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Paolo Giudici

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.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Iñaki Aldasoro & Leonardo Gambacorta & Paolo Giudici & Thomas Leach, 2020. "The drivers of cyber risk," BIS Working Papers 865, Bank for International Settlements.

    Mentioned in:

    1. Cyber Risk, Financial Stability and the Payments System
      by Steve Cecchetti and Kim Schoenholtz in Money, Banking and Financial Markets on 2020-07-26 15:50:41

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
    2. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Health
    3. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Modelling > Statistical Modelling
  2. Arianna Agosto & Paolo Giudici, 2020. "A Poisson Autoregressive Model to Understand COVID-19 Contagion Dynamics," Risks, MDPI, vol. 8(3), pages 1-8, July.

    Mentioned in:

    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19
    2. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Health
    3. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Modelling > Statistical Modelling

Working papers

  1. A. Agosto & Alexandra Campmas & P. Giudici & A. Renda, 2021. "Monitoring COVID-19 contagion growth," Post-Print hal-03407115, HAL.

    Cited by:

    1. Ugofilippo Basellini & Carlo Giovanni Camarda, 2020. "Modelling COVID-19 mortality at the regional level in Italy," Working Papers axq0sudakgkzhr-blecv, French Institute for Demographic Studies.
    2. Ray, Evan L. & Brooks, Logan C. & Bien, Jacob & Biggerstaff, Matthew & Bosse, Nikos I. & Bracher, Johannes & Cramer, Estee Y. & Funk, Sebastian & Gerding, Aaron & Johansson, Michael A. & Rumack, Aaron, 2023. "Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1366-1383.

  2. 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.

    Cited by:

    1. Daniel Felix Ahelegbey, 2022. "Statistical Modelling of Downside Risk Spillovers," FinTech, MDPI, vol. 1(2), pages 1-10, April.

  3. 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.

    Cited by:

    1. Daniel Felix Ahelegbey & Paolo Giudici & Fatemeh Mojtahedi, 2022. "Crypto Asset Portfolio Selection," FinTech, MDPI, vol. 1(1), pages 1-9, February.
    2. González-Sánchez, Mariano & Nave Pineda, Juan M., 2023. "Where is the distribution tail threshold? A tale on tail and copulas in financial risk measurement," International Review of Financial Analysis, Elsevier, vol. 86(C).
    3. Bojaj, Martin M. & Muhadinovic, Milica & Bracanovic, Andrej & Mihailovic, Andrej & Radulovic, Mladen & Jolicic, Ivan & Milosevic, Igor & Milacic, Veselin, 2022. "Forecasting macroeconomic effects of stablecoin adoption: A Bayesian approach," Economic Modelling, Elsevier, vol. 109(C).
    4. Daniel Felix Ahelegbey, 2022. "Statistical Modelling of Downside Risk Spillovers," FinTech, MDPI, vol. 1(2), pages 1-10, April.
    5. Babaei, Golnoosh & Giudici, Paolo & Raffinetti, Emanuela, 2022. "Explainable artificial intelligence for crypto asset allocation," Finance Research Letters, Elsevier, vol. 47(PB).
    6. 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.
    7. Zaevski, Tsvetelin S. & Nedeltchev, Dragomir C., 2023. "From BASEL III to BASEL IV and beyond: Expected shortfall and expectile risk measures," International Review of Financial Analysis, Elsevier, vol. 87(C).
    8. Jalan, Akanksha & Matkovskyy, Roman, 2023. "Systemic risks in the cryptocurrency market: Evidence from the FTX collapse," Finance Research Letters, Elsevier, vol. 53(C).
    9. Fang, Sheng & Cao, Guangxi & Egan, Paul, 2023. "Forecasting and backtesting systemic risk in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 54(C).
    10. Zaremba, Adam & Bilgin, Mehmet Huseyin & Long, Huaigang & Mercik, Aleksander & Szczygielski, Jan J., 2021. "Up or down? Short-term reversal, momentum, and liquidity effects in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 78(C).
    11. Francesca Mariani & Gloria Polinesi & Maria Cristina Recchioni, 2022. "A tail-revisited Markowitz mean-variance approach and a portfolio network centrality," Computational Management Science, Springer, vol. 19(3), pages 425-455, July.
    12. Goodell, John W. & Alon, Ilan & Chiaramonte, Laura & Dreassi, Alberto & Paltrinieri, Andrea & Piserà, Stefano, 2023. "Risk substitution in cryptocurrencies: Evidence from BRICS announcements," Emerging Markets Review, Elsevier, vol. 54(C).
    13. Wang, Qunwei & Liu, Mengmeng & Xiao, Ling & Dai, Xingyu & Li, Matthew C. & Wu, Fei, 2022. "Conditional sovereign CDS in market basket risk scenario: A dynamic vine-copula analysis," International Review of Financial Analysis, Elsevier, vol. 80(C).
    14. Samia Nasreen & Aviral Kumar Tiwari & Seong-Min Yoon, 2021. "Dynamic Connectedness and Portfolio Diversification during the Coronavirus Disease 2019 Pandemic: Evidence from the Cryptocurrency Market," Sustainability, MDPI, vol. 13(14), pages 1-14, July.
    15. Naifar, Nader & Shahzad, Syed Jawad Hussain, 2022. "Tail event-based sovereign credit risk transmission network during COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).

  4. 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.

    Cited by:

    1. Ahelegbey, Daniel Felix & Giudici, Paolo & Hashem, Shatha Qamhieh, 2021. "Network VAR models to measure financial contagion," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    2. 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.
    3. Zhang, Ping & Yin, Shiqi & Sha, Yezhou, 2023. "Global systemic risk dynamic network connectedness during the COVID-19: Evidence from nonlinear Granger causality," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).

  5. 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.

    Cited by:

    1. Nenad Milojević & Srdjan Redzepagic, 2021. "Prospects of Artificial Intelligence and Machine Learning Application in Banking Risk Management," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 10(3), pages 41-57.
    2. Ajjima Jiravichai & Ruth Banomyong, 2022. "A Proposed Methodology for Literature Review on Operational Risk Management in Banks," Risks, MDPI, vol. 10(5), pages 1-18, May.
    3. Md. Hamid Uddin & Md. Hakim Ali & Mohammad Kabir Hassan, 2020. "Cybersecurity hazards and financial system vulnerability: a synthesis of literature," Risk Management, Palgrave Macmillan, vol. 22(4), pages 239-309, December.
    4. Eisenbach, Thomas M. & Kovner, Anna & Lee, Michael Junho, 2022. "Cyber risk and the U.S. financial system: A pre-mortem analysis," Journal of Financial Economics, Elsevier, vol. 145(3), pages 802-826.
    5. Rumyana Marinova, 2022. "Accounting Aspects of the Risk of Digital Payment Operations in Bulgarian Banks," Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series, Union of Scientists - Varna, Economic Sciences Section, vol. 11(2), pages 105-113, August.
    6. Cheng, Maoyong & Qu, Yang & Jiang, Chunxia & Zhao, Chenchen, 2022. "Is cloud computing the digital solution to the future of banking?," Journal of Financial Stability, Elsevier, vol. 63(C).
    7. Uddin, Md Hamid & Mollah, Sabur & Islam, Nazrul & Ali, Md Hakim, 2023. "Does digital transformation matter for operational risk exposure?," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    8. Gambacorta, Leonardo & Doerr, Sebastian & Leach, Thomas & Legros, Bertrand & Whyte, David, 2022. "Cyber risk in central banking," CEPR Discussion Papers 17660, C.E.P.R. Discussion Papers.
    9. Aldasoro, Iñaki & Gambacorta, Leonardo & Giudici, Paolo & Leach, Thomas, 2022. "The drivers of cyber risk," Journal of Financial Stability, Elsevier, vol. 60(C).
    10. Carletti, Elena & Claessens, Stijn & Fatás, Antonio & Vives, Xavier (ed.), 2020. "Barcelona Report 2 - The Bank Business Model in the Post-Covid-19 World," Vox eBooks, Centre for Economic Policy Research, number p329.
    11. Andrés Alonso Robisco & José Manuel Carbó Martínez, 2022. "Measuring the model risk-adjusted performance of machine learning algorithms in credit default prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-35, December.

  6. 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.

    Cited by:

    1. Guglielmo Maria Caporale & Woo-Young Kang & Fabio Spagnolo & Nicola Spagnolo, 2021. "The Covid-19 Pandemic, Policy Responses and Stock Markets in the G20," CESifo Working Paper Series 9299, CESifo.
    2. Stefano Cabras, 2021. "A Bayesian-Deep Learning Model for Estimating COVID-19 Evolution in Spain," Mathematics, MDPI, vol. 9(22), pages 1-18, November.
    3. Chénangnon Frédéric Tovissodé & Bruno Enagnon Lokonon & Romain Glèlè Kakaï, 2020. "On the use of growth models to understand epidemic outbreaks with application to COVID-19 data," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-14, October.
    4. Lucio Palazzo & Riccardo Ievoli, 2023. "Detecting Regional Differences in Italian Health Services during Five COVID-19 Waves," Stats, MDPI, vol. 6(2), pages 1-13, April.
    5. Şule Şahin & María del Carmen Boado-Penas & Corina Constantinescu & Julia Eisenberg & Kira Henshaw & Maoqi Hu & Jing Wang & Wei Zhu, 2020. "First Quarter Chronicle of COVID-19: An Attempt to Measure Governments’ Responses," Risks, MDPI, vol. 8(4), pages 1-26, November.

  7. 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.

    Cited by:

    1. Alin Marius Andries & Steven Ongena & Nicu Sprincean & Radu Tunaru, 2020. "Risk Spillovers and Interconnectedness between Systemically Important Institutions," Swiss Finance Institute Research Paper Series 20-40, Swiss Finance Institute.
    2. Shanshan Jiang & Jie Wang & Ruiting Dong & Yutong Li & Min Xia, 2023. "Systemic Risk with Multi-Channel Risk Contagion in the Interbank Market," Sustainability, MDPI, vol. 15(3), pages 1-24, February.
    3. Anca Ionășcuți & Bogdan Dima, 2022. "Contagion effects on financial markets risk," Journal of Financial Studies, Institute of Financial Studies, vol. 12(7), pages 105-133, May.
    4. Kanas, Angelos & Molyneux, Philip & Zervopoulos, Panagiotis D., 2023. "Systemic risk and CO2 emissions in the U.S," Journal of Financial Stability, Elsevier, vol. 64(C).
    5. Li, Jingwei & Li, Shouwei, 2023. "Immunization of systemic risk in trade–investment networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    6. Zhang, Yi & Zhou, Long & Chen, Yajiao & Liu, Fang, 2022. "The contagion effect of jump risk across Asian stock markets during the Covid-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    7. Daniel Felix Ahelegbey & Paola Cerchiello & Roberta Scaramozzino, 2021. "Network Based Evidence of the Financial Impact of Covid-19 Pandemic," DEM Working Papers Series 198, University of Pavia, Department of Economics and Management.

  8. Daniel Felix Ahelegbey & Paolo Giudici, 2020. "NetVIX - A Network Volatility Index of Financial Markets," DEM Working Papers Series 192, University of Pavia, Department of Economics and Management.

    Cited by:

    1. Lv, Jiamin & Ben, Shenglin & Huang, Wenli & Xu, Yueling, 2023. "How to reduce the default contagion risk of intercorporate credit guarantee networks? Evidence from China," Emerging Markets Review, Elsevier, vol. 55(C).
    2. Daniel Felix Ahelegbey, 2022. "Statistical Modelling of Downside Risk Spillovers," FinTech, MDPI, vol. 1(2), pages 1-10, April.
    3. Daniel Felix Ahelegbey & Paola Cerchiello & Roberta Scaramozzino, 2021. "Network Based Evidence of the Financial Impact of Covid-19 Pandemic," DEM Working Papers Series 198, University of Pavia, Department of Economics and Management.

  9. Iñaki Aldasoro & Leonardo Gambacorta & Paolo Giudici & Thomas Leach, 2020. "The drivers of cyber risk," BIS Working Papers 865, Bank for International Settlements.

