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Luca De Angelis

Citations

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

Working papers

  1. Luca De Angelis & J. James Reade, 2022. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Economics Discussion Papers em-dp2022-01, Department of Economics, University of Reading.

    Cited by:

    1. Carl Singleton & Alex Bryson & Peter Dolton & James Reade & Dominik Schreyer, 2022. "Economics lessons from sports during the COVID-19 pandemic," Chapters, in: Paul M. Pedersen (ed.), Research Handbook on Sport and COVID-19, chapter 2, pages 9-18, Edward Elgar Publishing.

  2. Giovanni Angelini & Luca De Angelis & Carl Singleton, 2019. "Informational efficiency and behaviour within in-play prediction markets," Economics Discussion Papers em-dp2019-20, Department of Economics, University of Reading, revised 01 Apr 2021.

    Cited by:

    1. S. E. Hill, 2022. "In-game win probability models for Canadian football," Journal of Business Analytics, Taylor & Francis Journals, vol. 5(2), pages 164-178, July.
    2. He, Xue-Zhong & Treich, Nicolas, 2017. "Prediction market prices under risk aversion and heterogeneous beliefs," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 105-114.
    3. Tim Pawlowski & Dooruj Rambaccussing & Philip Ramirez & James & Giambattista Rossi, 2023. "Exploring Entertainment Utility from Football Games," Economics Discussion Papers em-dp2023-13, Department of Economics, University of Reading.
    4. Travis Richardson & Georgios Nalbantis & Tim Pawlowski, 2023. "Emotional Cues and the Demand for Televised Sports: Evidence from the UEFA Champions League," Journal of Sports Economics, , vol. 24(8), pages 993-1025, December.
    5. Goto, Shingo & Yamada, Toru, 2023. "What drives biased odds in sports betting markets: Bettors’ irrationality and the role of bookmakers," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 252-270.
    6. Raphael Flepp & Oliver Merz & Egon Franck, 2024. "When the league table lies: Does outcome bias lead to informationally inefficient markets?," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 414-429, January.
    7. J Reade & C Singleton & L Vaughan Williams, 2020. "Betting Markets for English Premier League Results and Scorelines: Evaluating a Simple Forecasting Model," Economic Issues Journal Articles, Economic Issues, vol. 25(1), pages 87-106, March.
    8. Luca De Angelis & J. James Reade, 2022. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Economics Discussion Papers em-dp2022-01, Department of Economics, University of Reading.
    9. Fischer, Kai & Haucap, Justus, 2020. "Betting market efficiency in the presence of unfamiliar shocks: The case of ghost games during the COVID-19 pandemic," DICE Discussion Papers 349, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    10. Ramirez, Philip & Reade, J. James & Singleton, Carl, 2023. "Betting on a buzz: Mispricing and inefficiency in online sportsbooks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1413-1423.
    11. Ruud H. Koning & Renske Zijm, 2023. "Betting market efficiency and prediction in binary choice models," Annals of Operations Research, Springer, vol. 325(1), pages 135-148, June.
    12. Aitazaz Ali Raja & Pierre Pinson & Jalal Kazempour & Sergio Grammatico, 2022. "A Market for Trading Forecasts: A Wagering Mechanism," Papers 2205.02668, arXiv.org, revised Oct 2022.
    13. Kai Fischer & Justus Haucap, 2022. "Home advantage in professional soccer and betting market efficiency: The role of spectator crowds," Kyklos, Wiley Blackwell, vol. 75(2), pages 294-316, May.
    14. Marius Otting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Papers 2211.06052, arXiv.org.
    15. Luca De Angelis & J. James Reade, 2023. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Annals of Operations Research, Springer, vol. 325(1), pages 391-418, June.
    16. Carl Singleton & Alex Bryson & Peter Dolton & James Reade & Dominik Schreyer, 2022. "Economics lessons from sports during the COVID-19 pandemic," Chapters, in: Paul M. Pedersen (ed.), Research Handbook on Sport and COVID-19, chapter 2, pages 9-18, Edward Elgar Publishing.
    17. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2023. "Gambling on Momentum in Contests," Economics Discussion Papers em-dp2023-08, Department of Economics, University of Reading.

  3. Giovanni Angelini & Luca De Angelis, 2016. "PARX model for football matches predictions," Quaderni di Dipartimento 2, Department of Statistics, University of Bologna.

    Cited by:

    1. Raffaele Mattera, 2023. "Forecasting binary outcomes in soccer," Annals of Operations Research, Springer, vol. 325(1), pages 115-134, June.
    2. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos & Verousis, Thanos, 2020. "A conditional fuzzy inference approach in forecasting," European Journal of Operational Research, Elsevier, vol. 283(1), pages 196-216.
    3. David Winkelmann & Marius Ötting & Christian Deutscher & Tomasz Makarewicz, 2024. "Are Betting Markets Inefficient? Evidence From Simulations and Real Data," Journal of Sports Economics, , vol. 25(1), pages 54-97, January.
    4. Alberto Arcagni & Vincenzo Candila & Rosanna Grassi, 2023. "A new model for predicting the winner in tennis based on the eigenvector centrality," Annals of Operations Research, Springer, vol. 325(1), pages 615-632, June.
    5. da Costa, Igor Barbosa & Marinho, Leandro Balby & Pires, Carlos Eduardo Santos, 2022. "Forecasting football results and exploiting betting markets: The case of “both teams to score”," International Journal of Forecasting, Elsevier, vol. 38(3), pages 895-909.
    6. Lu, Ye & Suthaharan, Neyavan, 2023. "Electricity price spike clustering: A zero-inflated GARX approach," Energy Economics, Elsevier, vol. 124(C).
    7. Andrei Shynkevich, 2022. "Informational efficiency of football transfer market," Economics Bulletin, AccessEcon, vol. 42(2), pages 1032-1039.
    8. Giovanni Angelini & Giuseppe Cavaliere & Enzo D'Innocenzo & Luca De Angelis, 2022. "Time-Varying Poisson Autoregression," Papers 2207.11003, arXiv.org.
    9. Angelini, Giovanni & De Angelis, Luca, 2019. "Efficiency of online football betting markets," International Journal of Forecasting, Elsevier, vol. 35(2), pages 712-721.
    10. Koopman, Siem Jan & Lit, Rutger, 2019. "Forecasting football match results in national league competitions using score-driven time series models," International Journal of Forecasting, Elsevier, vol. 35(2), pages 797-809.
    11. Angelini, Giovanni & Candila, Vincenzo & De Angelis, Luca, 2022. "Weighted Elo rating for tennis match predictions," European Journal of Operational Research, Elsevier, vol. 297(1), pages 120-132.

