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
- 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:
- 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.
- 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.
- 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.
Cited by:
- 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.
- 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.
- 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.
- J. James Reade & Carl Singleton & Leighton Vaughan Williams, 2020. "Betting markets for English Premier League results and scorelines: evaluating a forecasting model," Economics Discussion Papers em-dp2020-03, Department of Economics, University of Reading.
- 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.
- 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).
- Kai Fischer & Justus Haucap, 2020. "Betting Market Efficiency in the Presence of Unfamiliar Shocks: The Case of Ghost Games during the Covid-19 Pandemic," CESifo Working Paper Series 8526, CESifo.
- 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.
- Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022.
"Gambling on Momentum,"
Economics Discussion Papers
em-dp2022-10, Department of Economics, University of Reading.
- Marius Otting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Papers 2211.06052, arXiv.org.
- 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.
- 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.
- 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.
- 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.
- Pawlowski, Tim & Rambaccussing, Dooruj & Ramirez, Philip & Reade, J. James & Rossi, Giambattista, 2024. "Exploring entertainment utility from football games," Journal of Economic Behavior & Organization, Elsevier, vol. 223(C), pages 185-198.
- 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.
- 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.
- 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.
- Philip Ramirez & J. James Reade & Carl Singleton, 2021. "Betting on a buzz, mispricing and inefficiency in online sportsbooks," Economics Discussion Papers em-dp2021-10, Department of Economics, University of Reading, revised 27 Jul 2022.
- 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.
- 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.
- 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.
- Giovanni Angelini & Luca De Angelis, 2016.
"PARX model for football matches predictions,"
Quaderni di Dipartimento
2, Department of Statistics, University of Bologna.
- 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.
Cited by:
- 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.
- Andrei Shynkevich, 2022. "Informational efficiency of football transfer market," Economics Bulletin, AccessEcon, vol. 42(2), pages 1032-1039.
- Angelini, Giovanni & De Angelis, Luca, 2019. "Efficiency of online football betting markets," International Journal of Forecasting, Elsevier, vol. 35(2), pages 712-721.
- 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.
- Raffaele Mattera, 2023. "Forecasting binary outcomes in soccer," Annals of Operations Research, Springer, vol. 325(1), pages 115-134, June.
- 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.
- 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.
- 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.
- Lu, Ye & Suthaharan, Neyavan, 2023. "Electricity price spike clustering: A zero-inflated GARX approach," Energy Economics, Elsevier, vol. 124(C).
- Šárka Hudecová & Marie Hušková & Simos G. Meintanis, 2024. "Specifications tests for count time series models with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 33(4), pages 1014-1040, December.
- Giovanni Angelini & Giuseppe Cavaliere & Enzo D'Innocenzo & Luca De Angelis, 2022. "Time-Varying Poisson Autoregression," Papers 2207.11003, arXiv.org.
- 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.
- Siem Jan (S.J.) Koopman & Rutger Lit, 2017. "Forecasting Football Match Results in National League Competitions Using Score-Driven Time Series Models," Tinbergen Institute Discussion Papers 17-062/III, Tinbergen Institute.
- 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:
- 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.
- 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.
- 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.
Cited by:
- 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.
- Gianluca Cubadda & Alain Hecq, 2020. "Dimension Reduction for High Dimensional Vector Autoregressive Models," Papers 2009.03361, arXiv.org, revised Feb 2022.
- Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High‐Dimensional Vector Autoregressive Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(5), pages 1123-1152, October.
- Matteo Barigozzi & Giuseppe Cavaliere & Lorenzo Trapani, 2021.
"Inference in heavy-tailed non-stationary multivariate time series,"
Papers
2107.13894, arXiv.org.
- 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.
- Martin Bruns & Helmut Lutkepohl, 2024. "Heteroskedastic Structural Vector Autoregressions Identified via Long-run Restrictions," University of East Anglia School of Economics Working Paper Series 2024-06, School of Economics, University of East Anglia, Norwich, UK..