    Cited by:

    1. Helga Koo & Remco van der Molen & Robert Vermeulen & Ralph Verhoeks & Alessandro Pollastri, 2022. "A macroprudential perspective on cyber risk," Occasional Studies 2001, DNB.
    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. Zängerle, Daniel & Schiereck, Dirk, 2022. "Modelling and predicting enterprise‑level cyber risks in the context of sparse data availability," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 136276, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Malavasi, Matteo & Peters, Gareth W. & Shevchenko, Pavel V. & Trück, Stefan & Jang, Jiwook & Sofronov, Georgy, 2022. "Cyber risk frequency, severity and insurance viability," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 90-114.
    5. Zodwa Z. F. Mthiyane & Huibrecht M. van der Poll & Makgopa F. Tshehla, 2022. "A Framework for Risk Management in Small Medium Enterprises in Developing Countries," Risks, MDPI, vol. 10(9), pages 1-18, September.
    6. Crosignani, Matteo & Macchiavelli, Marco & Silva, André F., 2023. "Pirates without borders: The propagation of cyberattacks through firms’ supply chains," Journal of Financial Economics, Elsevier, vol. 147(2), pages 432-448.
    7. Milena Vučinić & Radoica Luburić, 2022. "Fintech, Risk-Based Thinking and Cyber Risk," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 11(2), pages 27-53.
    8. Bojaj, Martin M. & Muhadinovic, Milica & Bracanovic, Andrej & Mihailovic, Andrej & Radulovic, Mladen & Jolicic, Ivan & Milosevic, Igor & Milacic, Veselin, 2022. "Forecasting macroeconomic effects of stablecoin adoption: A Bayesian approach," Economic Modelling, Elsevier, vol. 109(C).
    9. Gambacorta, Leonardo & Cornelli, Giulio & Doerr, Sebastian & Merrouche, Ouarda, 2020. "Inside the Regulatory Sandbox: Effects on Fintech Funding," CEPR Discussion Papers 15502, C.E.P.R. Discussion Papers.
    10. Wei, Lu & Jing, Haozhe & Huang, Jie & Deng, Yuqi & Jing, Zhongbo, 2023. "Do textual risk disclosures reveal corporate risk? Evidence from U.S. fintech corporations," Economic Modelling, Elsevier, vol. 127(C).
    11. Cristian Roner & Claudia Di Caterina & Davide Ferrari, 2021. "Exponential Tilting for Zero-inflated Interval Regression with Applications to Cyber Security Survey Data," BEMPS - Bozen Economics & Management Paper Series BEMPS85, Faculty of Economics and Management at the Free University of Bozen.
    12. Ajjima Jiravichai & Ruth Banomyong, 2022. "A Proposed Methodology for Literature Review on Operational Risk Management in Banks," Risks, MDPI, vol. 10(5), pages 1-18, May.
    13. Boot, Arnoud & Hoffmann, Peter & Laeven, Luc & Ratnovski, Lev, 2021. "Fintech: what’s old, what’s new?," Journal of Financial Stability, Elsevier, vol. 53(C).
    14. Md. Hamid Uddin & Md. Hakim Ali & Mohammad Kabir Hassan, 2020. "Cybersecurity hazards and financial system vulnerability: a synthesis of literature," Risk Management, Palgrave Macmillan, vol. 22(4), pages 239-309, December.
    15. Ahnert, Toni & Assenmacher, Katrin & Hoffmann, Peter & Leonello, Agnese & Monnet, Cyril & Porcellacchia, Davide, 2022. "The economics of central bank digital currency," CEPR Discussion Papers 17617, C.E.P.R. Discussion Papers.
    16. Eisenbach, Thomas M. & Kovner, Anna & Lee, Michael Junho, 2022. "Cyber risk and the U.S. financial system: A pre-mortem analysis," Journal of Financial Economics, Elsevier, vol. 145(3), pages 802-826.
    17. Costantini, Mauro & Maaitah, Ahmad & Mishra, Tapas & Sousa, Ricardo M., 2023. "Bitcoin market networks and cyberattacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    18. Bikramaditya Ghosh & Spyros Papathanasiou & Georgios Pergeris, 2022. "Did cryptocurrencies exhibit log‐periodic power law signature during the second wave of COVID‐19?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(3), November.
    19. Uddin, Md Hamid & Mollah, Sabur & Islam, Nazrul & Ali, Md Hakim, 2023. "Does digital transformation matter for operational risk exposure?," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    20. Gambacorta, Leonardo & Doerr, Sebastian & Leach, Thomas & Legros, Bertrand & Whyte, David, 2022. "Cyber risk in central banking," CEPR Discussion Papers 17660, C.E.P.R. Discussion Papers.
    21. Martin Eling & Kwangmin Jung, 2022. "Heterogeneity in cyber loss severity and its impact on cyber risk measurement," Risk Management, Palgrave Macmillan, vol. 24(4), pages 273-297, December.
    22. Wang, Xiaoting & Hou, Siyuan & Kyaw, Khine & Xue, Xupeng & Liu, Xueqin, 2023. "Exploring the determinants of Fintech Credit: A comprehensive analysis," Economic Modelling, Elsevier, vol. 126(C).
    23. Matteo Malavasi & Gareth W. Peters & Pavel V. Shevchenko & Stefan Truck & Jiwook Jang & Georgy Sofronov, 2021. "Cyber Risk Frequency, Severity and Insurance Viability," Papers 2111.03366, arXiv.org, revised Mar 2022.
    24. Anand, Kartik & Duley, Chanelle & Gai, Prasanna, 2022. "Cybersecurity and financial stability," Discussion Papers 08/2022, Deutsche Bundesbank.
    25. Agosto, Arianna & Cerchiello, Paola & Pagnottoni, Paolo, 2022. "Sentiment, Google queries and explosivity in the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).

  10. Agosto, Arianna & Ahelegbey, Daniel Felix & Giudici, Paolo, 2020. "Tree Networks to assess Financial Contagion," MPRA Paper 107066, University Library of Munich, Germany.

    Cited by:

    1. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Hussain Shahzad, Syed Jawad & Výrost, Tomáš, 2022. "Measuring systemic risk in the global banking sector: A cross-quantilogram network approach," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics.
    2. Deng, Yang & Zhang, Ziqing & Zhu, Li, 2021. "A model-based index for systemic risk contribution measurement in financial networks," Economic Modelling, Elsevier, vol. 95(C), pages 35-48.
    3. Chong, Zhaohui & Wei, Xiaolin, 2023. "Exploring the spatial linkage network of peer-to-peer lending in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    4. Wang, Haiying & Yuan, Ying & Li, Yiou & Wang, Xunhong, 2021. "Financial contagion and contagion channels in the forex market: A new approach via the dynamic mixture copula-extreme value theory," Economic Modelling, Elsevier, vol. 94(C), pages 401-414.
    5. Laleh Tafakori & Armin Pourkhanali & Riccardo Rastelli, 2022. "Measuring systemic risk and contagion in the European financial network," Empirical Economics, Springer, vol. 63(1), pages 345-389, July.
    6. Su, Zhi & Xu, Fuwei, 2021. "Dynamic identification of systemically important financial markets in the spread of contagion: A ripple network based collective spillover effect approach," Journal of Multinational Financial Management, Elsevier, vol. 60(C).
    7. Fuwei Xu, 2024. "Modeling the Paths of China’s Systemic Financial Risk Contagion: A Ripple Network Perspective Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 47-73, January.
    8. Samitas, Aristeidis & Kampouris, Elias & Polyzos, Stathis, 2022. "Covid-19 pandemic and spillover effects in stock markets: A financial network approach," International Review of Financial Analysis, Elsevier, vol. 80(C).
    9. Okorie, David Iheke & Lin, Boqiang, 2021. "Adaptive market hypothesis: The story of the stock markets and COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    10. Okorie, David Iheke & Lin, Boqiang, 2021. "Stock markets and the COVID-19 fractal contagion effects," Finance Research Letters, Elsevier, vol. 38(C).
    11. Imen Bedoui-Belghith & Slaheddine Hallara & Faouzi Jilani, 2023. "Crisis transmission degree measurement under crisis propagation model," SN Business & Economics, Springer, vol. 3(1), pages 1-27, January.
    12. Ur Rehman, Mobeen & Al Rababa'a, Abdel Razzaq & El-Nader, Ghaith & Alkhataybeh, Ahmad & Vo, Xuan Vinh, 2022. "Modelling the quantile cross-coherence between exchange rates: Does the COVID-19 pandemic change the interlinkage structure?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).

  11. 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.

    Cited by:

    1. Gadzinski, Gregory & Castello, Alessio & Mazzorana, Florie, 2023. "Stablecoins: Does design affect stability?," Finance Research Letters, Elsevier, vol. 53(C).
    2. Olli-Pekka Hilmola, 2021. "On Prices of Privacy Coins and Bitcoin," JRFM, MDPI, vol. 14(8), pages 1-15, August.
    3. Costantini, Mauro & Maaitah, Ahmad & Mishra, Tapas & Sousa, Ricardo M., 2023. "Bitcoin market networks and cyberattacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    4. Sood, Kirti & Singh, Simarjeet & Behl, Abhishek & Sindhwani, Rahul & Kaur, Sandeepa & Pereira, Vijay, 2023. "Identification and prioritization of the risks in the mass adoption of artificial intelligence-driven stable coins: The quest for optimal resource utilization," Resources Policy, Elsevier, vol. 81(C).
    5. Vladimir Balash & Alexey Faizliev & Sergei Sidorov & Elena Chistopolskaya, 2021. "Conditional Time-Varying General Dynamic Factor Models and Its Application to the Measurement of Volatility Spillovers across Russian Assets," Mathematics, MDPI, vol. 9(19), pages 1-31, October.
    6. Yousaf, Imran & Jareño, Francisco & Esparcia, Carlos, 2022. "Tail connectedness between lending/borrowing tokens and commercial bank stocks," International Review of Financial Analysis, Elsevier, vol. 84(C).
    7. Pagnottoni, Paolo, 2023. "Superhighways and roads of multivariate time series shock transmission: Application to cryptocurrency, carbon emission and energy prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    8. Kunkler, Michael, 2023. "A stable aggregate currency revisited: Highlighting some fundamental issues," Economics Letters, Elsevier, vol. 231(C).

  12. 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, vol. 7(1), pages 1-25, January.
    2. Zhang, Xiaoyuan & Zhang, Tianqi, 2022. "Dynamic credit contagion and aggregate loss in networks," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    3. Alin Marius Andries & Steven Ongena & Nicu Sprincean & Radu Tunaru, 2020. "Risk Spillovers and Interconnectedness between Systemically Important Institutions," Swiss Finance Institute Research Paper Series 20-40, Swiss Finance Institute.
    4. Giada Adelfio & Arianna Agosto & Marcello Chiodi & Paolo Giudici, 2021. "Financial contagion through space-time point processes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 665-688, June.
    5. Lv, Jiamin & Ben, Shenglin & Huang, Wenli & Xu, Yueling, 2023. "How to reduce the default contagion risk of intercorporate credit guarantee networks? Evidence from China," Emerging Markets Review, Elsevier, vol. 55(C).
    6. Paolo Giudici & Gloria Polinesi & Alessandro Spelta, 2022. "Network models to improve robot advisory portfolios," Annals of Operations Research, Springer, vol. 313(2), pages 965-989, June.
    7. Ahelegbey, Daniel Felix & Giudici, Paolo & Hashem, Shatha Qamhieh, 2021. "Network VAR models to measure financial contagion," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    8. Daniel Felix Ahelegbey & Paolo Giudici, 2020. "NetVIX - A Network Volatility Index of Financial Markets," DEM Working Papers Series 192, University of Pavia, Department of Economics and Management.
    9. Veni Arakelian & Shatha Qamhieh Hashem, 2020. "The Leaders, the Laggers, and the “Vulnerables”," Risks, MDPI, vol. 8(1), pages 1-32, March.
    10. Bhattacharya, Mita & Inekwe, John Nkwoma & Valenzuela, Maria Rebecca, 2020. "Credit risk and financial integration: An application of network analysis," International Review of Financial Analysis, Elsevier, vol. 72(C).
    11. Capasso Salvatore & D’Uva Marcella, & Fiorelli Cristiana & Napolitano Oreste, 2022. "Assessing the Impact of Country-Specific Sovereign Risk on Financial and Banking System in EMU: the Role of Italy," CSEF Working Papers 654, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    12. Katerina Rigana & Ernst-Jan Camiel Wit & Samantha Cook, 2021. "Using Network-based Causal Inference to Detect the Sources of Contagion in the Currency Market," Papers 2112.13127, arXiv.org.
    13. Zhao, Hong & Li, Jiayi & Lei, Yiqing & Zhou, Mingming, 2022. "Risk spillover of banking across regions: Evidence from the belt and road countries," Emerging Markets Review, Elsevier, vol. 52(C).
    14. Pierre L. Siklos & Martin Stefan, 2021. "Exchange rate shocks in multicurrency interbank markets," CAMA Working Papers 2021-44, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Yun Feng & Xin Li, 2022. "The Cross-Shareholding Network and Risk Contagion from Stochastic Shocks: An Investigation Based on China’s Market," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 357-381, January.
    16. Capasso, Salvatore & D'Uva, Marcella & Fiorelli, Cristiana & Napolitano, Oreste, 2023. "Cross-border Italian sovereign risk transmission in EMU countries," Economic Modelling, Elsevier, vol. 126(C).
    17. Leonard Sabetti & Ronald Heijmans, 2020. "Shallow or deep? Detecting anomalous flows in the Canadian Automated Clearing and Settlement System using an autoencoder," Working Papers 681, DNB.
    18. Jakob Grazzini & Alessandro Spelta, 2015. "An empirical analysis of the global input-output network and its evolution," DISCE - Working Papers del Dipartimento di Economia e Finanza def031, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    19. Marwan Alzoubi & Ayman Abdalmajeed Alsmadi & Hamad kasasbeh, 2022. "Systemically Important Bank: A Bibliometric Analysis for the Period of 2002 to 2022," SAGE Open, , vol. 12(4), pages 21582440221, December.
    20. Kanas, Angelos & Molyneux, Philip & Zervopoulos, Panagiotis D., 2023. "Systemic risk and CO2 emissions in the U.S," Journal of Financial Stability, Elsevier, vol. 64(C).
    21. 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.
    22. Chen, Wang & Zhang, Zhiwen & Hamori, Shigeyuki & Kinkyo, Takuji, 2021. "Not all bank systemic risks are alike: Deposit insurance and bank risk revisited," International Review of Financial Analysis, Elsevier, vol. 77(C).
    23. Hai-Yen Chang & Lien-Wen Liang & Yu-Luan Liu, 2021. "Using Environmental, Social, Governance (ESG) and Financial Indicators to Measure Bank Cost Efficiency in Asia," Sustainability, MDPI, vol. 13(20), pages 1-20, October.
    24. Li, Fei & Kang, Hao & Xu, Jingfeng, 2022. "Financial stability and network complexity: A random matrix approach," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 177-185.
    25. Flori, Andrea & Pammolli, Fabio & Spelta, Alessandro, 2021. "Commodity prices co-movements and financial stability: A multidimensional visibility nexus with climate conditions," Journal of Financial Stability, Elsevier, vol. 54(C).
    26. Asror Nigmonov & Syed Shams, 2021. "COVID-19 pandemic risk and probability of loan default: evidence from marketplace lending market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-28, December.
    27. Nie, Chun-Xiao, 2022. "Analysis of critical events in the correlation dynamics of cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).