  4. Giuseppe Cavaliere & Luca De Angelis & Luca Fanelli, 2016. "Co-integration rank determination in partial systems using information criteria," Quaderni di Dipartimento 4, Department of Statistics, University of Bologna.

    Cited by:

    1. Takamitsu Kurita & Bent Nielsen, 2019. "Partial Cointegrated Vector Autoregressive Models with Structural Breaks in Deterministic Terms," Econometrics, MDPI, vol. 7(4), pages 1-35, October.

  5. Cavaliere, G & De Angelis, L & Rahbek, A & Taylor, AMR, 2016. "Determining the Cointegration Rank in Heteroskedastic VAR Models of Unknown Order," Essex Finance Centre Working Papers 17454, University of Essex, Essex Business School.

    Cited by:

    1. Motegi, Kaiji & Iitsuka, Yoshitaka, 2023. "Inter-regional dependence of J-REIT stock prices: A heteroscedasticity-robust time series approach," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    2. Gianluca Cubadda & Marco Mazzali, 2024. "The vector error correction index model: representation, estimation and identification," The Econometrics Journal, Royal Economic Society, vol. 27(1), pages 126-150.
    3. Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High Dimensional Vector Autoregressive Models," CEIS Research Paper 534, Tor Vergata University, CEIS, revised 24 Mar 2022.
    4. Matteo Barigozzi & Giuseppe Cavaliere & Lorenzo Trapani, 2024. "Inference in Heavy-Tailed Nonstationary Multivariate Time Series," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 119(545), pages 565-581, January.
    5. Boswijk, H Peter & Cavaliere, Giuseppe & De Angelis, Luca & Taylor, AM Robert, 2022. "Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models," Essex Finance Centre Working Papers 33707, University of Essex, Essex Business School.
    6. Helmut Lütkepohl & Aleksei Netsunajev, 2018. "The Relation between Monetary Policy and the Stock Market in Europe," Discussion Papers of DIW Berlin 1729, DIW Berlin, German Institute for Economic Research.
    7. She, Rui & Ling, Shiqing, 2020. "Inference in heavy-tailed vector error correction models," Journal of Econometrics, Elsevier, vol. 214(2), pages 433-450.
    8. Anna Pajor & Justyna Wróblewska, 2022. "Forecasting performance of Bayesian VEC-MSF models for financial data in the presence of long-run relationships," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 427-448, September.
    9. Guillermo Carlomagno & Antoni Espasa, 2021. "Discovering Specific Common Trends in a Large Set of Disaggregates: Statistical Procedures, their Properties and an Empirical Application," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 641-662, June.

  6. Giuseppe Cavaliere & Luca De Angelis & Anders Rahbek & A.M.Robert Taylor, 2013. "A comparison of sequential and information-based methods for determining the co-integration rank in heteroskedastic VAR models," Quaderni di Dipartimento 4, Department of Statistics, University of Bologna.

    Cited by:

    1. Gianluca Cubadda & Marco Mazzali, 2024. "The vector error correction index model: representation, estimation and identification," The Econometrics Journal, Royal Economic Society, vol. 27(1), pages 126-150.
    2. Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High Dimensional Vector Autoregressive Models," CEIS Research Paper 534, Tor Vergata University, CEIS, revised 24 Mar 2022.
    3. Boswijk, H Peter & Cavaliere, Giuseppe & De Angelis, Luca & Taylor, AM Robert, 2022. "Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models," Essex Finance Centre Working Papers 33707, University of Essex, Essex Business School.
    4. Pajor Anna & Wróblewska Justyna, 2017. "VEC-MSF models in Bayesian analysis of short- and long-run relationships," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(3), pages 1-22, June.
    5. Anna Pajor & Justyna Wróblewska, 2022. "Forecasting performance of Bayesian VEC-MSF models for financial data in the presence of long-run relationships," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 427-448, September.

  7. Michele Costa & Luca De angelis, 2010. "Model selection in hidden Markov models : a simulation study," Quaderni di Dipartimento 7, Department of Statistics, University of Bologna.

    Cited by:

    1. S. Bacci & S. Pandolfi & F. Pennoni, 2014. "A comparison of some criteria for states selection in the latent Markov model for longitudinal data," 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. 8(2), pages 125-145, June.
    2. Dias, José G. & Vermunt, Jeroen K. & Ramos, Sofia, 2015. "Clustering financial time series: New insights from an extended hidden Markov model," European Journal of Operational Research, Elsevier, vol. 243(3), pages 852-864.

Articles

  1. Angelini, Giovanni & De Angelis, Luca & Singleton, Carl, 2022. "Informational efficiency and behaviour within in-play prediction markets," International Journal of Forecasting, Elsevier, vol. 38(1), pages 282-299.
    See citations under working paper version above.
  2. Angelini, Giovanni & Candila, Vincenzo & De Angelis, Luca, 2022. "Weighted Elo rating for tennis match predictions," European Journal of Operational Research, Elsevier, vol. 297(1), pages 120-132.

    Cited by:

    1. He, Xue-Zhong & Treich, Nicolas, 2017. "Prediction market prices under risk aversion and heterogeneous beliefs," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 105-114.
    2. Alberto Arcagni & Vincenzo Candila & Rosanna Grassi, 2023. "A new model for predicting the winner in tennis based on the eigenvector centrality," Annals of Operations Research, Springer, vol. 325(1), pages 615-632, June.
    3. Luca De Angelis & J. James Reade, 2022. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Economics Discussion Papers em-dp2022-01, Department of Economics, University of Reading.
    4. Lawrence Clegg & John Cartlidge, 2023. "Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks," Papers 2306.01740, arXiv.org, revised Jul 2024.
    5. Ramirez, Philip & Reade, J. James & Singleton, Carl, 2023. "Betting on a buzz: Mispricing and inefficiency in online sportsbooks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1413-1423.
    6. Collingwood, James A.P. & Wright, Michael & Brooks, Roger J., 2023. "Simulating the progression of a professional snooker frame," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1286-1299.
    7. Luca De Angelis & J. James Reade, 2023. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Annals of Operations Research, Springer, vol. 325(1), pages 391-418, June.