- She, Rui & Ling, Shiqing, 2020. "Inference in heavy-tailed vector error correction models," Journal of Econometrics, Elsevier, vol. 214(2), pages 433-450.
- 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.
- Helmut Lütkepohl & Aleksei Netšunajev, 2018.
"The Relation between Monetary Policy and the Stock Market in Europe,"
Econometrics, MDPI, vol. 6(3), pages 1-14, August.
- 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.
- H. Peter Boswijk & Giuseppe Cavaliere & Luca De Angelis & A. M. Robert Taylor, 2023.
"Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models,"
Econometric Reviews, Taylor & Francis Journals, vol. 42(9-10), pages 725-757, November.
- 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.
- H. Peter Boswijk & Giuseppe Cavaliere & Luca De Angelis & A. M. Robert Taylor, 2022. "Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models," Papers 2202.02532, arXiv.org.
- Gianluca Cubadda, 2024. "VAR models with an index structure: A survey with new results," Papers 2412.11278, arXiv.org.
- Gianluca Cubadda & Marco Mazzali, 2023.
"The Vector Error Correction Index Model: Representation, Estimation and Identification,"
CEIS Research Paper
556, Tor Vergata University, CEIS, revised 04 Apr 2023.
- 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.
- 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).
- 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.
- Martin Bruns & Helmut Lütkepohl, 2024. "Heteroskedastic Structural Vector Autoregressions Identified via Long-run Restrictions," Discussion Papers of DIW Berlin 2103, DIW Berlin, German Institute for Economic Research.
- 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.
- 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.
Cited by:
- 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.
- Gianluca Cubadda & Alain Hecq, 2020. "Dimension Reduction for High Dimensional Vector Autoregressive Models," Papers 2009.03361, arXiv.org, revised Feb 2022.
- Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High‐Dimensional Vector Autoregressive Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(5), pages 1123-1152, October.
- 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.
- 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.
- H. Peter Boswijk & Giuseppe Cavaliere & Luca De Angelis & A. M. Robert Taylor, 2023.
"Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models,"
Econometric Reviews, Taylor & Francis Journals, vol. 42(9-10), pages 725-757, November.
- 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.
- H. Peter Boswijk & Giuseppe Cavaliere & Luca De Angelis & A. M. Robert Taylor, 2022. "Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models," Papers 2202.02532, arXiv.org.
- Gianluca Cubadda, 2024. "VAR models with an index structure: A survey with new results," Papers 2412.11278, arXiv.org.
- Gianluca Cubadda & Marco Mazzali, 2023.
"The Vector Error Correction Index Model: Representation, Estimation and Identification,"
CEIS Research Paper
556, Tor Vergata University, CEIS, revised 04 Apr 2023.
- 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.
- 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:
- 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.
- 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
- 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.
Cited by:
- Xuepeng Liu & Emanuel Ornelas & Huimin Shi, 2024. "Was COVID-19 a Game Changer for the Tokyo and Beijing Olympics?," Journal of Sports Economics, , vol. 25(7), pages 866-886, October.
- 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.
- 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.
- 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:
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Philip Ramirez & J. James Reade & Carl Singleton, 2021. "Betting on a buzz, mispricing and inefficiency in online sportsbooks," Economics Discussion Papers em-dp2021-10, Department of Economics, University of Reading, revised 27 Jul 2022.
- 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.
- 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:
- D’Ecclesia, Rita Laura & Morelli, Giacomo & Stefanelli, Kevyn, 2024. "Energy ETF performance: The role of fossil fuels," Energy Economics, Elsevier, vol. 131(C).
- 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.
- 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.
- 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.
- 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).
- 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).
- 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).
- 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.
- Ugolini, Andrea & Reboredo, Juan C. & Ojea-Ferreiro, Javier, 2024. "Is climate transition risk priced into corporate credit risk? Evidence from credit default swaps," Research in International Business and Finance, Elsevier, vol. 70(PB).