  13. 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.

    Cited by:

    1. Luis Alberto Geraldo-Campos & Juan J. Soria & Tamara Pando-Ezcurra, 2022. "Machine Learning for Credit Risk in the Reactive Peru Program: A Comparison of the Lasso and Ridge Regression Models," Economies, MDPI, vol. 10(8), pages 1-21, July.
    2. Štefan Lyócsa & Petra Vašaničová & Branka Hadji Misheva & Marko Dávid Vateha, 2022. "Default or profit scoring credit systems? Evidence from European and US peer-to-peer lending markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    3. Zanin, Luca, 2020. "Combining multiple probability predictions in the presence of class imbalance to discriminate between potential bad and good borrowers in the peer-to-peer lending market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).

  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.

    Cited by:

    1. Ahelegbey, Daniel & Giudici, Paolo & Pediroda, Valentino, 2023. "A network based fintech inclusion platform," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    2. 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. Chen, Xiao & Chong, Zhaohui & Giudici, Paolo & Huang, Bihong, 2022. "Network centrality effects in peer to peer lending," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    4. Chong, Zhaohui & Wei, Xiaolin, 2023. "Exploring the spatial linkage network of peer-to-peer lending in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    5. Tang, Xinyin & Feng, Chong & Zhu, Jianping & He, Minna, 2022. "How Can We Learn from Borrowers’ Online Behaviors? The Signal Effect of Borrowers’ Platform Involvement on Their Credit Risk," SocArXiv qga8j, Center for Open Science.
    6. Lisa Crosato & Caterina Liberati & Marco Repetto, 2021. "Look Who's Talking: Interpretable Machine Learning for Assessing Italian SMEs Credit Default," Papers 2108.13914, arXiv.org, revised Sep 2021.

  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.

    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, vol. 7(1), pages 1-25, January.
    2. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, vol. 6(3), pages 1-19, September.
    3. Zhang, Xiaoyuan & Zhang, Tianqi, 2022. "Dynamic credit contagion and aggregate loss in networks," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    4. Alin Marius Andries & Steven Ongena & Nicu Sprincean & Radu Tunaru, 2020. "Risk Spillovers and Interconnectedness between Systemically Important Institutions," Swiss Finance Institute Research Paper Series 20-40, Swiss Finance Institute.
    5. Aysan, Ahmet Faruk & Unal, Ibrahim Musa, 2022. "Fintech, Digitalization, And Blockchain In Inslamic Finance: Retrospective Investigation," MPRA Paper 115399, University Library of Munich, Germany.
    6. Addi, Abdelhamid & Bouoiyour, Jamal, 2023. "Interconnectedness and extreme risk: Evidence from dual banking systems," Economic Modelling, Elsevier, vol. 120(C).
    7. Pagnottoni, Paolo & Spelta, Alessandro & Pecora, Nicolò & Flori, Andrea & Pammolli, Fabio, 2021. "Financial earthquakes: SARS-CoV-2 news shock propagation in stock and sovereign bond markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    8. Ahmed A. Elamer & Collins G. Ntim & Hussein A. Abdou & Andrews Owusu & Mohamed Elmagrhi & Awad Elsayed Awad Ibrahim, 2021. "Are bank risk disclosures informative? Evidence from debt markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1270-1298, January.
    9. Ahmet Faruk Aysan & Abdelilah Belatik & Ibrahim Musa Unal & Rachid Ettaai, 2022. "Fintech Strategies of Islamic Banks: A Global Empirical Analysis," FinTech, MDPI, vol. 1(2), pages 1-10, June.
    10. Mushtaq Hussain Khan & Mohammad Bitar & Amine Tarazi & Arshad Hassan & Ahmad Fraz, 2021. "Corruption and bank risk-taking: The deterring role of Shari'ah supervision," Working Papers hal-03366460, HAL.
    11. Chao, Xiangrui & Ran, Qin & Chen, Jia & Li, Tie & Qian, Qian & Ergu, Daji, 2022. "Regulatory technology (Reg-Tech) in financial stability supervision: Taxonomy, key methods, applications and future directions," International Review of Financial Analysis, Elsevier, vol. 80(C).
    12. Leong, Soon Heng & Pellegrini, Carlo Bellavite & Urga, Giovanni, 2020. "The contribution of shadow insurance to systemic risk," Journal of Financial Stability, Elsevier, vol. 51(C).
    13. Lele Zhou & Maowei Chen & Hyangsook Lee, 2022. "Supply Chain Finance: A Research Review and Prospects Based on a Systematic Literature Analysis from a Financial Ecology Perspective," Sustainability, MDPI, vol. 14(21), pages 1-27, November.
    14. Abdelsalam, Omneya & Elnahass, Marwa & Batten, Jonathan A. & Mollah, Sabur, 2021. "New insights into bank asset securitization: The impact of religiosity," Journal of Financial Stability, Elsevier, vol. 54(C).
    15. Ma, Yu & Zhang, Yang & Ji, Qiang, 2021. "Do oil shocks affect Chinese bank risk?," Energy Economics, Elsevier, vol. 96(C).
    16. Julien Chevallier & Dominique Guégan & Stéphane Goutte, 2021. "Is It Possible to Forecast the Price of Bitcoin?," Post-Print halshs-04250269, HAL.
    17. M. Kabir Hassan & Md Nurul Islam Sohel & Tonmoy Choudhury & Mamunur Rashid, 2024. "A systematic literature review of risks in Islamic banking system: research agenda and future research directions," Risk Management, Palgrave Macmillan, vol. 26(1), pages 1-29, February.
    18. Ibrahim Musa Unal & Ahmet Faruk Aysan, 2022. "Fintech, Digitalization, and Blockchain in Islamic Finance: Retrospective Investigation," FinTech, MDPI, vol. 1(4), pages 1-11, November.
    19. Kok, Seng Kiong & Filomeni, Stefano, 2021. "The holding behavior of Shariah financial assets within the global Islamic financial sector: A macroeconomic and firm-based model," Global Finance Journal, Elsevier, vol. 50(C).
    20. Elsayed, Ahmed H. & Naifar, Nader & Uddin, Gazi Salah & Wang, Gang-Jin, 2023. "Multilayer information spillover networks between oil shocks and banking sectors: Evidence from oil-rich countries," International Review of Financial Analysis, Elsevier, vol. 87(C).
    21. Abuzayed, Bana & Al-Fayoumi, Nedal, 2021. "Risk spillover from crude oil prices to GCC stock market returns: New evidence during the COVID-19 outbreak," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    22. Kok, Seng Kiong & Giorgioni, Gianluigi & Farquhar, Stuart, 2022. "The trade-off between knowledge accumulation and independence: The case of the Shariah supervisory board within the Shariah governance and firm performance nexus," Research in International Business and Finance, Elsevier, vol. 59(C).
    23. Zaremba, Adam & Bilgin, Mehmet Huseyin & Long, Huaigang & Mercik, Aleksander & Szczygielski, Jan J., 2021. "Up or down? Short-term reversal, momentum, and liquidity effects in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 78(C).
    24. Francesca Mariani & Gloria Polinesi & Maria Cristina Recchioni, 2022. "A tail-revisited Markowitz mean-variance approach and a portfolio network centrality," Computational Management Science, Springer, vol. 19(3), pages 425-455, July.
    25. Abedifar, Pejman & Bouslah, Kais & Qamhieh Hashem, Shatha & Song, Liang, 2020. "How informative are stock prices of Islamic Banks?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 66(C).
    26. Hai-Yen Chang & Lien-Wen Liang & Yu-Luan Liu, 2021. "Using Environmental, Social, Governance (ESG) and Financial Indicators to Measure Bank Cost Efficiency in Asia," Sustainability, MDPI, vol. 13(20), pages 1-20, October.
    27. Li, Fei & Kang, Hao & Xu, Jingfeng, 2022. "Financial stability and network complexity: A random matrix approach," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 177-185.
    28. Khan, Mushtaq Hussain & Fraz, Ahmad & Hassan, Arshad & Abedifar, Pejman, 2020. "Female board representation, risk-taking and performance: Evidence from dual banking systems," Finance Research Letters, Elsevier, vol. 37(C).
    29. Naifar, Nader & Shahzad, Syed Jawad Hussain, 2022. "Tail event-based sovereign credit risk transmission network during COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).
    30. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.
    31. 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.

  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.

    Cited by:

    1. Chatterjee, Somnath & Jobst, Andreas, 2019. "Market-implied systemic risk and shadow capital adequacy," Bank of England working papers 823, Bank of England.
    2. 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.
    3. Laleh Tafakori & Armin Pourkhanali & Riccardo Rastelli, 2022. "Measuring systemic risk and contagion in the European financial network," Empirical Economics, Springer, vol. 63(1), pages 345-389, July.

  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.

    Cited by:

    1. Lukas Boeckelmann & Arthur Stalla-Bourdillon, 2021. "Structural Estimation of Time-Varying Spillovers:an Application to International Credit Risk Transmission," Working Papers hal-03338209, HAL.

  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.

    Cited by:

    1. Nicholas S. Coleman & Andromachi Georgosouli & Tara N. 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.).

  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.

    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.
    2. Le, Richard & Ku, Hyejin, 2022. "Reducing systemic risk in a multi-layer network using reinforcement learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).

  20. 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.

  21. 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 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.
    2. Scaramozzino, Roberta & Cerchiello, Paola & Aste, Tomaso, 2021. "Information theoretic causality detection between financial and sentiment data," LSE Research Online Documents on Economics 110903, London School of Economics and Political Science, LSE Library.
    3. Nicola, Giancarlo & Cerchiello, Paola & Aste, Tomaso, 2020. "Information network modeling for U.S. banking systemic risk," LSE Research Online Documents on Economics 107563, London School of Economics and Political Science, LSE Library.
    4. Daniel Felix Ahelegbey & Paola Cerchiello & Roberta Scaramozzino, 2021. "Network Based Evidence of the Financial Impact of Covid-19 Pandemic," DEM Working Papers Series 198, University of Pavia, Department of Economics and Management.

  22. 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 & 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.
    2. Paola Cerchiello & Giancarlo Nicola, 2017. "Assessing News Contagion in Finance," DEM Working Papers Series 139, University of Pavia, Department of Economics and Management.
    3. Paola Cerchiello & Giancarlo Nicola, 2018. "Assessing News Contagion in Finance," Econometrics, MDPI, vol. 6(1), pages 1-19, February.
    4. Daniel Felix Ahelegbey & Paola Cerchiello & Roberta Scaramozzino, 2021. "Network Based Evidence of the Financial Impact of Covid-19 Pandemic," DEM Working Papers Series 198, University of Pavia, Department of Economics and Management.
    5. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.

  23. 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. Jong Wook Lee & So Young Sohn, 2021. "Evaluating borrowers’ default risk with a spatial probit model reflecting the distance in their relational network," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-11, December.
    2. Matteo Foglia & Eliana Angelini, 2019. "The Time-Spatial Dimension of Eurozone Banking Systemic Risk," Risks, MDPI, vol. 7(3), pages 1-25, July.
    3. Chen, Yi-Pei & Chen, Yu-Lun & Chiang, Shu-Hen & Mo, Wan-Shin, 2023. "Determinants of connectedness in financial institutions: Evidence from Taiwan," Emerging Markets Review, Elsevier, vol. 55(C).
    4. A.F. Shorikov & A.S. Filippova & V.A. Tyulyukin, 2020. "Optimal Adaptive Control of Employees Number and Sales System of the Bank," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 19(3), pages 348-369.
    5. Islam, Raisul & Volkov, Vladimir, 2020. "Contagion or interdependence? Comparing signed and unsigned spillovers," Working Papers 2020-05, University of Tasmania, Tasmanian School of Business and Economics.
    6. März, Steven & Stelk, Ines & Stelzer, Franziska, 2022. "Are tenants willing to pay for energy efficiency? Evidence from a small-scale spatial analysis in Germany," Energy Policy, Elsevier, vol. 161(C).
    7. Meier, Samira & Rodriguez Gonzalez, Miguel & Kunze, Frederik, 2021. "The global financial crisis, the EMU sovereign debt crisis and international financial regulation: lessons from a systematic literature review," International Review of Law and Economics, Elsevier, vol. 65(C).
    8. 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.

  24. 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.

  25. 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.

  26. 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.

    Cited by:

    1. Silvia Figini & Roberto Savona & Marika Vezzoli, 2016. "Corporate Default Prediction Model Averaging: A Normative Linear Pooling Approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(1-2), pages 6-20, January.