  3. Monasterolo, Irene & de Angelis, Luca, 2020. "Blind to carbon risk? An analysis of stock market reaction to the Paris Agreement," Ecological Economics, Elsevier, vol. 170(C).

    Cited by:

    1. Alessi, Lucia & Battiston, Stefano & Kvedaras, Virmantas, 2024. "Over with carbon? Investors’ reaction to the Paris Agreement and the US withdrawal," Journal of Financial Stability, Elsevier, vol. 71(C).
    2. Caporin, Massimiliano & Fontini, Fulvio & Panzica, Roberto, 2023. "The systemic risk of US oil and natural gas companies," Energy Economics, Elsevier, vol. 121(C).
    3. D’Ecclesia, Rita Laura & Morelli, Giacomo & Stefanelli, Kevyn, 2024. "Energy ETF performance: The role of fossil fuels," Energy Economics, Elsevier, vol. 131(C).
    4. Alessi, Lucia & Elisa, Ossola & Panzica, Roberto, 2021. "When do investors go green? Evidence from a time-varying asset-pricing model," JRC Working Papers in Economics and Finance 2021-13, Joint Research Centre, European Commission.
    5. Ge, Xiaowen & Xue, Minggao & Cao, Ruiyi, 2024. "Do Chinese carbon-intensive stocks overreact to climate transition risk? Evidence from the COP26 news," International Review of Financial Analysis, Elsevier, vol. 94(C).
    6. Sibel Eker & Charlie Wilson & Niklas Hohne & Mark S. McCaffrey & Irene Monasterolo & Leila Niamir & Caroline Zimm, 2023. "A dynamic systems approach to harness the potential of social tipping," Papers 2309.14964, arXiv.org.
    7. Palea, Vera & Drogo, Federico, 2020. "Carbon Emissions and the Cost of Debt Financing: What Role for Policy Commitment, Firm Disclosure and Corporate Governance?," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202002, University of Turin.
    8. Lucia Alessi & Elisa, Ossola & Roberto Panzica, 2019. "The Greenium matters: greenhouse gas emissions, environmental disclosures, and stock prices," Working Papers 418, University of Milano-Bicocca, Department of Economics, revised Apr 2020.
    9. Ricardo Gimeno & Clara I. González, 2022. "The role of a green factor in stock prices. When Fama & French go green," Working Papers 2207, Banco de España.
    10. Shimbar, Ali, 2021. "Environment-related stranded assets: What does the market think about the impact of collective climate action on the value of fossil fuel stocks?," Energy Economics, Elsevier, vol. 103(C).
    11. Qingling Yu & Jing Li & Xinhai Lu & Liyu Wang, 2023. "A Multi-Attribute Approach for Low-Carbon and Intensive Land Use of Jinan, China," Land, MDPI, vol. 12(6), pages 1-22, June.
    12. Wang, Jiaxin & Qiang, Haofan & Liang, Yuchao & Huang, Xiang & Zhong, Wenrui, 2024. "How carbon risk affects corporate debt defaults: Evidence from Paris agreement," Energy Economics, Elsevier, vol. 129(C).
    13. Alessi, Lucia & Ossola, Elisa & Panzica, Roberto, 2021. "What greenium matters in the stock market? The role of greenhouse gas emissions and environmental disclosures," Journal of Financial Stability, Elsevier, vol. 54(C).
    14. Imane El Ouadghiri & Khaled Guesmi & Jonathan Peillex & Andreas Ziegler, 2019. "Public attention to environmental issues and stock market returns," MAGKS Papers on Economics 201922, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    15. Louis Daumas, 2021. "Should we fear transition risks - A review of the applied literature," Working Papers 2021.05, FAERE - French Association of Environmental and Resource Economists.
    16. Xing, Chao & Zhang, Yuming & Tripe, David, 2021. "Green credit policy and corporate access to bank loans in China: The role of environmental disclosure and green innovation," International Review of Financial Analysis, Elsevier, vol. 77(C).
    17. Siddhartha P. Chakrabarty & Suryadeepto Nag, 2023. "Risk measures and portfolio analysis in the paradigm of climate finance: a review," SN Business & Economics, Springer, vol. 3(3), pages 1-22, March.
    18. Andrea Ugolini & Juan C. Reboredo & Javier Ojea Ferreiro, 2023. "Is Climate Transition Risk Priced into Corporate Credit Risk? Evidence from Credit Default Swaps," Staff Working Papers 23-38, Bank of Canada.
    19. Ni, Yinan & Sun, Yanfei, 2023. "Environmental, social, and governance premium in Chinese stock markets," Global Finance Journal, Elsevier, vol. 55(C).
    20. Ouidad Yousfi & Nadia Loukil, 2024. "Environmental laws in France: What are the effects of the Grenelle laws on firms?," European Journal of Law and Economics, Springer, vol. 57(3), pages 347-389, June.
    21. Song, Yazhi & Li, Yin & Liu, Tiansen, 2023. "Carbon asset remolding and potential benefit measurement of machinery products in the light of lean production and low-carbon investment," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    22. Vítor Manuel de Sousa Gabriel & María Belén Lozano & Maria Fernanda Ludovina Inácio Matias, 2022. "The Low‐carbon Equity Market: A New Alternative for Investment Diversification?," Global Policy, London School of Economics and Political Science, vol. 13(1), pages 34-47, February.
    23. Michael D. Bauer & Eric Offner & Glenn D. Rudebusch, 2023. "The Effect of U.S. Climate Policy on Financial Markets: An Event Study of the Inflation Reduction Act," Working Paper Series 2023-30, Federal Reserve Bank of San Francisco.
    24. Nicholas Stern & Joseph E Stiglitz, 2023. "Climate change and growth," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 32(2), pages 277-303.
    25. Marzhan Beisenbina & Laura Fabregat‐Aibar & Maria‐Glòria Barberà‐Mariné & Maria‐Teresa Sorrosal‐Forradellas, 2023. "The burgeoning field of sustainable investment: Past, present and future," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(2), pages 649-667, April.
    26. Alessi, Lucia & Ossola, Elisa & Panzica, Roberto, 2023. "When do investors go green? Evidence from a time-varying asset-pricing model," International Review of Financial Analysis, Elsevier, vol. 90(C).
    27. Chen, Fanglin & Chen, Zhongfei & Zhang, Xin, 2024. "Belated stock returns for green innovation under carbon emissions trading market," Journal of Corporate Finance, Elsevier, vol. 85(C).
    28. Daniel Ramos-García & Carmen López-Martín & Raquel Arguedas-Sanz, 2023. "Climate transition risk in determining credit risk: evidence from firms listed on the STOXX Europe 600 index," Empirical Economics, Springer, vol. 65(5), pages 2091-2114, November.