- Ugolini, Andrea & Reboredo, Juan Carlos & Ojea-Ferreiro, Javier, 2023. "Is Climate Transition Risk Priced into Corporate Credit Risk? Evidence from Credit Default Swaps," FEEM Working Papers 330720, Fondazione Eni Enrico Mattei (FEEM).
- Andrea Ugolini & Juan C. Reboredo & Javier Ojea-Ferreiro, 2023. "Is Climate Transition Risk Priced into Corporate Credit Risk? Evidence from Credit Default Swaps," Working Papers 2023.04, Fondazione Eni Enrico Mattei.
- Andrea Ugolini & Juan C. Reboredo & Javier Ojea-Ferreiro, 2023. "Is climate transition risk priced into corporate credit risk? Evidence from credit default swaps," Working Papers 509, University of Milano-Bicocca, Department of Economics.
- Ni, Yinan & Sun, Yanfei, 2023. "Environmental, social, and governance premium in Chinese stock markets," Global Finance Journal, Elsevier, vol. 55(C).
- 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.
- 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.
- 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).
- 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.
- Refk Selmi, 2023. "Do investors care about carbon risk? The impact of the Paris agreement on the inflation hedging performance of commodities," Post-Print hal-04133736, HAL.
- Pastén-Henríquez, Boris & Tapia-Griñen, Pablo & Sepúlveda-Velásquez, Jorge, 2024. "Environmental policies on the systematic risk of critical metals companies," Finance Research Letters, Elsevier, vol. 69(PA).
- Louis Daumas, 2024. "Financial stability, stranded assets and the low‐carbon transition – A critical review of the theoretical and applied literatures," Journal of Economic Surveys, Wiley Blackwell, vol. 38(3), pages 601-716, July.
- Gourdel, Régis & Sydow, Matthias, 2023. "Non-banks contagion and the uneven mitigation of climate risk," International Review of Financial Analysis, Elsevier, vol. 89(C).
- Mueller, Isabella & Sfrappini, Eleonora, 2022. "Climate Change-Related Regulatory Risks and Bank Lending," Working Paper Series 2670, European Central Bank.
- 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).
- 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.
- 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.
- Marie Bessec & Julien Fouquau, 2024.
"A Green Wave in Media: A Change of Tack in Stock Markets,"
Post-Print
hal-04706501, HAL.
- Marie Bessec & Julien Fouquau, 2024. "A Green Wave in Media: A Change of Tack in Stock Markets," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(5), pages 1026-1057, October.
- 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).
- Reboredo, Juan C. & Ugolini, Andrea, 2022. "Climate transition risk, profitability and stock prices," International Review of Financial Analysis, Elsevier, vol. 83(C).
- Ringe Wolf-Georg, 2023. "Investor Empowerment for Sustainability," Review of Economics, De Gruyter, vol. 74(1), pages 21-52, April.
- Caporin, Massimiliano & Fontini, Fulvio & Panzica, Roberto, 2022.
"The systemic risk of US oil and natural gas companies,"
JRC Working Papers in Economics and Finance
2022-11, Joint Research Centre, European Commission.
- Caporin, Massimiliano & Fontini, Fulvio & Panzica, Roberto, 2023. "The systemic risk of US oil and natural gas companies," Energy Economics, Elsevier, vol. 121(C).
- 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.
- 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.
- Khalfaoui, Rabeh & Mefteh-Wali, Salma & Viviani, Jean-Laurent & Ben Jabeur, Sami & Abedin, Mohammad Zoynul & Lucey, Brian M., 2022. "How do climate risk and clean energy spillovers, and uncertainty affect U.S. stock markets?," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
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Cited by:
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Economic Issues Journal Articles, Economic Issues, vol. 25(1), pages 87-106, March.
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- 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.