  27. 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. 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.
    3. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, vol. 7(1), pages 1-25, January.
    4. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, vol. 6(3), pages 1-19, September.
    5. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2018. "Asset allocation: new evidence through network approaches," Papers 1810.09825, arXiv.org.
    6. Zhang, Xiaoyuan & Zhang, Tianqi, 2022. "Dynamic credit contagion and aggregate loss in networks," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    7. 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.
    8. Alin Marius Andries & Steven Ongena & Nicu Sprincean & Radu Tunaru, 2020. "Risk Spillovers and Interconnectedness between Systemically Important Institutions," Swiss Finance Institute Research Paper Series 20-40, Swiss Finance Institute.
    9. Giada Adelfio & Arianna Agosto & Marcello Chiodi & Paolo Giudici, 2021. "Financial contagion through space-time point processes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 665-688, June.
    10. Erick Treviño Aguilar, 2020. "The interdependency structure in the Mexican stock exchange: A network approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-31, October.
    11. 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.
    12. 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.
    13. 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.
    14. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2019. "Smart network based portfolios," Papers 1907.01274, arXiv.org.
    15. Bhattacharya, Mita & Inekwe, John Nkwoma & Valenzuela, Maria Rebecca, 2020. "Credit risk and financial integration: An application of network analysis," International Review of Financial Analysis, Elsevier, vol. 72(C).
    16. Mikhail Stolbov & Daniil Parfenov, 2023. "Credit risk linkages in the international banking network, 2000–2019," Risk Management, Palgrave Macmillan, vol. 25(3), pages 1-38, September.
    17. Paolo Bartesaghi & Gian Paolo Clemente & Rosanna Grassi, 2020. "Community structure in the World Trade Network based on communicability distances," Papers 2001.06356, arXiv.org, revised Jul 2020.
    18. Chao, Xiangrui & Ran, Qin & Chen, Jia & Li, Tie & Qian, Qian & Ergu, Daji, 2022. "Regulatory technology (Reg-Tech) in financial stability supervision: Taxonomy, key methods, applications and future directions," International Review of Financial Analysis, Elsevier, vol. 80(C).
    19. 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.
    20. 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.
    21. Paolo Giudici & Shatha Hashem, 2015. "Systemic risk of Islamic Banks," DEM Working Papers Series 103, University of Pavia, Department of Economics and Management.
    22. Makoto Naraoka & Teruaki Hayashi & Takaaki Yoshino & Toshiaki Sugie & Kota Takano & Yukio Ohsawa, 2021. "Explaining Dynamic Changes in Various Asset’s Relationships in Financial Markets," The Review of Socionetwork Strategies, Springer, vol. 15(2), pages 597-611, November.
    23. Yun Feng & Xin Li, 2022. "The Cross-Shareholding Network and Risk Contagion from Stochastic Shocks: An Investigation Based on China’s Market," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 357-381, January.
    24. Sigríður Benediktsdóttir & Margrét V. Bjarnadóttir & Guðmundur A. Hansen, 2016. "Large exposure estimation through automatic business group identification," Annals of Operations Research, Springer, vol. 247(2), pages 503-521, December.
    25. Roy Cerqueti & Gian Paolo Clemente & Rosanna Grassi, 2018. "Systemic risk assessment through high order clustering coefficient," Papers 1810.13250, arXiv.org, revised Jul 2020.
    26. Roy Cerqueti & Gian Paolo Clemente & Rosanna Grassi, 2021. "Systemic risk assessment through high order clustering coefficient," Annals of Operations Research, Springer, vol. 299(1), pages 1165-1187, April.
    27. 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.
    28. Lucas Paiva de Carvalho & Tanya Araújo, 2023. "The Dynamics of Exchange Traded Funds: a geometrical and topological approach," Working Papers REM 2023/0302, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    29. Pagnottoni, Paolo & Spelta, Alessandro, 2023. "The motifs of risk transmission in multivariate time series: Application to commodity prices," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    30. Emma Apps, 2020. "Applying a Bayesian Network to VaR Calculations," Working Papers 202024, University of Liverpool, Department of Economics.
    31. Erick Trevi~no Aguilar, 2020. "The interdependency structure in the Mexican stock exchange: A network approach," Papers 2004.06676, arXiv.org.
    32. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," International Journal of Forecasting, Elsevier, vol. 35(1), pages 25-44.
    33. 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.
    34. Zhu, Bo & Liu, Jiahao & Lin, Renda & Chevallier, Julien, 2021. "Cross-border systemic risk spillovers in the global oil system: Does the oil trade pattern matter?," Energy Economics, Elsevier, vol. 101(C).
    35. Jinzhou Li & Marloes H. Maathuis, 2021. "GGM knockoff filter: False discovery rate control for Gaussian graphical models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(3), pages 534-558, July.
    36. 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.
    37. Kanas, Angelos & Molyneux, Philip & Zervopoulos, Panagiotis D., 2023. "Systemic risk and CO2 emissions in the U.S," Journal of Financial Stability, Elsevier, vol. 64(C).
    38. 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.
    39. 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.
    40. Li, Jingwei & Li, Shouwei, 2023. "Immunization of systemic risk in trade–investment networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    41. 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.
    42. Nicola, Giancarlo & Cerchiello, Paola & Aste, Tomaso, 2020. "Information network modeling for U.S. banking systemic risk," LSE Research Online Documents on Economics 107563, London School of Economics and Political Science, LSE Library.
    43. Chen, Naixi & Fan, Hong, 2023. "Credit risk contagion and optimal dual control—An SIS/R model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 210(C), pages 448-472.
    44. Laurenţiu Cătălin Hinoveanu & Fabrizio Leisen & Cristiano Villa, 2020. "A loss‐based prior for Gaussian graphical models," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 62(4), pages 444-466, December.
    45. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2022. "Smart network based portfolios," Annals of Operations Research, Springer, vol. 316(2), pages 1519-1541, September.
    46. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2021. "Asset allocation: new evidence through network approaches," Annals of Operations Research, Springer, vol. 299(1), pages 61-80, April.
    47. Ying Chen & Paolo Giudici & Branka Hadji Misheva & Simon Trimborn, 2020. "Lead Behaviour in Bitcoin Markets," Risks, MDPI, vol. 8(1), pages 1-14, January.
    48. Pagnottoni, Paolo & Spelta, Alessandro & Flori, Andrea & Pammolli, Fabio, 2022. "Climate change and financial stability: Natural disaster impacts on global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    49. Daniel Felix Ahelegbey & Paola Cerchiello & Roberta Scaramozzino, 2021. "Network Based Evidence of the Financial Impact of Covid-19 Pandemic," DEM Working Papers Series 198, University of Pavia, Department of Economics and Management.
    50. 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.
    51. Paolo Bartesaghi & Gian Paolo Clemente & Rosanna Grassi, 2022. "Community structure in the World Trade Network based on communicability distances," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(2), pages 405-441, April.
    52. Hull, Isaiah & Sattath, Or & Diamanti, Eleni & Wendin, Göran, 2020. "Quantum Technology for Economists," Working Paper Series 398, Sveriges Riksbank (Central Bank of Sweden).
    53. 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.
    54. Gian Paolo Clemente & Rosanna Grassi & Chiara Pederzoli, 2020. "Networks and market-based measures of systemic risk: the European banking system in the aftermath of the financial crisis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 159-181, January.
    55. 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.
    56. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.

  28. 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 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.
    3. Raffaella Calabrese & Silvia Osmetti, 2014. "Modelling cross-border systemic risk in the European banking sector: a copula approach," Papers 1411.1348, arXiv.org.
    4. 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.

  29. 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, 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. Daniele Pala & Enea Parimbelli & Cristiana Larizza & Cindy Cheng & Manuel Ottaviano & Andrea Pogliaghi & Goran Đukić & Aleksandar Jovanović & Ognjen Milićević & Vladimir Urošević & Paola Cerchiello & , 2022. "A New Interactive Tool to Visualize and Analyze COVID-19 Data: The PERISCOPE Atlas," IJERPH, MDPI, vol. 19(15), pages 1-16, July.

    Cited by:

    1. Petr Iakovlevitch Ekel & Sandro Laudares & Adriano José de Barros & Douglas Alexandre Gomes Vieira & Carlos Augusto Paiva da Silva Martins & Matheus Pereira Libório, 2023. "Geovisualization: A Practical Approach for COVID-19 Spatial Analysis," Geographies, MDPI, vol. 3(4), pages 1-16, December.
    2. Ekaterina Ignatenko & Manuel Ribeiro & Mónica D. Oliveira, 2022. "Informing the Design of Data Visualization Tools to Monitor the COVID-19 Pandemic in Portugal: A Web-Delphi Participatory Approach," IJERPH, MDPI, vol. 19(17), pages 1-18, September.
    3. Cheng, Cindy & Messerschmidt, Luca & Bravo, Isaac & Waldbauer, Marco & Bhavikatti, Rohan & Schenk, Caress & Grujic, Vanja & Model, Tim & Kubinec, Robert & Barceló, Joan, 2023. "A General Guide for Harmonizing Data," OSF Preprints baf2j, Center for Open Science.
    4. Nathaniel R. Geyer & Eugene J. Lengerich, 2023. "LionVu: A Data-Driven Geographical Web-GIS Tool for Community Health and Decision-Making in a Catchment Area," Geographies, MDPI, vol. 3(2), pages 1-17, April.

  2. Aldasoro, Iñaki & Gambacorta, Leonardo & Giudici, Paolo & Leach, Thomas, 2022. "The drivers of cyber risk," Journal of Financial Stability, Elsevier, vol. 60(C).
    See citations under working paper version above.
  3. Paolo Giudici & Gloria Polinesi & Alessandro Spelta, 2022. "Network models to improve robot advisory portfolios," Annals of Operations Research, Springer, vol. 313(2), pages 965-989, June.

    Cited by:

    1. Roman Mestre, 2023. "Stock profiling using time–frequency-varying systematic risk measure," Post-Print hal-04058285, HAL.

  4. Ahelegbey, Daniel Felix & Giudici, Paolo, 2022. "NetVIX — A network volatility index of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    See citations under working paper version above.
  5. Giudici, Paolo & Leach, Thomas & Pagnottoni, Paolo, 2022. "Libra or Librae? Basket based stablecoins to mitigate foreign exchange volatility spillovers," Finance Research Letters, Elsevier, vol. 44(C).
    See citations under working paper version above.
  6. Chen, Xiao & Chong, Zhaohui & Giudici, Paolo & Huang, Bihong, 2022. "Network centrality effects in peer to peer lending," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).

    Cited by:

    1. Chong, Zhaohui & Wei, Xiaolin, 2023. "Exploring the spatial linkage network of peer-to-peer lending in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    2. Wang, Jin & Li, Rui, 2023. "Asymmetric information in peer-to-peer lending: empirical evidence from China," Finance Research Letters, Elsevier, vol. 51(C).

  7. Babaei, Golnoosh & Giudici, Paolo & Raffinetti, Emanuela, 2022. "Explainable artificial intelligence for crypto asset allocation," Finance Research Letters, Elsevier, vol. 47(PB).

    Cited by:

    1. Jacopo Fior & Luca Cagliero & Paolo Garza, 2022. "Leveraging Explainable AI to Support Cryptocurrency Investors," Future Internet, MDPI, vol. 14(9), pages 1-19, August.
    2. Wei Jie Yeo & Wihan van der Heever & Rui Mao & Erik Cambria & Ranjan Satapathy & Gianmarco Mengaldo, 2023. "A Comprehensive Review on Financial Explainable AI," Papers 2309.11960, arXiv.org.
    3. Berger, Theo, 2023. "Explainable artificial intelligence and economic panel data: A study on volatility spillover along the supply chains," Finance Research Letters, Elsevier, vol. 54(C).

  8. Ahelegbey, Daniel Felix & Giudici, Paolo & Hashem, Shatha Qamhieh, 2021. "Network VAR models to measure financial contagion," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    See citations under working paper version above.
  9. Paolo Giudici & Gloria Polinesi, 2021. "Crypto price discovery through correlation networks," Annals of Operations Research, Springer, vol. 299(1), pages 443-457, April.

    Cited by:

    1. Khalfaoui, Rabeh & Mefteh-Wali, Salma & Dogan, Buhari & Ghosh, Sudeshna, 2023. "Extreme spillover effect of COVID-19 pandemic-related news and cryptocurrencies on green bond markets: A quantile connectedness analysis," International Review of Financial Analysis, Elsevier, vol. 86(C).
    2. Akyildirim, Erdinc & Cepni, Oguzhan & Corbet, Shaen & Uddin, Gazi Salah, 2020. "Forecasting Mid-price Movement of Bitcoin Futures Using Machine Learning," Working Papers 20-2020, Copenhagen Business School, Department of Economics.
    3. Paolo Giudici & Gloria Polinesi & Alessandro Spelta, 2022. "Network models to improve robot advisory portfolios," Annals of Operations Research, Springer, vol. 313(2), pages 965-989, June.
    4. Lennart Ante, 2022. "The Non-Fungible Token (NFT) Market and Its Relationship with Bitcoin and Ethereum," FinTech, MDPI, vol. 1(3), pages 1-9, June.
    5. Fulvia Pennoni & Francesco Bartolucci & Gianfranco Forte & Ferdinando Ametrano, 2022. "Exploring the dependencies among main cryptocurrency log‐returns: A hidden Markov model," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(1), February.
    6. Nicolás Magner & Nicolás Hardy, 2022. "Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle," Mathematics, MDPI, vol. 10(13), pages 1-27, July.
    7. Fabian Woebbeking, 2021. "Cryptocurrency volatility markets," Digital Finance, Springer, vol. 3(3), pages 273-298, December.
    8. Babaei, Golnoosh & Giudici, Paolo & Raffinetti, Emanuela, 2022. "Explainable artificial intelligence for crypto asset allocation," Finance Research Letters, Elsevier, vol. 47(PB).
    9. Su, Fei & Wang, Xinyi & Yuan, Yulin, 2022. "The intraday dynamics and intraday price discovery of bitcoin," Research in International Business and Finance, Elsevier, vol. 60(C).
    10. Amzallag, Adrien, 2022. "Fund portfolio networks: A climate risk perspective," International Review of Financial Analysis, Elsevier, vol. 84(C).
    11. Wei, Lu & Jing, Haozhe & Huang, Jie & Deng, Yuqi & Jing, Zhongbo, 2023. "Do textual risk disclosures reveal corporate risk? Evidence from U.S. fintech corporations," Economic Modelling, Elsevier, vol. 127(C).
    12. Arianna Agosto & Alessia Cafferata, 2020. "Financial Bubbles: A Study of Co-Explosivity in the Cryptocurrency Market," Risks, MDPI, vol. 8(2), pages 1-14, April.
    13. Costantini, Mauro & Maaitah, Ahmad & Mishra, Tapas & Sousa, Ricardo M., 2023. "Bitcoin market networks and cyberattacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    14. Julien Chevallier & Dominique Guégan & Stéphane Goutte, 2021. "Is It Possible to Forecast the Price of Bitcoin?," Post-Print halshs-04250269, HAL.
    15. Bikramaditya Ghosh & Spyros Papathanasiou & Georgios Pergeris, 2022. "Did cryptocurrencies exhibit log‐periodic power law signature during the second wave of COVID‐19?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(3), November.
    16. Rasoul Amirzadeh & Asef Nazari & Dhananjay Thiruvady & Mong Shan Ee, 2023. "Modelling Determinants of Cryptocurrency Prices: A Bayesian Network Approach," Papers 2303.16148, arXiv.org.
    17. Bejaoui, Azza & Frikha, Wajdi & Jeribi, Ahmed & Bariviera, Aurelio F., 2023. "Connectedness between emerging stock markets, gold, cryptocurrencies, DeFi and NFT: Some new evidence from wavelet analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    18. Ying Chen & Paolo Giudici & Branka Hadji Misheva & Simon Trimborn, 2020. "Lead Behaviour in Bitcoin Markets," Risks, MDPI, vol. 8(1), pages 1-14, January.
    19. Sasan Barak & Navid Parvini, 2023. "Transfer‐entropy‐based dynamic feature selection for evaluating Bitcoin price drivers," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(12), pages 1695-1726, December.
    20. Timothy King & Dimitrios Koutmos, 2021. "Herding and feedback trading in cryptocurrency markets," Annals of Operations Research, Springer, vol. 300(1), pages 79-96, May.
    21. Liu, Ying Lin & Zhang, Jing Jie & Fang, Yan, 2023. "The driving factors of China's carbon prices: Evidence from using ICEEMDAN-HC method and quantile regression," Finance Research Letters, Elsevier, vol. 54(C).
    22. Agosto, Arianna & Cerchiello, Paola & Pagnottoni, Paolo, 2022. "Sentiment, Google queries and explosivity in the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    23. Nie, Chun-Xiao, 2022. "Analysis of critical events in the correlation dynamics of cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    24. Jun Deng & Huifeng Pan & Shuyu Zhang & Bin Zou, 2021. "Optimal Bitcoin trading with inverse futures," Annals of Operations Research, Springer, vol. 304(1), pages 139-163, September.

  10. Ahelegbey, Daniel Felix & Giudici, Paolo & Mojtahedi, Fatemeh, 2021. "Tail risk measurement in crypto-asset markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    See citations under working paper version above.
  11. Niklas Bussmann & Paolo Giudici & Dimitri Marinelli & Jochen Papenbrock, 2021. "Explainable Machine Learning in Credit Risk Management," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 203-216, January.

    Cited by:

    1. Chen, Dangxing & Ye, Jiahui & Ye, Weicheng, 2023. "Interpretable selective learning in credit risk," Research in International Business and Finance, Elsevier, vol. 65(C).
    2. Ahelegbey, Daniel & Giudici, Paolo & Pediroda, Valentino, 2023. "A network based fintech inclusion platform," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    3. Babaei, Golnoosh & Giudici, Paolo & Raffinetti, Emanuela, 2022. "Explainable artificial intelligence for crypto asset allocation," Finance Research Letters, Elsevier, vol. 47(PB).
    4. Dangxing Chen, 2023. "Can I Trust the Explanations? Investigating Explainable Machine Learning Methods for Monotonic Models," Papers 2309.13246, arXiv.org.
    5. Hoang Hiep Nguyen & Jean-Laurent Viviani & Sami Ben Jabeur, 2023. "Bankruptcy prediction using machine learning and Shapley additive explanations," Post-Print hal-04223161, HAL.
    6. Zhang, Tianjiao & Zhu, Weidong & Wu, Yong & Wu, Zihao & Zhang, Chao & Hu, Xue, 2023. "An explainable financial risk early warning model based on the DS-XGBoost model," Finance Research Letters, Elsevier, vol. 56(C).
    7. Yanhui Shen, 2023. "American Option Pricing using Self-Attention GRU and Shapley Value Interpretation," Papers 2310.12500, arXiv.org.
    8. Julien Chevallier & Dominique Guégan & Stéphane Goutte, 2021. "Is It Possible to Forecast the Price of Bitcoin?," Post-Print halshs-04250269, HAL.
    9. Marc Wildi & Branka Hadji Misheva, 2022. "A Time Series Approach to Explainability for Neural Nets with Applications to Risk-Management and Fraud Detection," Papers 2212.02906, arXiv.org.
    10. Alhanouf Abdulrahman Saleh Alsuwailem & Emad Salem & Abdul Khader Jilani Saudagar, 2023. "Performance of Different Machine Learning Algorithms in Detecting Financial Fraud," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1631-1667, December.
    11. Wei Jie Yeo & Wihan van der Heever & Rui Mao & Erik Cambria & Ranjan Satapathy & Gianmarco Mengaldo, 2023. "A Comprehensive Review on Financial Explainable AI," Papers 2309.11960, arXiv.org.
    12. Kim Long Tran & Hoang Anh Le & Thanh Hien Nguyen & Duc Trung Nguyen, 2022. "Explainable Machine Learning for Financial Distress Prediction: Evidence from Vietnam," Data, MDPI, vol. 7(11), pages 1-12, November.
    13. Berger, Theo, 2023. "Explainable artificial intelligence and economic panel data: A study on volatility spillover along the supply chains," Finance Research Letters, Elsevier, vol. 54(C).
    14. Md Shajalal & Alexander Boden & Gunnar Stevens, 2022. "Explainable product backorder prediction exploiting CNN: Introducing explainable models in businesses," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2107-2122, December.
    15. Elena Ivona DUMITRESCU & Sullivan HUE & Christophe HURLIN & Sessi TOKPAVI, 2020. "Machine Learning or Econometrics for Credit Scoring: Let’s Get the Best of Both Worlds," LEO Working Papers / DR LEO 2839, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    16. Chen, Yujia & Calabrese, Raffaella & Martin-Barragan, Belen, 2024. "Interpretable machine learning for imbalanced credit scoring datasets," European Journal of Operational Research, Elsevier, vol. 312(1), pages 357-372.
    17. Ajitha Kumari Vijayappan Nair Biju & Ann Susan Thomas & J Thasneem, 2024. "Examining the research taxonomy of artificial intelligence, deep learning & machine learning in the financial sphere—a bibliometric analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(1), pages 849-878, February.
    18. Babaei, Golnoosh & Giudici, Paolo & Raffinetti, Emanuela, 2023. "Explainable FinTech lending," Journal of Economics and Business, Elsevier, vol. 125.
    19. Sunghyon Kyeong & Daehee Kim & Jinho Shin, 2021. "Can System Log Data Enhance the Performance of Credit Scoring?—Evidence from an Internet Bank in Korea," Sustainability, MDPI, vol. 14(1), pages 1-12, December.
    20. Mohsin Ali & Abdul Razaque & Joon Yoo & Uskenbayeva Raissa Kabievna & Aiman Moldagulova & Satybaldiyeva Ryskhan & Kalpeyeva Zhuldyz & Aizhan Kassymova, 2024. "Designing an Intelligent Scoring System for Crediting Manufacturers and Importers of Goods in Industry 4.0," Logistics, MDPI, vol. 8(1), pages 1-30, March.
    21. Bastos, João A. & Matos, Sara M., 2022. "Explainable models of credit losses," European Journal of Operational Research, Elsevier, vol. 301(1), pages 386-394.
    22. Lisa Crosato & Caterina Liberati & Marco Repetto, 2021. "Look Who's Talking: Interpretable Machine Learning for Assessing Italian SMEs Credit Default," Papers 2108.13914, arXiv.org, revised Sep 2021.
    23. Alex Gramegna & Paolo Giudici, 2020. "Why to Buy Insurance? An Explainable Artificial Intelligence Approach," Risks, MDPI, vol. 8(4), pages 1-9, December.
    24. David Mhlanga, 2021. "Financial Inclusion in Emerging Economies: The Application of Machine Learning and Artificial Intelligence in Credit Risk Assessment," IJFS, MDPI, vol. 9(3), pages 1-16, July.

  12. Giada Adelfio & Arianna Agosto & Marcello Chiodi & Paolo Giudici, 2021. "Financial contagion through space-time point processes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 665-688, June.

    Cited by:

    1. Pagnottoni, Paolo & Spelta, Alessandro & Flori, Andrea & Pammolli, Fabio, 2022. "Climate change and financial stability: Natural disaster impacts on global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    2. Imen Bedoui-Belghith & Slaheddine Hallara & Faouzi Jilani, 2023. "Crisis transmission degree measurement under crisis propagation model," SN Business & Economics, Springer, vol. 3(1), pages 1-27, January.

  13. Paolo Giudici & Emanuela Raffinetti, 2021. "Cyber risk ordering with rank-based statistical models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(3), pages 469-484, September.

    Cited by:

    1. Matteo Malavasi & Gareth W. Peters & Pavel V. Shevchenko & Stefan Truck & Jiwook Jang & Georgy Sofronov, 2021. "Cyber Risk Frequency, Severity and Insurance Viability," Papers 2111.03366, arXiv.org, revised Mar 2022.

  14. Alex Gramegna & Paolo Giudici, 2020. "Why to Buy Insurance? An Explainable Artificial Intelligence Approach," Risks, MDPI, vol. 8(4), pages 1-9, December.

    Cited by:

    1. Emer Owens & Barry Sheehan & Martin Mullins & Martin Cunneen & Juliane Ressel & German Castignani, 2022. "Explainable Artificial Intelligence (XAI) in Insurance," Risks, MDPI, vol. 10(12), pages 1-50, December.
    2. Wei Jie Yeo & Wihan van der Heever & Rui Mao & Erik Cambria & Ranjan Satapathy & Gianmarco Mengaldo, 2023. "A Comprehensive Review on Financial Explainable AI," Papers 2309.11960, arXiv.org.
    3. Alex Gramegna & Paolo Giudici, 2022. "Shapley Feature Selection," FinTech, MDPI, vol. 1(1), pages 1-9, February.
    4. Esther Salmerón-Manzano, 2021. "Legaltech and Lawtech: Global Perspectives, Challenges, and Opportunities," Laws, MDPI, vol. 10(2), pages 1-9, April.
    5. Siti Nurasyikin Shamsuddin & Noriszura Ismail & R. Nur-Firyal, 2023. "Life Insurance Prediction and Its Sustainability Using Machine Learning Approach," Sustainability, MDPI, vol. 15(13), pages 1-20, July.
    6. Javier Sada Bittini & Salvador Cruz Rambaud & Joaquín López Pascual & Roberto Moro-Visconti, 2022. "Business Models and Sustainability Plans in the FinTech, InsurTech, and PropTech Industry: Evidence from Spain," Sustainability, MDPI, vol. 14(19), pages 1-21, September.

  15. Ying Chen & Paolo Giudici & Branka Hadji Misheva & Simon Trimborn, 2020. "Lead Behaviour in Bitcoin Markets," Risks, MDPI, vol. 8(1), pages 1-14, January.

    Cited by:

    1. Fulvia Pennoni & Francesco Bartolucci & Gianfranco Forte & Ferdinando Ametrano, 2022. "Exploring the dependencies among main cryptocurrency log‐returns: A hidden Markov model," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(1), February.
    2. Arianna Agosto & Alessia Cafferata, 2020. "Financial Bubbles: A Study of Co-Explosivity in the Cryptocurrency Market," Risks, MDPI, vol. 8(2), pages 1-14, April.

  16. Arianna Agosto & Paolo Giudici, 2020. "COVID-19 contagion and digital finance," Digital Finance, Springer, vol. 2(1), pages 159-167, September.

    Cited by:

    1. Asror Nigmonov & Syed Shams, 2021. "COVID-19 pandemic risk and probability of loan default: evidence from marketplace lending market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-28, December.

  17. 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.