    29. Refk Selmi, 2023. "Do investors care about carbon risk? The impact of the Paris agreement on the inflation hedging performance of commodities," Economics Bulletin, AccessEcon, vol. 43(2), pages 1111-1121.
    30. Reboredo, Juan C. & Ugolini, Andrea & Ojea-Ferreiro, Javier, 2022. "Do green bonds de-risk investment in low-carbon stocks?," Economic Modelling, Elsevier, vol. 108(C).
    31. Louisa Chen & Koji Takahashi, "undated". "The road to net zero: a fund flow investigation," BIS Working Papers 1220, Bank for International Settlements.
    32. Gourdel, Régis & Sydow, Matthias, 2023. "Non-banks contagion and the uneven mitigation of climate risk," International Review of Financial Analysis, Elsevier, vol. 89(C).
    33. Mueller, Isabella & Sfrappini, Eleonora, 2022. "Climate Change-Related Regulatory Risks and Bank Lending," Working Paper Series 2670, European Central Bank.
    34. Reboredo, Juan C. & Otero, Luis A., 2021. "Are investors aware of climate-related transition risks? Evidence from mutual fund flows," Ecological Economics, Elsevier, vol. 189(C).
    35. Wu, Gabriel Shui Tang & Wan, Wilson Tsz Shing, 2023. "What drives the cross-border spillover of climate transition risks? Evidence from global stock markets," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 432-447.
    36. Yang, Lu & Hamori, Shigeyuki, 2021. "The role of the carbon market in relation to the cryptocurrency market: Only diversification or more?," International Review of Financial Analysis, Elsevier, vol. 77(C).
    37. Indre Lapinskaite & Viktorija Skvarciany & Patrikas Janulevicius, 2020. "Impact of Investment Sources for Sustainability on a Country’s Sustainable Development: Evidence from the EU," Sustainability, MDPI, vol. 12(6), pages 1-24, March.
    38. Vilija Aleknevičien&# & Asta Bendoraityt&#, 2023. "Role of Green Finance in Greening the Economy: Conceptual Approach," Central European Business Review, Prague University of Economics and Business, vol. 2023(2), pages 105-130.
    39. Curcio, Domenico & Gianfrancesco, Igor & Vioto, Davide, 2023. "Climate change and financial systemic risk: Evidence from US banks and insurers," Journal of Financial Stability, Elsevier, vol. 66(C).
    40. Samson Mukanjari & Thomas Sterner, 2024. "Do markets Trump politics? Fossil and renewable market reactions to major political events," Economic Inquiry, Western Economic Association International, vol. 62(2), pages 805-836, April.
    41. Qingxia (Jenny) Wang, 2023. "Financial effects of carbon risk and carbon disclosure: A review," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(4), pages 4175-4219, December.
    42. Bingler, Julia Anna & Kraus, Mathias & Leippold, Markus & Webersinke, Nicolas, 2024. "How cheap talk in climate disclosures relates to climate initiatives, corporate emissions, and reputation risk," Journal of Banking & Finance, Elsevier, vol. 164(C).
    43. Nguyen, Quyen & Diaz-Rainey, Ivan & Kuruppuarachchi, Duminda, 2023. "In search of climate distress risk," International Review of Financial Analysis, Elsevier, vol. 85(C).
    44. Reboredo, Juan C. & Ugolini, Andrea, 2022. "Climate transition risk, profitability and stock prices," International Review of Financial Analysis, Elsevier, vol. 83(C).
    45. Ringe Wolf-Georg, 2023. "Investor Empowerment for Sustainability," Review of Economics, De Gruyter, vol. 74(1), pages 21-52, April.
    46. Livieri, Giulia & Radi, Davide & Smaniotto, Elia, 2024. "Pricing transition risk with a jump-diffusion credit risk model: evidences from the CDS market," LSE Research Online Documents on Economics 123650, London School of Economics and Political Science, LSE Library.
    47. Rabeh Khalfaoui & Salma Mefteh-Wali & Jean-Laurent Viviani & Sami Ben Jabeur & Mohammad Zoynul Abedin & Brian Lucey, 2022. "How do climate risk and clean energy spillovers, and uncertainty affect U.S. stock markets?," Post-Print hal-03797937, HAL.
    48. Wang, Lu & Wu, Jiangbin & Cao, Yang & Hong, Yanran, 2022. "Forecasting renewable energy stock volatility using short and long-term Markov switching GARCH-MIDAS models: Either, neither or both?," Energy Economics, Elsevier, vol. 111(C).
    49. Irene Monasterolo & Nepomuk Dunz & Andrea Mazzocchetti & Régis Gourdel, 2022. "Derisking the low-carbon transition: investors’ reaction to climate policies, decarbonization and distributive effects," Review of Evolutionary Political Economy, Springer, vol. 3(1), pages 31-71, April.
    50. Popescu, Ioana-Stefania & Gibon, Thomas & Hitaj, Claudia & Rubin, Mirco & Benetto, Enrico, 2023. "Are SRI funds financing carbon emissions? An input-output life cycle assessment of investment funds," Ecological Economics, Elsevier, vol. 212(C).
    51. Irene Aldridge & Payton Martin, 2022. "ESG In Corporate Filings: An AI Perspective," Papers 2212.00018, arXiv.org.
    52. Giulia Livieri & Davide Radi & Elia Smaniotto, 2023. "Pricing Transition Risk with a Jump-Diffusion Credit Risk Model: Evidences from the CDS market," Papers 2303.12483, arXiv.org.
    53. Garel, Alexandre & Petit-Romec, Arthur, 2021. "Investor rewards to environmental responsibility: Evidence from the COVID-19 crisis," Journal of Corporate Finance, Elsevier, vol. 68(C).
    54. Dunz, Nepomuk & Naqvi, Asjad & Monasterolo, Irene, 2021. "Climate sentiments, transition risk, and financial stability in a stock-flow consistent model," Journal of Financial Stability, Elsevier, vol. 54(C).
    55. Monica Billio & Michele Costola & Iva Hristova & Carmelo Latino & Loriana Pelizzon, 2021. "Inside the ESG ratings: (Dis)agreement and performance," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 28(5), pages 1426-1445, September.
    56. Billio, Monica & Costola, Michele & Hristova, Iva & Latino, Carmelo & Pelizzon, Loriana, 2022. "Sustainable finance: A journey toward ESG and climate risk," SAFE Working Paper Series 349, Leibniz Institute for Financial Research SAFE.
    57. Yevheniia Antoniuk & Thomas Leirvik, 2021. "Climate Transition Risk and the Impact on Green Bonds," JRFM, MDPI, vol. 14(12), pages 1-19, December.
