapture experiment," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(12), pages 2759-2773, August.
    25. Ronald W. Butler & Marc S. Paolella, 2017. "Autoregressive Lag—Order Selection Using Conditional Saddlepoint Approximations," Econometrics, MDPI, Open Access Journal, vol. 5(3), pages 1-33, September.
    26. McVinish, R. & Mengersen, K., 2008. "Semiparametric Bayesian circular statistics," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4722-4730, June.
    27. Streftaris, George & Worton, Bruce J., 2008. "Efficient and accurate approximate Bayesian inference with an application to insurance data," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2604-2622, January.
    28. Rigat, F. & Mira, A., 2012. "Parallel hierarchical sampling: A general-purpose interacting Markov chains Monte Carlo algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1450-1467.
    29. Chigozie E. Utazi, 2017. "Bayesian Single Changepoint Estimation in a Parameter-driven Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(3), pages 765-779, September.
    30. Chen, Langnan & Luo, Jiawen & Liu, Hao, 2013. "The determinants of liquidity with G-RJMCMC-VS model: Evidence from China," Economic Modelling, Elsevier, vol. 35(C), pages 192-198.

  21. Giudici, Paolo & Passerone, Gianluca, 2002. "Data mining of association structures to model consumer behaviour," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 533-541, February.

    Cited by:

    1. Antonoio Forcina, 2019. "Estimation and testing of multiplicative models for frequency data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(7), pages 807-822, October.
    2. Brosig, Stephan & Bavorova, Miroslava, 2019. "Association of attitudes towards genetically modified food among young adults and their referent persons," EconStor Open Access Articles, ZBW - Leibniz Information Centre for Economics, pages 1-19.

  22. Paolo Giudici, 2001. "Bayesian data mining, with application to benchmarking and credit scoring," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 17(1), pages 69-81, January.

    Cited by:

    1. Paola Cerchiello & Paolo Giudici, 2013. "Bayesian Credit Ratings (new version)," DEM Working Papers Series 030, University of Pavia, Department of Economics and Management.
    2. Dan Cheng & Pasquale Cirillo, 2019. "An Urn-Based Nonparametric Modeling of the Dependence between PD and LGD with an Application to Mortgages," Risks, MDPI, Open Access Journal, vol. 7(3), pages 1-21, July.
    3. Ahelegbey, Daniel Felix & Giudici, Paolo & Hadji-Misheva, Branka, 2018. "Latent Factor Models for Credit Scoring in P2P Systems," MPRA Paper 92636, University Library of Munich, Germany, revised 11 Oct 2018.
    4. Lkhagvadorj Munkhdalai & Tsendsuren Munkhdalai & Oyun-Erdene Namsrai & Jong Yun Lee & Keun Ho Ryu, 2019. "An Empirical Comparison of Machine-Learning Methods on Bank Client Credit Assessments," Sustainability, MDPI, Open Access Journal, vol. 11(3), pages 1-23, January.
    5. Paola Cerchiello & Paolo Giudici, 2012. "Bayesian Credit Rating Assessment," DEM Working Papers Series 019, University of Pavia, Department of Economics and Management.

  23. Paolo Giudici & Elena Stanghellini, 2001. "Bayesian inference for graphical factor analysis models," Psychometrika, Springer;The Psychometric Society, vol. 66(4), pages 577-591, December.

    Cited by:

    1. Claudia Tarantola & Paola Vicard, 2002. "Spanning trees and identifiability of a single-factor model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(2), pages 139-152, June.

  24. Paolo Giudici & Tobias Ryden & Pierre Vandekerkhove, 2000. "Likelihood-Ratio Tests for Hidden Markov Models," Biometrics, The International Biometric Society, vol. 56(3), pages 742-747, September.

    Cited by:

    1. Roberto Colombi & Sabrina Giordano, 2011. "Testing lumpability for marginal discrete hidden Markov models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(3), pages 293-311, September.
    2. Bolano, Danilo & Berchtold, André, 2016. "General framework and model building in the class of Hidden Mixture Transition Distribution models," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 131-145.
    3. Jörn Dannemann & Hajo Holzmann, 2008. "Likelihood Ratio Testing for Hidden Markov Models Under Non‐standard Conditions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(2), pages 309-321, June.
    4. Rachel MacKay Altman, 2004. "Assessing the Goodness-of-Fit of Hidden Markov Models," Biometrics, The International Biometric Society, vol. 60(2), pages 444-450, June.
    5. Max Greenfeld & Dmitri S Pavlichin & Hideo Mabuchi & Daniel Herschlag, 2012. "Single Molecule Analysis Research Tool (SMART): An Integrated Approach for Analyzing Single Molecule Data," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-12, February.