    Cited by:

    1. Yen, Kuang-Chieh & Nie, Wei-Ying & Chang, Hsuan-Ling & Chang, Li-Han, 2023. "Cryptocurrency return dependency and economic policy uncertainty," Finance Research Letters, Elsevier, vol. 56(C).
    2. Alin Marius Andries & Steven Ongena & Nicu Sprincean & Radu Tunaru, 2020. "Risk Spillovers and Interconnectedness between Systemically Important Institutions," Swiss Finance Institute Research Paper Series 20-40, Swiss Finance Institute.
    3. Shahzad, Syed Jawad Hussain & Bouri, Elie & Ahmad, Tanveer & Naeem, Muhammad Abubakr, 2022. "Extreme tail network analysis of cryptocurrencies and trading strategies," Finance Research Letters, Elsevier, vol. 44(C).
    4. Paolo Giudici & Gloria Polinesi & Alessandro Spelta, 2022. "Network models to improve robot advisory portfolios," Annals of Operations Research, Springer, vol. 313(2), pages 965-989, June.
    5. Giudici, Paolo & Leach, Thomas & Pagnottoni, Paolo, 2022. "Libra or Librae? Basket based stablecoins to mitigate foreign exchange volatility spillovers," Finance Research Letters, Elsevier, vol. 44(C).
    6. Pagnottoni, Paolo & Spelta, Alessandro & Pecora, Nicolò & Flori, Andrea & Pammolli, Fabio, 2021. "Financial earthquakes: SARS-CoV-2 news shock propagation in stock and sovereign bond markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    7. Fulvia Pennoni & Francesco Bartolucci & Gianfranco Forte & Ferdinando Ametrano, 2022. "Exploring the dependencies among main cryptocurrency log‐returns: A hidden Markov model," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(1), February.
    8. Jong-Min Kim & Chanho Cho & Chulhee Jun, 2022. "Forecasting the Price of the Cryptocurrency Using Linear and Nonlinear Error Correction Model," JRFM, MDPI, vol. 15(2), pages 1-10, February.
    9. Bouri, Elie & Saeed, Tareq & Vo, Xuan Vinh & Roubaud, David, 2021. "Quantile connectedness in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    10. Gianna Figá-Talamanca & Sergio Focardi & Marco Patacca, 2021. "Common dynamic factors for cryptocurrencies and multiple pair-trading statistical arbitrages," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 863-882, December.
    11. Arianna Agosto & Alessia Cafferata, 2020. "Financial Bubbles: A Study of Co-Explosivity in the Cryptocurrency Market," Risks, MDPI, vol. 8(2), pages 1-14, April.
    12. Nikolaos A. Kyriazis, 2021. "Investigating the diversifying or hedging nexus of cannabis cryptocurrencies with major digital currencies," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 845-861, December.
    13. Costantini, Mauro & Maaitah, Ahmad & Mishra, Tapas & Sousa, Ricardo M., 2023. "Bitcoin market networks and cyberattacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    14. Francesca Mariani & Gloria Polinesi & Maria Cristina Recchioni, 2022. "A tail-revisited Markowitz mean-variance approach and a portfolio network centrality," Computational Management Science, Springer, vol. 19(3), pages 425-455, July.
    15. Ying Chen & Paolo Giudici & Branka Hadji Misheva & Simon Trimborn, 2020. "Lead Behaviour in Bitcoin Markets," Risks, MDPI, vol. 8(1), pages 1-14, January.
    16. Pagnottoni, Paolo & Spelta, Alessandro & Flori, Andrea & Pammolli, Fabio, 2022. "Climate change and financial stability: Natural disaster impacts on global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    17. Nicoló Andrea Caserini & Paolo Pagnottoni, 2022. "Effective transfer entropy to measure information flows in credit markets," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 729-757, October.
    18. Stylianos Asimakopoulos & Marco Lorusso & Francesco Ravazzolo, 2019. "A New Economic Framework: A DSGE Model with Cryptocurrency," Working Papers No 07/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    19. Paolo Giudici & Paolo Pagnottoni, 2019. "High Frequency Price Change Spillovers in Bitcoin Markets," Risks, MDPI, vol. 7(4), pages 1-18, November.
    20. Vladimir Balash & Alexey Faizliev & Sergei Sidorov & Elena Chistopolskaya, 2021. "Conditional Time-Varying General Dynamic Factor Models and Its Application to the Measurement of Volatility Spillovers across Russian Assets," Mathematics, MDPI, vol. 9(19), pages 1-31, October.
    21. Achraf Ghorbel & Ahmed Jeribi, 2021. "Investigating the relationship between volatilities of cryptocurrencies and other financial assets," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 817-843, December.
    22. Marina Resta & Paolo Pagnottoni & Maria Elena De Giuli, 2020. "Technical Analysis on the Bitcoin Market: Trading Opportunities or Investors’ Pitfall?," Risks, MDPI, vol. 8(2), pages 1-15, May.
    23. Agosto, Arianna & Cerchiello, Paola & Pagnottoni, Paolo, 2022. "Sentiment, Google queries and explosivity in the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    24. Nie, Chun-Xiao, 2022. "Analysis of critical events in the correlation dynamics of cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    25. Urom, Christian & Abid, Ilyes & Guesmi, Khaled & Chevallier, Julien, 2020. "Quantile spillovers and dependence between Bitcoin, equities and strategic commodities," Economic Modelling, Elsevier, vol. 93(C), pages 230-258.
    26. Pagnottoni, Paolo, 2023. "Superhighways and roads of multivariate time series shock transmission: Application to cryptocurrency, carbon emission and energy prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    27. Yianni Doumenis & Javad Izadi & Pradeep Dhamdhere & Epameinondas Katsikas & Dimitrios Koufopoulos, 2021. "A Critical Analysis of Volatility Surprise in Bitcoin Cryptocurrency and Other Financial Assets," Risks, MDPI, vol. 9(11), pages 1-15, November.

  18. Paolo Giudici & Emanuela Raffinetti, 2020. "Lorenz Model Selection," Journal of Classification, Springer;The Classification Society, vol. 37(3), pages 754-768, October.

    Cited by:

    1. Babaei, Golnoosh & Giudici, Paolo & Raffinetti, Emanuela, 2022. "Explainable artificial intelligence for crypto asset allocation," Finance Research Letters, Elsevier, vol. 47(PB).
    2. Giudici, Paolo & Gramegna, Alex & Raffinetti, Emanuela, 2023. "Machine Learning Classification Model Comparison," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    3. Agarwal, Shivam & Muckley, Cal B. & Neelakantan, Parvati, 2023. "Countering racial discrimination in algorithmic lending: A case for model-agnostic interpretation methods," Economics Letters, Elsevier, vol. 226(C).

  19. Arianna Agosto & Paolo Giudici, 2020. "A Poisson Autoregressive Model to Understand COVID-19 Contagion Dynamics," Risks, MDPI, vol. 8(3), pages 1-8, July.
    See citations under working paper version above.
  20. Fatemeh Mojtahedi & Seyed Mojtaba Mojaverian & Daniel F. Ahelegbey & Paolo Giudici, 2020. "Tail Risk Transmission: A Study of the Iran Food Industry," Risks, MDPI, vol. 8(3), pages 1-17, July.
    See citations under working paper version above.
  21. 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.

    Cited by:

    1. Paolo Giudici & Emanuela Raffinetti, 2021. "Cyber risk ordering with rank-based statistical models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(3), pages 469-484, September.

  22. Agosto, Arianna & Ahelegbey, Daniel Felix & Giudici, Paolo, 2020. "Tree networks to assess financial contagion," Economic Modelling, Elsevier, vol. 85(C), pages 349-366.
    See citations under working paper version above.
  23. 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. N. Wei & W. -J. Xie & W. -X. Zhou, 2021. "Robustness of the international oil trade network under targeted attacks to economies," Papers 2101.10679, arXiv.org, revised Jan 2021.
    2. Wen-Jie Xie & Na Wei & Wei-Xing Zhou, 2020. "Evolving efficiency and robustness of global oil trade networks," Papers 2004.05325, arXiv.org.
    3. Wei, Na & Xie, Wen-Jie & Zhou, Wei-Xing, 2022. "Robustness of the international oil trade network under targeted attacks to economies," Energy, Elsevier, vol. 251(C).
    4. Ma, Xinxin & Zong, Xiangyu & Chen, Ximing, 2022. "Economic fitness and economy growth potentiality: Evidence from BRICS and OECD countries," Finance Research Letters, Elsevier, vol. 50(C).
    5. Di, Jinghan & Wen, Zongguo & Jiang, Meihui & Miatto, Alessio, 2022. "Patterns and features of embodied environmental flow networks in the international trade of metal resources: A study of aluminum," Resources Policy, Elsevier, vol. 77(C).

  24. 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. Le, TN-Lan & Abakah, Emmanuel Joel Aikins & Tiwari, Aviral Kumar, 2021. "Time and frequency domain connectedness and spill-over among fintech, green bonds and cryptocurrencies in the age of the fourth industrial revolution," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    2. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, vol. 6(3), pages 1-19, September.
    3. Mensi, Walid & Ur Rehman, Mobeen & Maitra, Debasish & Hamed Al-Yahyaee, Khamis & Sensoy, Ahmet, 2020. "Does bitcoin co-move and share risk with Sukuk and world and regional Islamic stock markets? Evidence using a time-frequency approach," Research in International Business and Finance, Elsevier, vol. 53(C).
    4. Uzonwanne, Godfrey, 2021. "Volatility and return spillovers between stock markets and cryptocurrencies," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 30-36.
    5. Shaen Corbet & John W. Goodell & Samet Gunay & Kerem Kaskaloglu, 2023. "Are DeFi tokens a separate asset class from conventional cryptocurrencies?," Annals of Operations Research, Springer, vol. 322(2), pages 609-630, March.
    6. Paolo Giudici & Gloria Polinesi & Alessandro Spelta, 2022. "Network models to improve robot advisory portfolios," Annals of Operations Research, Springer, vol. 313(2), pages 965-989, June.
    7. Fousekis, Panos & Tzaferi, Dimitra, 2021. "Returns and volume: Frequency connectedness in cryptocurrency markets," Economic Modelling, Elsevier, vol. 95(C), pages 13-20.
    8. Farman Ullah Khan & Faridoon Khan & Parvez Ahmed Shaikh, 2023. "Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms," Future Business Journal, Springer, vol. 9(1), pages 1-11, December.
    9. 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).
    10. 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).
    11. Νikolaos A. Kyriazis & Paraskevi Prassa, 2019. "Which Cryptocurrencies Are Mostly Traded in Distressed Times?," JRFM, MDPI, vol. 12(3), pages 1-12, August.
    12. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2023. "Multivariate dynamics between emerging markets and digital asset markets: An application of the SNP-DCC model," Emerging Markets Review, Elsevier, vol. 56(C).
    13. Wu, Xiangling & Ding, Shusheng, 2023. "The impact of the Bitcoin price on carbon neutrality: Evidence from futures markets," Finance Research Letters, Elsevier, vol. 56(C).
    14. Roman Matkovskyy & Akanksha Jalan, 2019. "From financial markets to Bitcoin markets: A fresh look at the contagion effect," Post-Print hal-02131637, HAL.
    15. Kwon, Ji Ho, 2020. "Tail behavior of Bitcoin, the dollar, gold and the stock market index," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    16. Yang, Boyu & Sun, Yuying & Wang, Shouyang, 2020. "A novel two-stage approach for cryptocurrency analysis," International Review of Financial Analysis, Elsevier, vol. 72(C).
    17. Rico-Peña, Juan Jesús & Arguedas-Sanz, Raquel & López-Martin, Carmen, 2023. "Models used to characterise blockchain features. A systematic literature review and bibliometric analysis," Technovation, Elsevier, vol. 123(C).
    18. Aggarwal, Divya & Chandrasekaran, Shabana & Annamalai, Balamurugan, 2020. "A complete empirical ensemble mode decomposition and support vector machine-based approach to predict Bitcoin prices," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    19. Park, Sangjin & Jang, Kwahngsoo & Yang, Jae-Suk, 2021. "Information flow between bitcoin and other financial assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    20. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    21. Borgards, Oliver & Czudaj, Robert L., 2020. "The prevalence of price overreactions in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    22. Giudici, Paolo & Raffinetti, Emanuela, 2023. "SAFE Artificial Intelligence in finance," Finance Research Letters, Elsevier, vol. 56(C).
    23. Arianna Agosto & Alessia Cafferata, 2020. "Financial Bubbles: A Study of Co-Explosivity in the Cryptocurrency Market," Risks, MDPI, vol. 8(2), pages 1-14, April.
    24. 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.
    25. Nikolaos A. Kyriazis, 2021. "Investigating the diversifying or hedging nexus of cannabis cryptocurrencies with major digital currencies," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 845-861, December.
    26. 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.
    27. Costantini, Mauro & Maaitah, Ahmad & Mishra, Tapas & Sousa, Ricardo M., 2023. "Bitcoin market networks and cyberattacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    28. Paolo Giudici & Gloria Polinesi, 2021. "Crypto price discovery through correlation networks," Annals of Operations Research, Springer, vol. 299(1), pages 443-457, April.
    29. Moratis, George, 2021. "Quantifying the spillover effect in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 38(C).
    30. Corbet, Shaen & Hou, Yang & Hu, Yang & Oxley, Les, 2020. "The influence of the COVID-19 pandemic on asset-price discovery: Testing the case of Chinese informational asymmetry," International Review of Financial Analysis, Elsevier, vol. 72(C).
    31. Haffar, Adlane & Le Fur, Eric, 2021. "Structural vector error correction modelling of Bitcoin price," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 170-178.
    32. Rehman, Mobeen Ur & Katsiampa, Paraskevi & Zeitun, Rami & Vo, Xuan Vinh, 2023. "Conditional dependence structure and risk spillovers between Bitcoin and fiat currencies," Emerging Markets Review, Elsevier, vol. 55(C).
    33. Paolo Giudici & Emanuela Raffinetti, 2020. "Lorenz Model Selection," Journal of Classification, Springer;The Classification Society, vol. 37(3), pages 754-768, October.
    34. 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.
    35. Alin Marius Andries & Elena Galasan, 2020. "Measuring Financial Contagion and Spillover Effects with a State-Dependent Sensitivity Value-at-Risk Model," Risks, MDPI, vol. 8(1), pages 1-20, January.
    36. 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.
    37. Feriel Gharbi, 2019. "Time-varying volatility spillovers among bitcoin and commodity currencies," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 8(4), pages 1-2.
    38. Hanif, Waqas & Areola Hernandez, Jose & Troster, Victor & Kang, Sang Hoon & Yoon, Seong-Min, 2022. "Nonlinear dependence and spillovers between cryptocurrency and global/regional equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    39. Ji, Qiang & Bouri, Elie & Kristoufek, Ladislav & Lucey, Brian, 2021. "Realised volatility connectedness among Bitcoin exchange markets," Finance Research Letters, Elsevier, vol. 38(C).
    40. Yuanyuan (Catherine) Chen, 2021. "Empirical analysis of bitcoin price," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(4), pages 692-715, October.
    41. Bejaoui, Azza & Frikha, Wajdi & Jeribi, Ahmed & Bariviera, Aurelio F., 2023. "Connectedness between emerging stock markets, gold, cryptocurrencies, DeFi and NFT: Some new evidence from wavelet analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    42. Parthajit Kayal & Purnima Rohilla, 2021. "Bitcoin in the economics and finance literature: a survey," SN Business & Economics, Springer, vol. 1(7), pages 1-21, July.
    43. 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).
    44. Ying Chen & Paolo Giudici & Branka Hadji Misheva & Simon Trimborn, 2020. "Lead Behaviour in Bitcoin Markets," Risks, MDPI, vol. 8(1), pages 1-14, January.
    45. Say Keat Ooi & Chai Aun Ooi & Jasmine A. L. Yeap & Tok Hao Goh, 2021. "Embracing Bitcoin: users’ perceived security and trust," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(4), pages 1219-1237, August.
    46. Daniel Felix Ahelegbey & Paola Cerchiello & Roberta Scaramozzino, 2021. "Network Based Evidence of the Financial Impact of Covid-19 Pandemic," DEM Working Papers Series 198, University of Pavia, Department of Economics and Management.
    47. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    48. 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.
    49. Gregoriou, Greg N. & Racicot, François-Éric & Théoret, Raymond, 2021. "The response of hedge fund tail risk to macroeconomic shocks: A nonlinear VAR approach," Economic Modelling, Elsevier, vol. 94(C), pages 843-872.
    50. Ahmed M. Khedr & Ifra Arif & Pravija Raj P V & Magdi El‐Bannany & Saadat M. Alhashmi & Meenu Sreedharan, 2021. "Cryptocurrency price prediction using traditional statistical and machine‐learning techniques: A survey," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(1), pages 3-34, January.
    51. Yi, Shuyue & Xu, Zishuang & Wang, Gang-Jin, 2018. "Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 98-114.
    52. Zhou, Yang & Xie, Chi & Wang, Gang-Jin & Zhu, You & Uddin, Gazi Salah, 2023. "Analysing and forecasting co-movement between innovative and traditional financial assets based on complex network and machine learning," Research in International Business and Finance, Elsevier, vol. 64(C).
    53. 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.
    54. Choi, Hyungeun, 2021. "Investor attention and bitcoin liquidity: Evidence from bitcoin tweets," Finance Research Letters, Elsevier, vol. 39(C).
    55. Kim, Hyeonoh & Ha, Chang Yong & Ahn, Kwangwon, 2022. "Preference heterogeneity in Bitcoin and its forks' network," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    56. Gaies, Brahim & Nakhli, Mohamed Sahbi & Sahut, Jean-Michel & Schweizer, Denis, 2023. "Interactions between investors’ fear and greed sentiment and Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    57. Sayed Mohammad Mousavi & Yazdan Shahin Rad, 2023. "Challenges and Legal Aspects of Financing Projects Through Cryptocurrencies in Iran," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 13(4), pages 127-151.
    58. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.
    59. Wang, Fang & Gacesa, Marko, 2023. "Semi-strong efficient market of Bitcoin and Twitter: An analysis of semantic vector spaces of extracted keywords and light gradient boosting machine models," International Review of Financial Analysis, Elsevier, vol. 88(C).
    60. Toan Luu Duc Huynh & Muhammad Shahbaz & Muhammad Ali Nasir & Subhan Ullah, 2022. "Financial modelling, risk management of energy instruments and the role of cryptocurrencies," Annals of Operations Research, Springer, vol. 313(1), pages 47-75, June.

