IDEAS home Printed from https://ideas.repec.org/f/pag213.html
   My authors  Follow this author

Arianna Agosto

Personal Details

First Name:Arianna
Middle Name:
Last Name:Agosto
Suffix:
RePEc Short-ID:pag213
[This author has chosen not to make the email address public]

Affiliation

Dipartimento di Scienze Economiche e Aziendali
Università degli Studi di Pavia

Pavia, Italy
https://economiaemanagement.dip.unipv.it/
RePEc:edi:dppavit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Arianna Agosto & Daniel Felix Ahelegbey, 2020. "Default count-based network models for credit contagion," DEM Working Papers Series 180, University of Pavia, Department of Economics and Management.
  2. Agosto, Arianna & Ahelegbey, Daniel Felix & Giudici, Paolo, 2020. "Tree Networks to assess Financial Contagion," MPRA Paper 107066, University Library of Munich, Germany.
  3. Arianna Agosto & Paolo Giudici & Emanuela Raffinetti, 2020. "A rank graduation accuracy measure," DEM Working Papers Series 179, University of Pavia, Department of Economics and Management.
  4. 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.
  5. Arianna Agosto & Alessandra Mainini & Enrico Moretto, 2016. "Covariance of random stock prices in the Stochastic Dividend Discount Model," Papers 1609.03029, arXiv.org, revised Apr 2017.
  6. Arianna Agosto & Giuseppe Cavaliere & Dennis Kristensen & Anders Rahbek, 2015. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," CREATES Research Papers 2015-11, Department of Economics and Business Economics, Aarhus University.
  7. Arianna Agosto & Enrico Moretto, 2013. "Variance matters (in stochastic dividend discount models)," Papers 1311.0236, arXiv.org.
  8. Arianna Agosto & Enrico Moretto, 2010. "Applying default probabilities in an exponential barrier structural model," Economics and Quantitative Methods qf1005, Department of Economics, University of Insubria.

Articles

  1. 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.
  2. Arianna Agosto & Paolo Giudici, 2020. "COVID-19 contagion and digital finance," Digital Finance, Springer, vol. 2(1), pages 159-167, September.
  3. Arianna Agosto & Paolo Giudici, 2020. "A Poisson Autoregressive Model to Understand COVID-19 Contagion Dynamics," Risks, MDPI, vol. 8(3), pages 1-8, July.
  4. 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.
  5. Agosto, Arianna & Ahelegbey, Daniel Felix & Giudici, Paolo, 2020. "Tree networks to assess financial contagion," Economic Modelling, Elsevier, vol. 85(C), pages 349-366.
  6. Arianna Agosto & Alessandra Mainini & Enrico Moretto, 2019. "Stochastic dividend discount model: covariance of random stock prices," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(3), pages 552-568, July.
  7. Agosto, Arianna & Cavaliere, Giuseppe & Kristensen, Dennis & Rahbek, Anders, 2016. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 640-663.
  8. Arianna Agosto & Enrico Moretto, 2015. "Variance matters (in stochastic dividend discount models)," Annals of Finance, Springer, vol. 11(2), pages 283-295, May.

    RePEc:taf:apfiec:v:22:y:2012:i:8:p:667-679 is not listed on IDEAS

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

RePEc Biblio mentions

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

    Mentioned in:

    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19
    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. Arianna Agosto & Daniel Felix Ahelegbey, 2020. "Default count-based network models for credit contagion," DEM Working Papers Series 180, University of Pavia, Department of Economics and Management.

    Cited by:

    1. Zhang, Xiaoyu & Xu, Maochao & Su, Jianxi & Zhao, Peng, 2023. "Structural models for fog computing based internet of things architectures with insurance and risk management applications," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1273-1291.
    2. Joanna Wieprow & Agnieszka Gawlik, 2021. "The Use of Discriminant Analysis to Assess the Risk of Bankruptcy of Enterprises in Crisis Conditions Using the Example of the Tourism Sector in Poland," Risks, MDPI, vol. 9(4), pages 1-11, April.

  2. 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. Cécile Bastidon & Fredj Jawadi, 2024. "Trade fragmentation and volatility-of-volatility networks," Post-Print hal-04478721, HAL.
    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. 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.
    5. Okorie, David Iheke & Lin, Boqiang, 2021. "Stock markets and the COVID-19 fractal contagion effects," Finance Research Letters, Elsevier, vol. 38(C).
    6. 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.
    7. 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," Economic Modelling, Elsevier, vol. 109(C).
    8. Tian, Sihua & Li, Shaofang & Gu, Qinen, 2023. "Measurement and contagion modelling of systemic risk in China's financial sectors: Evidence for functional data analysis and complex network," International Review of Financial Analysis, Elsevier, vol. 90(C).
    9. Rigana, Katerina & Wit, Ernst-Jan Camiel & Cook, Samantha, 2023. "A new way of measuring effects of financial crisis on contagion in currency markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    10. 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.
    11. 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).
    12. 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.
    13. 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).
    14. 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).
    15. 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).