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CEPR Discussion Papers
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"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
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- 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.
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"Gambling on Momentum,"
Economics Discussion Papers
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- Marius Otting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Papers 2211.06052, arXiv.org.
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- 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.
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- 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.
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"Betting on a buzz: Mispricing and inefficiency in online sportsbooks,"
International Journal of Forecasting, Elsevier, vol. 39(3), pages 1413-1423.
- Philip Ramirez & J. James Reade & Carl Singleton, 2021. "Betting on a buzz, mispricing and inefficiency in online sportsbooks," Economics Discussion Papers em-dp2021-10, Department of Economics, University of Reading, revised 27 Jul 2022.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Hegarty, Tadgh & Whelan, Karl, 2023. "Disagreement and Market Structure in Betting Markets: Theory and Evidence from European Soccer," CEPR Discussion Papers 18144, C.E.P.R. Discussion Papers.
- Hegarty, Tadgh & Whelan, Karl, 2024. "Comparing Two Methods for Testing the Efficiency of Sports Betting Markets," MPRA Paper 121382, University Library of Munich, Germany.
- 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.
- 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.
- 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:
- 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.
- 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.
- 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.
- 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.
- Giovanni Angelini & Luca De Angelis, 2016. "PARX model for football matches predictions," Quaderni di Dipartimento 2, Department of Statistics, University of Bologna.
- 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.
- Luca De Angelis & Attilio Gardini, 2015. "Disequilibria and Contagion in Financial Markets: Evidence from a New Test," Journal of Applied Economics, Taylor & Francis Journals, vol. 18(2), pages 247-265, November.
Cited by:
- 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.
- 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.
- 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.
- 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.
- 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.
- 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:
- 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.
- 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.
- 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.
- Rota Bulò, Samuel & Pelillo, Marcello, 2017. "Dominant-set clustering: A review," European Journal of Operational Research, Elsevier, vol. 262(1), pages 1-13.
- 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:
- Beatrice Foroni & Luca Merlo & Lea Petrella, 2023. "Expectile hidden Markov regression models for analyzing cryptocurrency returns," Papers 2301.09722, arXiv.org, revised Jan 2024.
- 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.
- 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.
- 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.
- 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.
- Beatrice Foroni & Luca Merlo & Lea Petrella, 2024. "Hidden Markov graphical models with state-dependent generalized hyperbolic distributions," Papers 2412.03668, arXiv.org.
- Danisman, Ozgur & Uzunoglu Kocer, Umay, 2021. "Hidden Markov models with binary dependence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
- 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.
- 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.
- 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.
- 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.
- 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.
- Giner, Javier & Zakamulin, Valeriy, 2023. "A regime-switching model of stock returns with momentum and mean reversion," Economic Modelling, Elsevier, vol. 122(C).
- 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.
- 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:
- 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.
- 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:
- Serge Darolles & Jeremy Dudek & Gaëlle Le Fol, 2014.
"Contagion in Emerging Markets,"
Post-Print
hal-01632778, HAL.
- Serge Darolles & Jérémy Dudek & Gaëlle Le Fol, 2015. "Contagion in Emerging Markets," Palgrave Macmillan Books, in: Nigel Finch (ed.), Emerging Markets and Sovereign Risk, chapter 3, pages 45-58, Palgrave Macmillan.
- Serge Darolles & Jeremy Dudek & Gaëlle Le Fol, 2014.
"Contagion in Emerging Markets,"
Post-Print
hal-01632778, HAL.
- 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:
- 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.
- 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.
- 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.
- 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.
- Drago, Carlo, 2020.
"The Analysis and the Measurement of Poverty: An Interval Based Composite Indicator Approach,"
MPRA Paper
104462, University Library of Munich, Germany.
- Drago, Carlo, 2021. "The Analysis and the Measurement of Poverty: An Interval-Based Composite Indicator Approach," MPRA Paper 109307, University Library of Munich, Germany.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.