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

    Cited by:

    1. Zhang, Xiaoyuan & Zhang, Tianqi, 2022. "Dynamic credit contagion and aggregate loss in networks," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    2. Alin Marius Andries & Steven Ongena & Nicu Sprincean & Radu Tunaru, 2020. "Risk Spillovers and Interconnectedness between Systemically Important Institutions," Swiss Finance Institute Research Paper Series 20-40, Swiss Finance Institute.
    3. Shaen Corbet & John W. Goodell & Samet Gunay & Kerem Kaskaloglu, 2023. "Are DeFi tokens a separate asset class from conventional cryptocurrencies?," Annals of Operations Research, Springer, vol. 322(2), pages 609-630, March.
    4. Mardi Dungey & Moses Kangogo & Vladimir Volkov, 2022. "Dynamic effects of network exposure on equity markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 569-629, December.
    5. Giudici, Paolo & Leach, Thomas & Pagnottoni, Paolo, 2022. "Libra or Librae? Basket based stablecoins to mitigate foreign exchange volatility spillovers," Finance Research Letters, Elsevier, vol. 44(C).
    6. Pagnottoni, Paolo & Spelta, Alessandro & Pecora, Nicolò & Flori, Andrea & Pammolli, Fabio, 2021. "Financial earthquakes: SARS-CoV-2 news shock propagation in stock and sovereign bond markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    7. Fulvia Pennoni & Francesco Bartolucci & Gianfranco Forte & Ferdinando Ametrano, 2022. "Exploring the dependencies among main cryptocurrency log‐returns: A hidden Markov model," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(1), February.
    8. Olli-Pekka Hilmola, 2021. "On Prices of Privacy Coins and Bitcoin," JRFM, MDPI, vol. 14(8), pages 1-15, August.
    9. Arianna Agosto & Alessia Cafferata, 2020. "Financial Bubbles: A Study of Co-Explosivity in the Cryptocurrency Market," Risks, MDPI, vol. 8(2), pages 1-14, April.
    10. Nikolaos A. Kyriazis, 2021. "Investigating the diversifying or hedging nexus of cannabis cryptocurrencies with major digital currencies," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 845-861, December.
    11. Costantini, Mauro & Maaitah, Ahmad & Mishra, Tapas & Sousa, Ricardo M., 2023. "Bitcoin market networks and cyberattacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    12. Tiago E. Pratas & Filipe R. Ramos & Lihki Rubio, 2023. "Forecasting bitcoin volatility: exploring the potential of deep learning," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 285-305, June.
    13. Ahmet Faruk Aysan & Asad Ul Islam Khan & Humeyra Topuz, 2021. "Bitcoin and Altcoins Price Dependency: Resilience and Portfolio Allocation in COVID-19 Outbreak," Risks, MDPI, vol. 9(4), pages 1-13, April.
    14. Abubakr Naeem, Muhammad & Iqbal, Najaf & Lucey, Brian M. & Karim, Sitara, 2022. "Good versus bad information transmission in the cryptocurrency market: Evidence from high-frequency data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    15. Danai Likitratcharoen & Nopadon Kronprasert & Karawan Wiwattanalamphong & Chakrin Pinmanee, 2021. "The Accuracy of Risk Measurement Models on Bitcoin Market during COVID-19 Pandemic," Risks, MDPI, vol. 9(12), pages 1-16, December.
    16. Kumar, Anoop S & Padakandla, Steven Raj, 2022. "Testing the safe-haven properties of gold and bitcoin in the backdrop of COVID-19: A wavelet quantile correlation approach," Finance Research Letters, Elsevier, vol. 47(PB).
    17. Efe Caglar Cagli & Pinar Evrim Mandaci, 2021. "Information transmission between bitcoin derivatives and spot markets: high-frequency causality analysis with Fourier approximation," Economics and Business Letters, Oviedo University Press, vol. 10(4), pages 394-402.
    18. Alex Plastun & Ludmila Khomutenko & Serhii Bashlai, 2022. "Is There Any Witching in the Cryptocurrency Market?," JRFM, MDPI, vol. 15(2), pages 1-14, February.
    19. Ying Chen & Paolo Giudici & Branka Hadji Misheva & Simon Trimborn, 2020. "Lead Behaviour in Bitcoin Markets," Risks, MDPI, vol. 8(1), pages 1-14, January.
    20. Pagnottoni, Paolo & Spelta, Alessandro & Flori, Andrea & Pammolli, Fabio, 2022. "Climate change and financial stability: Natural disaster impacts on global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    21. Nicoló Andrea Caserini & Paolo Pagnottoni, 2022. "Effective transfer entropy to measure information flows in credit markets," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 729-757, October.
    22. Vladimir Balash & Alexey Faizliev & Sergei Sidorov & Elena Chistopolskaya, 2021. "Conditional Time-Varying General Dynamic Factor Models and Its Application to the Measurement of Volatility Spillovers across Russian Assets," Mathematics, MDPI, vol. 9(19), pages 1-31, October.
    23. Choi, Hyungeun, 2021. "Investor attention and bitcoin liquidity: Evidence from bitcoin tweets," Finance Research Letters, Elsevier, vol. 39(C).
    24. Marina Resta & Paolo Pagnottoni & Maria Elena De Giuli, 2020. "Technical Analysis on the Bitcoin Market: Trading Opportunities or Investors’ Pitfall?," Risks, MDPI, vol. 8(2), pages 1-15, May.
    25. Agosto, Arianna & Cerchiello, Paola & Pagnottoni, Paolo, 2022. "Sentiment, Google queries and explosivity in the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    26. Pagnottoni, Paolo, 2023. "Superhighways and roads of multivariate time series shock transmission: Application to cryptocurrency, carbon emission and energy prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    27. Samet Gunay & Kerem Kaskaloglu & Shahnawaz Muhammed, 2021. "Bitcoin and Fiat Currency Interactions: Surprising Results from Asian Giants," Mathematics, MDPI, vol. 9(12), pages 1-18, June.

  26. 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.
  27. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, vol. 7(1), pages 1-25, January.

    Cited by:

    1. Borri, Nicola & Giorgio, Giorgio di, 2022. "Systemic risk and the COVID challenge in the european banking sector," Journal of Banking & Finance, Elsevier, vol. 140(C).
    2. Y'erali Gandica & Sophie B'ereau & Jean-Yves Gnabo, 2019. "A multilevel analysis to systemic exposure: insights from local and system-wide information," Papers 1910.08611, arXiv.org.

  28. 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.
  29. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.

    Cited by:

    1. Niklas Bussmann & Paolo Giudici & Dimitri Marinelli & Jochen Papenbrock, 2021. "Explainable Machine Learning in Credit Risk Management," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 203-216, January.
    2. 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.
    3. 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, vol. 12(5), pages 1-21, February.

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

    Cited by:

    1. Colin Ellis, 2020. "Are Corporate Bond Defaults Contagious across Sectors?," IJFS, MDPI, vol. 8(1), pages 1-17, January.
    2. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, vol. 7(1), pages 1-25, January.
    3. Chen, Yan & Mo, Dongxu & Xu, Zezhou, 2022. "A study of interconnections and contagion among Chinese financial institutions using a ΔCoV aR network," Finance Research Letters, Elsevier, vol. 45(C).
    4. Matteo Foglia & Eliana Angelini, 2019. "The Time-Spatial Dimension of Eurozone Banking Systemic Risk," Risks, MDPI, vol. 7(3), pages 1-25, July.
    5. Mehmet Ali Balcı & Larissa M. Batrancea & Ömer Akgüller, 2022. "Network-Induced Soft Sets and Stock Market Applications," Mathematics, MDPI, vol. 10(21), pages 1-24, October.
    6. Katerina Rigana & Ernst-Jan Camiel Wit & Samantha Cook, 2021. "Using Network-based Causal Inference to Detect the Sources of Contagion in the Currency Market," Papers 2112.13127, arXiv.org.
    7. Laleh Tafakori & Armin Pourkhanali & Riccardo Rastelli, 2022. "Measuring systemic risk and contagion in the European financial network," Empirical Economics, Springer, vol. 63(1), pages 345-389, July.
    8. Alin Marius Andries & Elena Galasan, 2020. "Measuring Financial Contagion and Spillover Effects with a State-Dependent Sensitivity Value-at-Risk Model," Risks, MDPI, vol. 8(1), pages 1-20, January.
    9. Foglia, Matteo & Addi, Abdelhamid & Wang, Gang-Jin & Angelini, Eliana, 2022. "Bearish Vs Bullish risk network: A Eurozone financial system analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    10. Nicoló Andrea Caserini & Paolo Pagnottoni, 2022. "Effective transfer entropy to measure information flows in credit markets," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 729-757, October.
    11. Yudistira Permana & Saiqa Akbar & Anisa Nurpita, 2022. "Systemic risk and the financial network system: an experimental investigation," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 631-651, December.
    12. 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.

  31. 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. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, vol. 6(3), pages 1-19, September.
    2. Yali Cao & Yue Shao & Hongxia Zhang, 2022. "Study on early warning of E-commerce enterprise financial risk based on deep learning algorithm," Electronic Commerce Research, Springer, vol. 22(1), pages 21-36, March.
    3. 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.
    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.
    5. Nicoló Andrea Caserini & Paolo Pagnottoni, 2022. "Effective transfer entropy to measure information flows in credit markets," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 729-757, October.
    6. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.
    7. Basse, Tobias, 2020. "Solvency II and sovereign credit risk: Additional empirical evidence and some thoughts about implications for regulators and lawmakers," International Review of Law and Economics, Elsevier, vol. 64(C).

  32. Silvia Figini & Paolo Giudici, 2017. "Credit risk assessment with Bayesian model averaging," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(19), pages 9507-9517, October.

    Cited by:

    1. Jeon, Bang Nam & Wu, Ji & Guo, Mengmeng & Chen, Minghua, 2018. "Market power and the risk-taking of banks: Some semiparametric evidence from emerging economies," School of Economics Working Paper Series 2018-1, LeBow College of Business, Drexel University.
    2. Paritosh Navinchandra Jha & Marco Cucculelli, 2021. "A New Model Averaging Approach in Predicting Credit Risk Default," Risks, MDPI, vol. 9(6), pages 1-15, June.