  3. 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. Stefano Cabras, 2021. "A Bayesian-Deep Learning Model for Estimating COVID-19 Evolution in Spain," Mathematics, MDPI, vol. 9(22), pages 1-18, November.
    2. Otilia Boldea & Adriana Cornea-Madeira & João Madeira, 2023. "Disentangling the effect of measures, variants, and vaccines on SARS-CoV-2 infections in England: a dynamic intensity model," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 444-466.
    3. Guglielmo Maria Caporale & Woo-Young Kang & Fabio Spagnolo & Nicola Spagnolo, 2022. "The COVID-19 pandemic, policy responses and stock markets in the G20," International Economics, CEPII research center, issue 172, pages 77-90.
    4. 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.
    5. 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.
    6. 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.

  4. Arianna Agosto & Giuseppe Cavaliere & Dennis Kristensen & Anders Rahbek, 2015. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," CREATES Research Papers 2015-11, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. 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.
    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. Weiß, Christian H. & Zhu, Fukang, 2024. "Conditional-mean multiplicative operator models for count time series," Computational Statistics & Data Analysis, Elsevier, vol. 191(C).
    4. Yang, Kai & Yu, Xinyang & Zhang, Qingqing & Dong, Xiaogang, 2022. "On MCMC sampling in self-exciting integer-valued threshold time series models," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    5. Rasmus Soendergaard Pedersen & Anders Rahbek, 2017. "Testing Garch-X Type Models," Discussion Papers 17-15, University of Copenhagen. Department of Economics.
    6. Cavaliere, Giuseppe & Nielsen, Heino Bohn & Pedersen, Rasmus Søndergaard & Rahbek, Anders, 2022. "Bootstrap inference on the boundary of the parameter space, with application to conditional volatility models," Journal of Econometrics, Elsevier, vol. 227(1), pages 241-263.
    7. Mengya Liu & Qi Li & Fukang Zhu, 2020. "Self-excited hysteretic negative binomial autoregression," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 385-415, September.
    8. Escribano, Ana & Maggi, Mario, 2019. "Intersectoral default contagion: A multivariate Poisson autoregression analysis," Economic Modelling, Elsevier, vol. 82(C), pages 376-400.
    9. Huaping Chen, 2023. "A New Soft-Clipping Discrete Beta GARCH Model and Its Application on Measles Infection," Stats, MDPI, vol. 6(1), pages 1-19, February.
    10. Maia, Gisele de Oliveira & Barreto-Souza, Wagner & Bastos, Fernando de Souza & Ombao, Hernando, 2021. "Semiparametric time series models driven by latent factor," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1463-1479.
    11. 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.
    12. Cavaliere, Giuseppe & Lu, Ye & Rahbek, Anders & Stærk-Østergaard, Jacob, 2023. "Bootstrap inference for Hawkes and general point processes," Journal of Econometrics, Elsevier, vol. 235(1), pages 133-165.
    13. Arianna Agosto & Paolo Giudici, 2020. "COVID-19 contagion and digital finance," Digital Finance, Springer, vol. 2(1), pages 159-167, September.
    14. Huaping Chen & Qi Li & Fukang Zhu, 2023. "A covariate-driven beta-binomial integer-valued GARCH model for bounded counts with an application," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(7), pages 805-826, October.
    15. Giuseppe Cavaliere & Indeewara Perera & Anders Rahbek, 2021. "Specification tests for GARCH processes," Papers 2105.14081, arXiv.org.
    16. Aknouche, Abdelhakim & Francq, Christian, 2018. "Count and duration time series with equal conditional stochastic and mean orders," MPRA Paper 90838, University Library of Munich, Germany.
    17. Rémy Garnier, 2022. "Concurrent neural network: a model of competition between times series," Annals of Operations Research, Springer, vol. 313(2), pages 945-964, June.
    18. Geir D. Berentsen & Jan Bulla & Antonello Maruotti & Bård Støve, 2022. "Modelling clusters of corporate defaults: Regime‐switching models significantly reduce the contagion source," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 698-722, June.
    19. Huaping Chen & Qi Li & Fukang Zhu, 2022. "A new class of integer-valued GARCH models for time series of bounded counts with extra-binomial variation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 243-270, June.
    20. Giovanni Angelini & Giuseppe Cavaliere & Enzo D'Innocenzo & Luca De Angelis, 2022. "Time-Varying Poisson Autoregression," Papers 2207.11003, arXiv.org.
    21. Giovanni Angelini & Luca De Angelis, 2017. "PARX model for football match predictions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(7), pages 795-807, November.
    22. Dennis Kristensen & Young Jun Lee, 2019. "Local Polynomial Estimation of Time-Varying Parameters in Nonlinear Models," Papers 1904.05209, arXiv.org, revised Aug 2023.
    23. Randal Douc & François Roueff & Tepmony Sim, 2021. "Necessary and sufficient conditions for the identifiability of observation‐driven models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(2), pages 140-160, March.
    24. Wang, Xiaoting & Hou, Siyuan & Shen, Jie, 2021. "Default clustering of the nonfinancial sector and systemic risk: Evidence from China," Economic Modelling, Elsevier, vol. 96(C), pages 196-208.
    25. Gagliardini, Patrick & Gouriéroux, Christian, 2019. "Identification by Laplace transforms in nonlinear time series and panel models with unobserved stochastic dynamic effects," Journal of Econometrics, Elsevier, vol. 208(2), pages 613-637.
    26. Truquet, Lionel, 2023. "Strong mixing properties of discrete-valued time series with exogenous covariates," Stochastic Processes and their Applications, Elsevier, vol. 160(C), pages 294-317.
    27. Christis Katsouris, 2024. "Robust Estimation in Network Vector Autoregression with Nonstationary Regressors," Papers 2401.04050, arXiv.org.
    28. Gorgi, P. & Koopman, S.J., 2023. "Beta observation-driven models with exogenous regressors: A joint analysis of realized correlation and leverage effects," Journal of Econometrics, Elsevier, vol. 237(2).
    29. Lu, Ye & Suthaharan, Neyavan, 2023. "Electricity price spike clustering: A zero-inflated GARX approach," Energy Economics, Elsevier, vol. 124(C).