    58. Ghaemi Asl, Mahdi & Ben Jabeur, Sami, 2024. "Could the Russia-Ukraine war stir up the persistent memory of interconnectivity among Islamic equity markets, energy commodities, and environmental factors?," Research in International Business and Finance, Elsevier, vol. 69(C).
    59. Gianni Guastella & Stefano Pareglio & Caterina Schiavoni, 2023. "An Empirical Approach to Integrating Climate Reputational Risk in Long-Term Scenario Analysis," Sustainability, MDPI, vol. 15(7), pages 1-17, March.
    60. Zanin, Luca, 2023. "A flexible estimation of sectoral portfolio exposure to climate transition risks in the European stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    61. Ghosh, Saibal, 2023. "Does climate legislation matter for bank lending? Evidence from MENA countries," Ecological Economics, Elsevier, vol. 212(C).
    62. Alexandre Garel & Arthur Petit-Romec, 2021. "Investor rewards to environmental responsibility: Evidence from the COVID-19 crisis," Post-Print hal-03204216, HAL.
    63. Emre Kuvvet, 2024. "Reassessing climate disclosure demands: An examination of stakeholder perspectives beyond institutional investors," Economic Affairs, Wiley Blackwell, vol. 44(1), pages 95-117, February.
    64. Vera Palea & Federico Drogo, 2020. "Carbon emissions and the cost of debt in the eurozone: The role of public policies, climate‐related disclosure and corporate governance," Business Strategy and the Environment, Wiley Blackwell, vol. 29(8), pages 2953-2972, December.
    65. Banerjee, Ameet Kumar & Özer, Zeynep Sueda & Rahman, Molla Ramizur & Sensoy, Ahmet, 2024. "How does the time-varying dynamics of spillover between clean and brown energy ETFs change with the intervention of climate risk and climate policy uncertainty?," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 442-468.
    66. Zhu, Qing & Lu, Kai & Liu, Shan & Ruan, Yinglin & Wang, Lin & Yang, Sung-Byung, 2022. "Can low-carbon value bring high returns? Novel quantitative trading from portfolio-of-investment targets in a new-energy market," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 755-769.
    67. Monasterolo,Irene & Mandel,Antoine & Battiston,Stefano & Mazzocchetti,Andrea & Oppermann,Klaus & Coony,Jonathan D'Entremont & Stretton,Stephen John & Stewart,Fiona Elizabeth & Dunz,Nepomuk Max Ferdina, 2022. "The Role of Green Financial Sector Initiatives in the Low-Carbon Transition : A Theoryof Change," Policy Research Working Paper Series 10181, The World Bank.
    68. Polat, Onur & Demirer, Riza & Ekşi, İbrahim Halil, 2024. "What drives green betas? Climate uncertainty or speculation," Finance Research Letters, Elsevier, vol. 60(C).
    69. Birindelli, Giuliana & Miazza, Aline & Paimanova, Viktoriia & Palea, Vera, 2023. "Just “blah blah blah”? Stock market expectations and reactions to COP26," International Review of Financial Analysis, Elsevier, vol. 88(C).
    70. Diaz-Rainey, Ivan & Gehricke, Sebastian A. & Roberts, Helen & Zhang, Renzhu, 2021. "Trump vs. Paris: The impact of climate policy on U.S. listed oil and gas firm returns and volatility," International Review of Financial Analysis, Elsevier, vol. 76(C).
    71. Agliardi, Elettra & Alexopoulos, Thomas & Karvelas, Kleanthis, 2023. "The environmental pillar of ESG and financial performance: A portfolio analysis," Energy Economics, Elsevier, vol. 120(C).
    72. He, Feng & Duan, Lin & Cao, Yi & Wen, Shuyang, 2024. "Green credit policy and corporate climate risk exposure," Energy Economics, Elsevier, vol. 133(C).
    73. Okorie, David Iheke & Wesseh, Presley K., 2023. "Climate agreements and carbon intensity: Towards increased production efficiency and technical progress?," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 300-313.
    74. Dirk Broeders & Marleen de Jonge & David Rijsbergen, 2024. "The European Carbon Bond Premium," Working Papers 798, DNB.
    75. Thomas Cauthorn & Christian Klein & Leonard Remme & Bernhard Zwergel, 2023. "Portfolio benefits of taxonomy orientated and renewable European electric utilities," Journal of Asset Management, Palgrave Macmillan, vol. 24(7), pages 558-571, December.
    76. Zhu, Danyu & Gao, Xin & Luo, Zijun & Xu, Weidong, 2022. "Environmental performance and corporate risk-taking: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    77. Imane El Ouadghiri & Mathieu Gomes & Jonathan Peillex & Guillaume Pijourlet, 2022. "Investor Attention to the Fossil Fuel Divestment Movement and Stock Returns," Post-Print hal-03549713, HAL.
    78. Demiralay, Sercan & Gencer, Hatice Gaye & Bayraci, Selcuk, 2022. "Carbon credit futures as an emerging asset: Hedging, diversification and downside risks," Energy Economics, Elsevier, vol. 113(C).
    79. Irene Monasterolo, 2020. "Embedding Finance in the Macroeconomics of Climate Change: Research Challenges and Opportunities Ahead," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 21(04), pages 25-32, November.
    80. Michele Costa, 2023. "The evaluation of the effects of ESG scores on financial markets," Working Papers wp1189, Dipartimento Scienze Economiche, Universita' di Bologna.
    81. Thomas Allen & Stéphane Dees & Jean Boissinot & Carlos Mateo Caicedo Graciano & Valérie Chouard & Laurent Clerc & Annabelle de Gaye & Antoine Devulder & Sébastien Diot & Noémie Lisack & Fulvio Pegorar, 2020. "Climate-Related Scenarios for Financial Stability Assessment: an Application to France," Working papers 774, Banque de France.
    82. Liu, Haiyue & Wang, Yile & Shi, Xiaoshuang & Pang, Lina, 2022. "How do environmental policies affect capital market reactions? Evidence from China's construction waste treatment policy," Ecological Economics, Elsevier, vol. 198(C).
    83. Bingler, Julia Anna & Colesanti Senni, Chiara & Monnin, Pierre, 2022. "Understand what you measure: Where climate transition risk metrics converge and why they diverge," Finance Research Letters, Elsevier, vol. 50(C).
    84. Han, Hope H. & Lee, Jiyoon & Wang, Boxian, 2023. "Greenhouse gas emissions, firm value, and the investor base: Evidence from Korea," Emerging Markets Review, Elsevier, vol. 56(C).
    85. Wu, Baohui & Zhu, Pingheng & Yin, Hua & Wen, Fenghua, 2023. "The risk spillover of high carbon enterprises in China: Evidence from the stock market," Energy Economics, Elsevier, vol. 126(C).