  33. 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.
  34. 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.
  35. 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.
  36. 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. 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. Athanasios Triantafyllou & George Dotsis & Alexandros Sarris, 2020. "Assessing the Vulnerability to Price Spikes in Agricultural Commodity Markets," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 631-651, September.
    3. 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.
    4. Veni Arakelian & Shatha Qamhieh Hashem, 2020. "The Leaders, the Laggers, and the “Vulnerables”," Risks, MDPI, vol. 8(1), pages 1-32, March.
    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.
    6. 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.
    7. Katleho Makatjane & Ntebogang Moroke, 2021. "Predicting Extreme Daily Regime Shifts in Financial Time Series Exchange/Johannesburg Stock Exchange—All Share Index," IJFS, MDPI, vol. 9(2), pages 1-18, March.
    8. 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.
    10. Paolo Giudici & Gloria Polinesi, 2021. "Crypto price discovery through correlation networks," Annals of Operations Research, Springer, vol. 299(1), pages 443-457, April.
    11. 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.
    12. 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.
    13. Yang Liu & Fei Huang & Lili Ma & Qingguo Zeng & Jiale Shi, 2024. "Credit scoring prediction leveraging interpretable ensemble learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 286-308, March.
    14. Dan Cheng & Pasquale Cirillo, 2019. "An Urn-Based Nonparametric Modeling of the Dependence between PD and LGD with an Application to Mortgages," Risks, MDPI, vol. 7(3), pages 1-21, July.
    15. Paolo Giudici & Emanuela Raffinetti, 2020. "Lorenz Model Selection," Journal of Classification, Springer;The Classification Society, vol. 37(3), pages 754-768, October.
    16. 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.
    17. Kočenda, Evžen & Iwasaki, Ichiro, 2021. "Bank Survival Around the World A Meta‐Analytic Review," CEI Working Paper Series 2021-02, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    18. Nicola, Giancarlo & Cerchiello, Paola & Aste, Tomaso, 2020. "Information network modeling for U.S. banking systemic risk," LSE Research Online Documents on Economics 107563, London School of Economics and Political Science, LSE Library.
    19. Paolo Giudici & Paolo Pagnottoni, 2019. "High Frequency Price Change Spillovers in Bitcoin Markets," Risks, MDPI, vol. 7(4), pages 1-18, November.
    20. 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.
    21. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.

  37. 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.

  38. 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. Donata Marasini & Piero Quatto, 2014. "A characterization of linear satisfaction measures," METRON, Springer;Sapienza Università di Roma, vol. 72(1), pages 17-23, April.
    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. 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, 2015. "A Bayesian h-index: how to measure research impact," DEM Working Papers Series 102, University of Pavia, Department of Economics and Management.
    6. Paola Cerchiello & Paolo Giudici, 2014. "On a statistical h index," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 299-312, May.

  39. 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.

    Cited by:

    1. Daniel Felix Ahelegbey & Paola Cerchiello & Roberta Scaramozzino, 2021. "Network Based Evidence of the Financial Impact of Covid-19 Pandemic," DEM Working Papers Series 198, University of Pavia, Department of Economics and Management.
    2. Agosto, Arianna & Cerchiello, Paola & Pagnottoni, Paolo, 2022. "Sentiment, Google queries and explosivity in the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).

  40. Giudici, P. & Raffinetti, E., 2011. "On the Gini measure decomposition," Statistics & Probability Letters, Elsevier, vol. 81(1), pages 133-139, January.

    Cited by:

    1. Paolo Giudici & Emanuela Raffinetti, 2020. "Lorenz Model Selection," Journal of Classification, Springer;The Classification Society, vol. 37(3), pages 754-768, October.
    2. Paolo Giudici & Emanuela Raffinetti, 2021. "Cyber risk ordering with rank-based statistical models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(3), pages 469-484, September.

  41. S Figini & P Giudici, 2011. "Statistical merging of rating models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1067-1074, June.

    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. Silvia Figini & Roberto Savona & Marika Vezzoli, 2016. "Corporate Default Prediction Model Averaging: A Normative Linear Pooling Approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(1-2), pages 6-20, January.
    3. 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.
    4. Andreeva, Galina & Calabrese, Raffaella & Osmetti, Silvia Angela, 2016. "A comparative analysis of the UK and Italian small businesses using Generalised Extreme Value models," European Journal of Operational Research, Elsevier, vol. 249(2), pages 506-516.
    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.
    6. Carmen Gallucci & Rosalia Santullli & Michele Modina & Vincenzo Formisano, 2023. "Financial ratios, corporate governance and bank-firm information: a Bayesian approach to predict SMEs’ default," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 27(3), pages 873-892, September.
    7. Silvia Figini & Lijun Gao & Paolo Giudici, 2013. "Bayesian operational risk models," DEM Working Papers Series 047, University of Pavia, Department of Economics and Management.
    8. Yu Zhao & Huaming Du & Qing Li & Fuzhen Zhuang & Ji Liu & Gang Kou, 2022. "A Comprehensive Survey on Enterprise Financial Risk Analysis from Big Data Perspective," Papers 2211.14997, arXiv.org, revised May 2023.
    9. 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.
    10. Zhu, You & Zhou, Li & Xie, Chi & Wang, Gang-Jin & Nguyen, Truong V., 2019. "Forecasting SMEs' credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach," International Journal of Production Economics, Elsevier, vol. 211(C), pages 22-33.
    11. Paolo Giudici & Gloria Polinesi, 2021. "Crypto price discovery through correlation networks," Annals of Operations Research, Springer, vol. 299(1), pages 443-457, April.
    12. Dan Cheng & Pasquale Cirillo, 2019. "An Urn-Based Nonparametric Modeling of the Dependence between PD and LGD with an Application to Mortgages," Risks, MDPI, vol. 7(3), pages 1-21, July.
    13. Paolo Giudici & Emanuela Raffinetti, 2020. "Lorenz Model Selection," Journal of Classification, Springer;The Classification Society, vol. 37(3), pages 754-768, October.
    14. Zanin, Luca, 2020. "Combining multiple probability predictions in the presence of class imbalance to discriminate between potential bad and good borrowers in the peer-to-peer lending market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    15. Paolo Giudici & Paolo Pagnottoni, 2019. "High Frequency Price Change Spillovers in Bitcoin Markets," Risks, MDPI, vol. 7(4), pages 1-18, November.
    16. Francesco Ciampi & Alessandro Giannozzi & Giacomo Marzi & Edward I. Altman, 2021. "Rethinking SME default prediction: a systematic literature review and future perspectives," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2141-2188, March.

  42. 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. 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.
    2. 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.
    3. 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.

  43. Danae Politou & Paolo Giudici, 2009. "Modelling Operational Risk Losses with Graphical Models and Copula Functions," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 65-93, March.

    Cited by:

    1. Silvia Figini & Lijun Gao & Paolo Giudici, 2013. "Bayesian operational risk models," DEM Working Papers Series 047, University of Pavia, Department of Economics and Management.
    2. 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.
    3. Denuit, Michel & Robert, Christian Y., 2020. "Conditional mean risk sharing for dependent risks using graphical models," LIDAM Discussion Papers ISBA 2020029, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  44. 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. 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).
    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. Facchinetti, Silvia & Osmetti, Silvia Angela & Tarantola, Claudia, 2023. "Network models for cyber attacks evaluation," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    12. 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.
    13. Paola Cerchiello & Paolo Giudici, 2013. "H Index: A Statistical Proposal," DEM Working Papers Series 039, University of Pavia, Department of Economics and Management.
    14. 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. 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.
    16. 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.
    17. Paola Cerchiello & Paolo Giudici, 2014. "On a statistical h index," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 299-312, May.
    18. 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.

  45. 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.
    4. Katrina M Groth & Ali Mosleh, 2012. "Deriving causal Bayesian networks from human reliability analysis data: A methodology and example model," Journal of Risk and Reliability, , vol. 226(4), pages 361-379, August.

  46. 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. 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. 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.
    4. Bojaj, Martin M. & Muhadinovic, Milica & Bracanovic, Andrej & Mihailovic, Andrej & Radulovic, Mladen & Jolicic, Ivan & Milosevic, Igor & Milacic, Veselin, 2022. "Forecasting macroeconomic effects of stablecoin adoption: A Bayesian approach," Economic Modelling, Elsevier, vol. 109(C).
    5. Marco Bardoscia & Roberto Bellotti, 2012. "A Dynamical Approach to Operational Risk Measurement," Papers 1202.2532, arXiv.org.
    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. Paola Cerchiello & Paolo Giudici, 2013. "Bayesian Credit Ratings (new version)," DEM Working Papers Series 030, University of Pavia, Department of Economics and Management.
    9. Paola Cerchiello & Paolo Giudici, 2012. "Bayesian Credit Rating Assessment," DEM Working Papers Series 019, University of Pavia, Department of Economics and Management.
    10. 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.
    11. 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.
    12. Danae Politou & Paolo Giudici, 2009. "Modelling Operational Risk Losses with Graphical Models and Copula Functions," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 65-93, March.
    13. 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.
    14. 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.

  47. 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. 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.
    2. Daniel Felix Ahelegbey & Paolo Giudici, 2014. "Hierarchical Graphical Models, With Application To Systemic Risk," DEM Working Papers Series 063, University of Pavia, Department of Economics and Management.
    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. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Bayesian Graphical Models for STructural Vector Autoregressive Processes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 357-386, March.
    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.
    6. 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".
    7. Webb, Emily L. & Forster, Jonathan J., 2008. "Bayesian model determination for multivariate ordinal and binary data," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2632-2649, January.

  48. 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. Griffin, J.E. & Steel, M.F.J., 2010. "Bayesian inference with stochastic volatility models using continuous superpositions of non-Gaussian Ornstein-Uhlenbeck processes," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2594-2608, November.
    2. McVinish, R. & Mengersen, K., 2008. "Semiparametric Bayesian circular statistics," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4722-4730, June.
    3. 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.
    4. 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.
    5. Sridhar Narayanan, 2013. "Bayesian estimation of discrete games of complete information," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 39-81, March.
    6. 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.
    7. 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).
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. Sridhar Narayanan, 2013. "Bayesian estimation of discrete games of complete information," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 39-81, March.
    21. 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.
    22. 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).
    23. Yinghan Chen & Steven Andrew Culpepper & Yuguo Chen, 2023. "Bayesian Inference for an Unknown Number of Attributes in Restricted Latent Class Models," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 613-635, June.
    24. Riccardo (Jack) Lucchetti & Luca Pedini, 2020. "ParMA: Parallelised Bayesian Model Averaging for Generalised Linear Models," Working Papers 2020:28, Department of Economics, University of Venice "Ca' Foscari".
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. McGrory, C.A. & Pettitt, A.N. & Faddy, M.J., 2009. "A fully Bayesian approach to inference for Coxian phase-type distributions with covariate dependent mean," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4311-4321, October.
    31. Ronald W. Butler & Marc S. Paolella, 2017. "Autoregressive Lag—Order Selection Using Conditional Saddlepoint Approximations," Econometrics, MDPI, vol. 5(3), pages 1-33, September.
    32. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.
    33. 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.

  49. 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. Stephan Brosig & Miroslava Bavorova, 2019. "Association of attitudes towards genetically modified food among young adults and their referent persons," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-19, February.
    2. 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.

  50. 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. Ahelegbey, Daniel & Giudici, Paolo & Pediroda, Valentino, 2023. "A network based fintech inclusion platform," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    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.
    3. Paolo Giudici & Gloria Polinesi, 2021. "Crypto price discovery through correlation networks," Annals of Operations Research, Springer, vol. 299(1), pages 443-457, April.
    4. Dan Cheng & Pasquale Cirillo, 2019. "An Urn-Based Nonparametric Modeling of the Dependence between PD and LGD with an Application to Mortgages," Risks, MDPI, vol. 7(3), pages 1-21, July.
    5. 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, vol. 11(3), pages 1-23, January.
    6. Paola Cerchiello & Paolo Giudici, 2013. "Bayesian Credit Ratings (new version)," DEM Working Papers Series 030, University of Pavia, Department of Economics and Management.
    7. Paola Cerchiello & Paolo Giudici, 2012. "Bayesian Credit Rating Assessment," DEM Working Papers Series 019, University of Pavia, Department of Economics and Management.

  51. 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.
    2. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.

  52. 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. Dannemann, Jorn & Holzmann, Hajo, 2008. "The likelihood ratio test for hidden Markov models in two-sample problems," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1850-1859, January.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Tim Sainburg & Marvin Thielk & Timothy Q Gentner, 2020. "Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires," PLOS Computational Biology, Public Library of Science, vol. 16(10), pages 1-48, October.
    7. 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.

  53. 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: Bayesian Model Comparison, volume 34, pages 117-153, Emerald Group Publishing Limited.

    Cited by:

    1. Agosto, Arianna & Ahelegbey, Daniel Felix & Giudici, Paolo, 2020. "Tree Networks to assess Financial Contagion," MPRA Paper 107066, University Library of Munich, Germany.
    2. Daniel Felix Ahelegbey & Emmanuel Senyo Fianu & Luigi Grossi, 2020. "Modeling Risk Contagion in the Italian Zonal Electricity Market," DEM Working Papers Series 182, University of Pavia, Department of Economics and Management.
    3. 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.
    4. Daniel Felix Ahelegbey, 2015. "The Econometrics of Networks: A Review," Working Papers 2015:13, Department of Economics, University of Venice "Ca' Foscari".
    5. 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".

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