  5. Arianna Agosto & Enrico Moretto, 2013. "Variance matters (in stochastic dividend discount models)," Papers 1311.0236, arXiv.org.

    Cited by:

    1. Guglielmo D'Amico, 2016. "Generalized semi-Markovian dividend discount model: risk and return," Papers 1605.02472, arXiv.org.
    2. Aziz Issaka & Indranil SenGupta, 2017. "Analysis of variance based instruments for Ornstein–Uhlenbeck type models: swap and price index," Annals of Finance, Springer, vol. 13(4), pages 401-434, November.
    3. Vlad Stefan Barbu & Guglielmo D’Amico & Riccardo Blasis, 2017. "Novel advancements in the Markov chain stock model: analysis and inference," Annals of Finance, Springer, vol. 13(2), pages 125-152, May.
    4. Guglielmo D'Amico & Riccardo De Blasis, 2020. "A review of the Dividend Discount Model: from deterministic to stochastic models," Papers 2001.00465, arXiv.org.
    5. D'Amico, Guglielmo & De Blasis, Riccardo, 2024. "Dividend based risk measures: A Markov chain approach," Applied Mathematics and Computation, Elsevier, vol. 471(C).
    6. Guglielmo D’Amico & Ada Lika & Filippo Petroni, 2019. "Change point dynamics for financial data: an indexed Markov chain approach," Annals of Finance, Springer, vol. 15(2), pages 247-266, June.
    7. Arianna Agosto & Alessandra Mainini & Enrico Moretto, 2019. "Stochastic dividend discount model: covariance of random stock prices," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(3), pages 552-568, July.
    8. Arianna Agosto & Alessandra Mainini & Enrico Moretto, 2016. "Covariance of random stock prices in the Stochastic Dividend Discount Model," Papers 1609.03029, arXiv.org, revised Apr 2017.
    9. Battulga Gankhuu, 2022. "Augmented Dynamic Gordon Growth Model," Papers 2201.06012, arXiv.org, revised Sep 2024.

Articles

  1. 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. 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.
    2. 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. 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.

  3. 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.
  4. 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.

    Cited by:

    1. Ahelegbey, Daniel Felix & Giudici, Paolo & Mojtahedi, Fatemeh, 2021. "Tail risk measurement in crypto-asset markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    2. 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.
    3. David Robles Ortiz & Luz Dary Beltrán Jaimes & María del Carmen Delgado López, 2022. "Impacto económico y social de la formalización laboral en México," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 41(86), pages 185-212, May.
    4. Marco Bellucci & Damiano Cesa Bianchi & Giacomo Manetti, 2021. "A literature review on blockchain in accounting research," Working Papers - Business wp2021_04.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    5. 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.
    6. Zhang, Pengcheng & Kong, Deli & Xu, Kunpeng & Qi, Jiayin, 2024. "Global economic policy uncertainty and the stability of cryptocurrency returns: The role of liquidity volatility," Research in International Business and Finance, Elsevier, vol. 67(PB).
    7. 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.
    8. Ramit Sawhney & Shivam Agarwal & Vivek Mittal & Paolo Rosso & Vikram Nanda & Sudheer Chava, 2022. "Cryptocurrency Bubble Detection: A New Stock Market Dataset, Financial Task & Hyperbolic Models," Papers 2206.06320, arXiv.org.
    9. 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.
    10. 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).
    11. Michael Demmler & Amilcar Orlian Fernández Domínguez, 2022. "Speculative bubble tendencies in time series of Bitcoin market prices," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 41(86), pages 159-183, May.
    12. Michael Demmler & Amilcar Orlian Fernández Domínguez, 2021. "Bitcoin and the South Sea Company: A comparative analysis," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 13(1), pages 197-224, March.
    13. Danai Likitratcharoen & Pan Chudasring & Chakrin Pinmanee & Karawan Wiwattanalamphong, 2023. "The Efficiency of Value-at-Risk Models during Extreme Market Stress in Cryptocurrencies," Sustainability, MDPI, vol. 15(5), pages 1-21, March.
    14. 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.
    15. 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).
    16. Kavya Clanganthuruthil Sajeev & Mohd Afjal, 2022. "Contagion effect of cryptocurrency on the securities market: a study of Bitcoin volatility using diagonal BEKK and DCC GARCH models," SN Business & Economics, Springer, vol. 2(6), pages 1-21, June.
    17. 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.
    18. 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.
    19. Pawan Kumar Singh & Alok Kumar Pandey & S. C. Bose, 2023. "A new grey system approach to forecast closing price of Bitcoin, Bionic, Cardano, Dogecoin, Ethereum, XRP Cryptocurrencies," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2429-2446, June.
    20. Şoiman, Florentina & Dumas, Jean-Guillaume & Jimenez-Garces, Sonia, 2023. "What drives DeFi market returns?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    21. Cevik, Emrah Ismail & Gunay, Samet & Dibooglu, Sel & Yıldırım, Durmuş Çağrı, 2023. "The impact of expected and unexpected events on Bitcoin price development: Introduction of futures market and COVID-19," Finance Research Letters, Elsevier, vol. 54(C).
    22. Gian Luca Vriz & Luigi Grossi, 2024. "Green bubbles: a four-stage paradigm for detection and propagation," Papers 2410.06564, arXiv.org.
    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. Florentina c{S}oiman & Guillaume Dumas & Sonia Jimenez-Garces, 2022. "The return of (I)DeFiX," Papers 2204.00251, arXiv.org.
    25. Dora Almeida & Andreia Dionísio & Isabel Vieira & Paulo Ferreira, 2022. "Uncertainty and Risk in the Cryptocurrency Market," JRFM, MDPI, vol. 15(11), pages 1-17, November.
    26. Filip-Mihai Toma & Cosmin-Octavian Cepoi & Matei Nicolae Kubinschi & Makoto Miyakoshi, 2023. "Gazing through the bubble: an experimental investigation into financial risk-taking using eye-tracking," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.

  5. 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.
  6. Arianna Agosto & Alessandra Mainini & Enrico Moretto, 2019. "Stochastic dividend discount model: covariance of random stock prices," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(3), pages 552-568, July.

    Cited by:

    1. Battulga Gankhuu, 2023. "Parameter Estimation Methods of Required Rate of Return," Papers 2305.19708, arXiv.org, revised Aug 2023.
    2. Guglielmo D'Amico & Riccardo De Blasis, 2020. "A review of the Dividend Discount Model: from deterministic to stochastic models," Papers 2001.00465, arXiv.org.
    3. D'Amico, Guglielmo & De Blasis, Riccardo, 2024. "Dividend based risk measures: A Markov chain approach," Applied Mathematics and Computation, Elsevier, vol. 471(C).

  7. Agosto, Arianna & Cavaliere, Giuseppe & Kristensen, Dennis & Rahbek, Anders, 2016. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 640-663.
    See citations under working paper version above.
  8. Arianna Agosto & Enrico Moretto, 2015. "Variance matters (in stochastic dividend discount models)," Annals of Finance, Springer, vol. 11(2), pages 283-295, May.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 7 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-CFN: Corporate Finance (2) 2020-12-21 2021-04-19
  2. NEP-NET: Network Economics (2) 2020-12-21 2021-04-19
  3. NEP-ORE: Operations Research (2) 2020-12-21 2020-12-21
  4. NEP-CNA: China (1) 2020-04-06
  5. NEP-ECM: Econometrics (1) 2015-02-22
  6. NEP-EEC: European Economics (1) 2021-04-19
  7. NEP-ETS: Econometric Time Series (1) 2020-04-06
  8. NEP-FDG: Financial Development and Growth (1) 2020-12-21
  9. NEP-MAC: Macroeconomics (1) 2021-04-19
  10. NEP-RMG: Risk Management (1) 2010-06-26
  11. NEP-SOG: Sociology of Economics (1) 2016-09-18

Corrections

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

To update listings or check citations waiting for approval, Arianna Agosto should log into the RePEc Author Service.

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

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

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

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