  4. Angelini, Giovanni & De Angelis, Luca, 2019. "Efficiency of online football betting markets," International Journal of Forecasting, Elsevier, vol. 35(2), pages 712-721.

    Cited by:

    1. Dagaev, Dmitry & Stoyan, Egor, 2020. "Parimutuel betting on the eSports duels: Evidence of the reverse favourite-longshot bias," Journal of Economic Psychology, Elsevier, vol. 81(C).
    2. Saidjon Shiralievich Tavarov & Alexander Sidorov & Zsolt Čonka & Murodbek Safaraliev & Pavel Matrenin & Mihail Senyuk & Svetlana Beryozkina & Inga Zicmane, 2023. "Control of Operational Modes of an Urban Distribution Grid under Conditions of Uncertainty," Energies, MDPI, vol. 16(8), pages 1-18, April.
    3. He, Xue-Zhong & Treich, Nicolas, 2017. "Prediction market prices under risk aversion and heterogeneous beliefs," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 105-114.
    4. Pascal Flurin Meier & Raphael Flepp & Egon Franck, 2021. "Are sports betting markets semistrong efficient? Evidence from the COVID-19 pandemic," Working Papers 387, University of Zurich, Department of Business Administration (IBW).
    5. Goto, Shingo & Yamada, Toru, 2023. "What drives biased odds in sports betting markets: Bettors’ irrationality and the role of bookmakers," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 252-270.
    6. Raphael Flepp & Oliver Merz & Egon Franck, 2024. "When the league table lies: Does outcome bias lead to informationally inefficient markets?," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 414-429, January.
    7. J Reade & C Singleton & L Vaughan Williams, 2020. "Betting Markets for English Premier League Results and Scorelines: Evaluating a Simple Forecasting Model," Economic Issues Journal Articles, Economic Issues, vol. 25(1), pages 87-106, March.
    8. David Winkelmann & Marius Ötting & Christian Deutscher & Tomasz Makarewicz, 2024. "Are Betting Markets Inefficient? Evidence From Simulations and Real Data," Journal of Sports Economics, , vol. 25(1), pages 54-97, January.
    9. Guy Elaad & J. James Reade & Carl Singleton, 2019. "Information, prices and efficiency in an online betting market," Economics Discussion Papers em-dp2019-10, Department of Economics, University of Reading.
    10. Luca De Angelis & J. James Reade, 2022. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Economics Discussion Papers em-dp2022-01, Department of Economics, University of Reading.
    11. da Costa, Igor Barbosa & Marinho, Leandro Balby & Pires, Carlos Eduardo Santos, 2022. "Forecasting football results and exploiting betting markets: The case of “both teams to score”," International Journal of Forecasting, Elsevier, vol. 38(3), pages 895-909.
    12. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    13. Marc Garnica-Caparrós & Daniel Memmert & Fabian Wunderlich, 2022. "Artificial data in sports forecasting: a simulation framework for analysing predictive models in sports," Information Systems and e-Business Management, Springer, vol. 20(3), pages 551-580, September.
    14. Wunderlich, Fabian & Memmert, Daniel, 2020. "Are betting returns a useful measure of accuracy in (sports) forecasting?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 713-722.
    15. Hegarty, Tadgh & Whelan, Karl, 2023. "Forecasting Soccer Matches With Betting Odds: A Tale of Two Markets," CEPR Discussion Papers 17949, C.E.P.R. Discussion Papers.
    16. Angelini, Giovanni & De Angelis, Luca & Singleton, Carl, 2022. "Informational efficiency and behaviour within in-play prediction markets," International Journal of Forecasting, Elsevier, vol. 38(1), pages 282-299.
    17. Hegarty, Tadgh & Whelan, Karl, 2023. "Do Gamblers Understand Complex Bets? Evidence From Asian Handicap Betting on Soccer," CEPR Discussion Papers 18153, C.E.P.R. Discussion Papers.
    18. Fischer, Kai & Haucap, Justus, 2020. "Betting market efficiency in the presence of unfamiliar shocks: The case of ghost games during the COVID-19 pandemic," DICE Discussion Papers 349, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    19. J. James Reade & Carl Singleton & Alasdair Brown, 2019. "Evaluating Strange Forecasts: The Curious Case of Football Match Scorelines," Economics Discussion Papers em-dp2019-18, Department of Economics, University of Reading, revised 01 Aug 2020.
    20. Ramirez, Philip & Reade, J. James & Singleton, Carl, 2023. "Betting on a buzz: Mispricing and inefficiency in online sportsbooks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1413-1423.
    21. Ruud H. Koning & Renske Zijm, 2023. "Betting market efficiency and prediction in binary choice models," Annals of Operations Research, Springer, vol. 325(1), pages 135-148, June.
    22. Oliver Merz & Raphael Flepp & Egon Franck, 2020. "Sonic Thunder vs. Brian the Snail : Are people affected by uninformative racehorse names?," Working Papers 384, University of Zurich, Department of Business Administration (IBW).
    23. Vaughan Williams Leighton & Liu Chunping & Dixon Lerato & Gerrard Hannah, 2021. "How well do Elo-based ratings predict professional tennis matches?," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(2), pages 91-105, June.
    24. Guy Elaad, 2020. "Home-field advantage and biased prediction markets in English soccer," Applied Economics Letters, Taylor & Francis Journals, vol. 27(14), pages 1170-1174, July.
    25. Kai Fischer & Justus Haucap, 2022. "Home advantage in professional soccer and betting market efficiency: The role of spectator crowds," Kyklos, Wiley Blackwell, vol. 75(2), pages 294-316, May.
    26. David Winkelmann & Christian Deutscher & Marius Ötting, 2021. "Bookmakers’ mispricing of the disappeared home advantage in the German Bundesliga after the COVID-19 break," Applied Economics, Taylor & Francis Journals, vol. 53(26), pages 3054-3064, June.
    27. Tadgh Hegarty, 2021. "Information and price efficiency in the absence of home crowd advantage," Applied Economics Letters, Taylor & Francis Journals, vol. 28(21), pages 1902-1907, December.
    28. Salvatore Caruso & Giuseppe Pernagallo, 2021. "On the efficiency of online soccer betting markets: a new methodology based on symbolic series," Economics Bulletin, AccessEcon, vol. 41(3), pages 1451-1460.
    29. Marius Otting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Papers 2211.06052, arXiv.org.
    30. Fry, John & Serbera, Jean-Philippe & Wilson, Rob, 2021. "Managing performance expectations in association football," Journal of Business Research, Elsevier, vol. 135(C), pages 445-453.
    31. Luca De Angelis & J. James Reade, 2023. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Annals of Operations Research, Springer, vol. 325(1), pages 391-418, June.
    32. Hegarty, Tadgh & Whelan, Karl, 2023. "Disagreement and Market Structure in Betting Markets: Theory and Evidence from European Soccer," MPRA Paper 117243, University Library of Munich, Germany.
    33. Hegarty, Tadgh & Whelan, Karl, 2024. "Comparing Two Methods for Testing the Efficiency of Sports Betting Markets," MPRA Paper 121382, University Library of Munich, Germany.
    34. Dmitry Dagaev & Egor Stoyan, 2019. "Parimutuel Betting On The Esports Duels: Reverse Favourite-Longshot Bias And Its Determinants," HSE Working papers WP BRP 216/EC/2019, National Research University Higher School of Economics.
    35. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2023. "Gambling on Momentum in Contests," Economics Discussion Papers em-dp2023-08, Department of Economics, University of Reading.