  25. Maura Mezzetti & Paolo Giudici, 1999. "Monte Carlo methods for nonparametric survival model determination," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 8(1), pages 49-60, April.

    Cited by:

    1. Eliana Christou & Michael G. Akritas, 2019. "Single index quantile regression for censored data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 655-678, December.

Chapters

  1. Daniel Felix Ahelegbey & Paolo Giudici, 2014. "Bayesian Selection of Systemic Risk Networks," Advances in Econometrics, in: Ivan Jeliazkov & Dale J. Poirier (ed.), Bayesian Model Comparison, volume 34, pages 117-153, Emerald Publishing Ltd.

    Cited by:

    1. Ahelegbey, Daniel Felix & Giudici, Paolo, 2019. "Tree Networks to Assess Financial Contagion," MPRA Paper 92632, University Library of Munich, Germany.
    2. Ahelegbey, Daniel Felix, 2015. "The Econometrics of Bayesian Graphical Models: A Review With Financial Application," MPRA Paper 92634, University Library of Munich, Germany, revised 25 Apr 2016.
    3. Roberto Casarin & Daniel Felix Ahelegbey & Monica Billio, 2014. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Working Papers 2014:29, Department of Economics, University of Venice "Ca' Foscari".
    4. Daniel Felix Ahelegbey, 2015. "The Econometrics of Networks: A Review," Working Papers 2015:13, Department of Economics, University of Venice "Ca' Foscari".

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Rankings

This author is among the top 5% authors according to these criteria:
  1. Number of Downloads through RePEc Services over the past 12 months
  2. Number of Downloads through RePEc Services over the past 12 months, Weighted by Number of Authors
  3. Betweenness measure in co-authorship network

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 32 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 (20) 2013-02-03 2013-02-16 2013-02-16 2013-03-16 2013-10-25 2014-09-25 2014-10-03 2015-06-05 2015-11-21 2016-02-23 2016-03-17 2016-04-04 2016-07-02 2017-02-19 2019-03-25 2020-03-02 2020-03-02 2020-04-06 2020-05-18 2020-05-18. Author is listed
  2. NEP-ECM: Econometrics (8) 2013-02-03 2013-02-16 2013-04-27 2013-10-25 2014-03-01 2014-10-03 2015-06-05 2016-03-17. Author is listed
  3. NEP-BAN: Banking (7) 2013-02-16 2013-03-16 2014-12-13 2016-02-23 2019-08-12 2020-03-02 2020-05-25. Author is listed
  4. NEP-CBA: Central Banking (7) 2013-03-16 2014-09-25 2015-05-22 2015-11-21 2016-02-23 2016-04-04 2016-07-02. Author is listed
  5. NEP-PAY: Payment Systems & Financial Technology (5) 2019-03-25 2019-03-25 2020-03-02 2020-04-06 2020-05-25. Author is listed
  6. NEP-EEC: European Economics (4) 2014-12-13 2015-11-21 2016-02-23 2019-03-25
  7. NEP-NET: Network Economics (4) 2013-10-25 2015-06-05 2016-04-04 2020-02-10
  8. NEP-ORE: Operations Research (3) 2020-04-06 2020-05-18 2020-05-18
  9. NEP-URE: Urban & Real Estate Economics (3) 2014-12-13 2019-03-25 2019-03-25
  10. NEP-ARA: MENA - Middle East & North Africa (2) 2015-06-05 2020-05-18
  11. NEP-FOR: Forecasting (2) 2013-02-16 2014-03-01
  12. NEP-HME: Heterodox Microeconomics (2) 2014-10-03 2016-04-04
  13. NEP-IFN: International Finance (2) 2013-10-25 2019-08-12
  14. NEP-MON: Monetary Economics (2) 2015-05-22 2020-03-02
  15. NEP-SOG: Sociology of Economics (2) 2013-04-27 2015-06-05
  16. NEP-AGR: Agricultural Economics (1) 2020-05-18
  17. NEP-CFN: Corporate Finance (1) 2017-02-19
  18. NEP-CNA: China (1) 2020-04-06
  19. NEP-ENT: Entrepreneurship (1) 2019-03-25
  20. NEP-ETS: Econometric Time Series (1) 2020-04-06
  21. NEP-FMK: Financial Markets (1) 2020-04-06
  22. NEP-IAS: Insurance Economics (1) 2019-03-25
  23. NEP-ICT: Information & Communication Technologies (1) 2020-05-25
  24. NEP-INT: International Trade (1) 2018-07-09
  25. NEP-KNM: Knowledge Management & Knowledge Economy (1) 2018-07-09
  26. NEP-LAW: Law & Economics (1) 2020-05-25
  27. NEP-MAC: Macroeconomics (1) 2015-05-22
  28. NEP-SEA: South East Asia (1) 2018-07-09

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, Paolo Giudici 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 hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.