  5. Cavaliere, Giuseppe & De Angelis, Luca & Rahbek, Anders & Robert Taylor, A.M., 2018. "Determining The Cointegration Rank In Heteroskedastic Var Models Of Unknown Order," Econometric Theory, Cambridge University Press, vol. 34(2), pages 349-382, April.
    See citations under working paper version above.
  6. Giuseppe Cavaliere & Luca De Angelis & Luca Fanelli, 2018. "Co†integration Rank Determination in Partial Systems Using Information Criteria," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(1), pages 65-89, February.

    Cited by:

    1. Takamitsu Kurita & Bent Nielsen, 2019. "Partial Cointegrated Vector Autoregressive Models with Structural Breaks in Deterministic Terms," Econometrics, MDPI, vol. 7(4), pages 1-35, October.
    2. Guillermo Carlomagno & Antoni Espasa, 2021. "Discovering Specific Common Trends in a Large Set of Disaggregates: Statistical Procedures, their Properties and an Empirical Application," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 641-662, June.
    3. Takamitsu Kurita & B. Nielsen, 2018. "Partial cointegrated vector autoregressive models with structural breaks in deterministic terms," Economics Papers 2018-W03, Economics Group, Nuffield College, University of Oxford.

  7. 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.
    See citations under working paper version above.
  8. Luca De Angelis & Attilio Gardini, 2015. "Disequilibria and contagion in financial markets: Evidence from a new test," Journal of Applied Economics, Universidad del CEMA, vol. 18, pages 247-266, November.

    Cited by:

    1. Valizadeh, Pourya & Karali, Berna & Ferreira, Susana, 2017. "Ripple effects of the 2011 Japan earthquake on international stock markets," Research in International Business and Finance, Elsevier, vol. 41(C), pages 556-576.
    2. Priya Malhotra & Pankaj Sinha, 2024. "Balanced Funds in India Amid COVID-19 Crisis: Spreader of Financial Contagion?," IIM Kozhikode Society & Management Review, , vol. 13(1), pages 7-24, January.
    3. Niţoi, Mihai & Pochea, Maria Miruna, 2020. "Time-varying dependence in European equity markets: A contagion and investor sentiment driven analysis," Economic Modelling, Elsevier, vol. 86(C), pages 133-147.

  9. Giuseppe Cavaliere & Luca De Angelis & Anders Rahbek & A. M. Robert Taylor, 2015. "A Comparison of Sequential and Information-based Methods for Determining the Co-integration Rank in Heteroskedastic VAR Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(1), pages 106-128, February.
    See citations under working paper version above.
  10. De Angelis, Luca & Dias, José G., 2014. "Mining categorical sequences from data using a hybrid clustering method," European Journal of Operational Research, Elsevier, vol. 234(3), pages 720-730.

    Cited by:

    1. Marco Guerra & Francesca Bassi & José G. Dias, 2020. "A Multiple-Indicator Latent Growth Mixture Model to Track Courses with Low-Quality Teaching," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(2), pages 361-381, January.
    2. Trindade, Graça & Dias, José G. & Ambrósio, Jorge, 2017. "Extracting clusters from aggregate panel data: A market segmentation study," Applied Mathematics and Computation, Elsevier, vol. 296(C), pages 277-288.
    3. Huang, Yan & Kou, Gang & Peng, Yi, 2017. "Nonlinear manifold learning for early warnings in financial markets," European Journal of Operational Research, Elsevier, vol. 258(2), pages 692-702.
    4. Rota Bulò, Samuel & Pelillo, Marcello, 2017. "Dominant-set clustering: A review," European Journal of Operational Research, Elsevier, vol. 262(1), pages 1-13.

  11. Luca De Angelis & Leonard J. Paas, 2013. "A dynamic analysis of stock markets using a hidden Markov model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(8), pages 1682-1700, August.

    Cited by:

    1. Anton Gerunov, 2023. "Stock Returns Under Different Market Regimes: An Application of Markov Switching Models to 24 European Indices," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 18-35.
    2. Beatrice Foroni & Luca Merlo & Lea Petrella, 2023. "Expectile hidden Markov regression models for analyzing cryptocurrency returns," Papers 2301.09722, arXiv.org, revised Jan 2024.
    3. De Angelis Luca & Viroli Cinzia, 2017. "A Markov-switching regression model with non-Gaussian innovations: estimation and testing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(2), pages 1-22, April.
    4. Leonard Paas, 2014. "Comments on: Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 473-477, September.
    5. Pennoni, Fulvia & Bartolucci, Francesco & Forte, Gianfranco & Ametrano, Ferdinando, 2020. "Exploring the dependencies among main cryptocurrency log-returns: A hidden Markov model," MPRA Paper 106150, University Library of Munich, Germany.
    6. Ichkitidze, Yuri, 2018. "Temporary price trends in the stock market with rational agents," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 103-117.
    7. Beatrice Foroni & Luca Merlo & Lea Petrella, 2023. "Quantile and expectile copula-based hidden Markov regression models for the analysis of the cryptocurrency market," Papers 2307.06400, arXiv.org.
    8. Dias, José G. & Vermunt, Jeroen K. & Ramos, Sofia, 2015. "Clustering financial time series: New insights from an extended hidden Markov model," European Journal of Operational Research, Elsevier, vol. 243(3), pages 852-864.
    9. Valeriy Zakamulin, 2023. "Not all bull and bear markets are alike: insights from a five-state hidden semi-Markov model," Risk Management, Palgrave Macmillan, vol. 25(1), pages 1-25, March.
    10. Giner, Javier & Zakamulin, Valeriy, 2023. "A regime-switching model of stock returns with momentum and mean reversion," Economic Modelling, Elsevier, vol. 122(C).
    11. Tsukasa Hokimoto & Kunio Shimizu, 2014. "A non-homogeneous hidden Markov model for predicting the distribution of sea surface elevation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(2), pages 294-319, February.
    12. Danisman, Ozgur & Uzunoglu Kocer, Umay, 2021. "Hidden Markov models with binary dependence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).

  12. Luca De Angelis, 2013. "Latent class models for financial data analysis: some statistical developments," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(2), pages 227-242, June.

    Cited by:

    1. Fabrizio Durante & Roberta Pappadà & Nicola Torelli, 2014. "Clustering of financial time series in risky scenarios," 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. 8(4), pages 359-376, December.

  13. Attilio Gardini & Luca De Angelis, 2012. "A statistical procedure for testing financial contagion," Statistica, Department of Statistics, University of Bologna, vol. 72(1), pages 37-61.

    Cited by:

    1. Serge Darolles & Jeremy Dudek & Gaëlle Le Fol, 2014. "Contagion in Emerging Markets," Post-Print hal-01632778, HAL.

  14. Michele Costa & Luca De Angelis, 2008. "The Multidimensional Measurement Of Poverty: A Fuzzy Set Approach," Statistica, Department of Statistics, University of Bologna, vol. 68(3), pages 303-319.

    Cited by:

    1. Lakhimi Nath & Dr. Mausumi Sen & Dr. Sumanash Dutta, 2015. "Women Empowerment and Occupation Linkage: A Case Study of Nagaon District," Indian Journal of Commerce and Management Studies, Educational Research Multimedia & Publications,India, vol. 6(3), pages 37-42, September.
    2. Bao, Yan Xi & Liao, Ting Xuan, 2021. "Capability Approach: Reconciling the Absolute Core and the Multidimensional Relative Poverty Measures," MPRA Paper 111333, University Library of Munich, Germany.
    3. Ke-Mei Chen & Chao-Hsien Leu & Te-Mu Wang, 2019. "Measurement and Determinants of Multidimensional Poverty: Evidence from Taiwan," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(2), pages 459-478, September.
    4. Carlo Drago, 2021. "The Analysis and the Measurement of Poverty: An Interval-Based Composite Indicator Approach," Economies, MDPI, vol. 9(4), pages 1-17, October.
    5. Antonio Acconcia & Maria Carannante & Michelangelo Misuraca & Germana Scepi, 2020. "Measuring Vulnerability to Poverty with Latent Transition Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 151(1), pages 1-31, August.
    6. Oula Ben Hassine & Hela Bouras, 2022. "Fuzzy Measures of Monetary and Non-monetary Deprivations in Tunisia," International Journal of Economics and Financial Issues, Econjournals, vol. 12(4), pages 65-71, July.
    7. Leu, Chao-Hsien & Chen, Ke-Mei & Chen, Hsiu-Hui, 2016. "A multidimensional approach to child poverty in Taiwan," Children and Youth Services Review, Elsevier, vol. 66(C), pages 35-44.
    8. Anh Thu Quang Pham & Pundarik Mukhopadhaya, 2022. "Multidimensionl Poverty and The Role of Social Capital in Poverty Alleviation Among Ethnic Groups in Rural Vietnam: A Multilevel Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(1), pages 281-317, January.
    9. Delalić Adela & Somun-Kapetanović Rabija & Resić Emina, 2017. "New multidimensional approaches to poverty measurement in Bosnia and Herzegovina," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 3(1), pages 1-15, June.
    10. Martina Ciani & Francesca Gagliardi & Samuele Riccarelli & Gianni Betti, 2018. "Fuzzy Measures of Multidimensional Poverty in the Mediterranean Area: A Focus on Financial Dimension," Sustainability, MDPI, vol. 11(1), pages 1-13, December.

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