IDEAS home Printed from https://ideas.repec.org/f/pma2509.html
   My authors  Follow this author

Raffaele Mattera

Personal Details

First Name:Raffaele
Middle Name:
Last Name:Mattera
Suffix:
RePEc Short-ID:pma2509
[This author has chosen not to make the email address public]
Terminal Degree: Dipartimento di Scienze Sociali ed Economiche; "Sapienza" Università di Roma (from RePEc Genealogy)

Affiliation

Dipartimento di Scienze Economiche e Statistiche
Università degli Studi di Napoli - "Federico II"

Napoli, Italy
http://www.dises.unina.it/
RePEc:edi:esnapit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.
  2. George Athanasopoulos & Rob J Hyndman & Raffaele Mattera, 2023. "Improving out-of-sample Forecasts of Stock Price Indexes with Forecast Reconciliation and Clustering," Monash Econometrics and Business Statistics Working Papers 17/23, Monash University, Department of Econometrics and Business Statistics.
  3. Roy Cerqueti & R. Mattera, 2023. "Fuzzy clustering of time series with time-varying memory," Post-Print hal-04321357, HAL.
  4. Roy Cerqueti & Raffaele Mattera & Germana Scepi, 2022. "Multiway clustering with time-varying parameters," Post-Print hal-04321377, HAL.
  5. Roy Cerqueti & P. d'Urso & L. de Giovanni & R. Mattera & V. Vitale, 2022. "INGARCH-based fuzzy clustering of count time series with a football application," Post-Print hal-04321538, HAL.
  6. Roy Cerqueti & L. de Giovanni & P. d'Urso & M. Giacalone & R. Mattera, 2022. "Weighted score-driven fuzzy clustering of time series with a financial application," Post-Print hal-03789065, HAL.
  7. Roy Cerqueti & M. Giacalone & R. Mattera, 2021. "Model-based fuzzy time series clustering of conditional higher moments," Post-Print hal-03789115, HAL.
  8. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.

Articles

  1. Mattera, Raffaele & Franses, Philip Hans, 2023. "Are African business cycles synchronized? Evidence from spatio-temporal modeling," Economic Modelling, Elsevier, vol. 128(C).
  2. Raffaele Mattera & Michelangelo Misuraca & Maria Spano & Germana Scepi, 2023. "Mixed frequency composite indicators for measuring public sentiment in the EU," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2357-2382, June.
  3. Raffaele Mattera, 2023. "Forecasting binary outcomes in soccer," Annals of Operations Research, Springer, vol. 325(1), pages 115-134, June.
  4. Raffaele Mattera & Fabrizio Di Sciorio & Juan E. Trinidad-Segovia & Sameh S. Askar, 2022. "A Composite Index for Measuring Stock Market Inefficiency," Complexity, Hindawi, vol. 2022, pages 1-13, January.
  5. Juan E. Trinidad Segovia & Fabrizio Di Sciorio & Raffaele Mattera & Maria Spano & Wei Xing Zhou, 2022. "A Bibliometric Analysis on Agent-Based Models in Finance: Identification of Community Clusters and Future Research Trends," Complexity, Hindawi, vol. 2022, pages 1-11, September.
  6. Giacalone, Massimiliano & Mattera, Raffaele & Nissi, Eugenia, 2022. "Well-being analysis of Italian provinces with spatial principal components," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
  7. Massimiliano Giacalone & Raffaele Mattera & Eugenia Nissi, 2020. "Economic indicators forecasting in presence of seasonal patterns: time series revision and prediction accuracy," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 67-84, February.
  8. Massimiliano Giacalone & Raffaele Mattera & Carlo Cusatelli, 2018. "Do sustainable well-being indicators affect GDP? Evidence from a longitudinal study in Italy based on BES approach," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 72(3), pages 125-148, July-Sept.
  9. Massimiliano Giacalone & Demetrio Panarello & Raffaele Mattera, 2018. "Multicollinearity in regression: an efficiency comparison between Lp-norm and least squares estimators," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1831-1859, July.

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. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.

    Cited by:

    1. Philipp Otto & Osman Dou{g}an & Suleyman Tac{s}p{i}nar & Wolfgang Schmid & Anil K. Bera, 2023. "Spatial and Spatiotemporal Volatility Models: A Review," Papers 2308.13061, arXiv.org.
    2. Tim Kutzker & Dominik Wied, 2024. "Testing the correct specification of a system of spatial dependence models for stock returns," Empirical Economics, Springer, vol. 66(5), pages 2083-2103, May.

  2. George Athanasopoulos & Rob J Hyndman & Raffaele Mattera, 2023. "Improving out-of-sample Forecasts of Stock Price Indexes with Forecast Reconciliation and Clustering," Monash Econometrics and Business Statistics Working Papers 17/23, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Cerqueti, Roy & Ficcadenti, Valerio & Mattera, Raffaele, 2024. "Investors’ attention and network spillover for commodity market forecasting," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).

  3. Roy Cerqueti & R. Mattera, 2023. "Fuzzy clustering of time series with time-varying memory," Post-Print hal-04321357, HAL.

    Cited by:

    1. Ruixin Wang & Kaijie Xu & Yixi Wang, 2024. "Augmentation of Soft Partition with a Granular Prototype Based Fuzzy C-Means," Mathematics, MDPI, vol. 12(11), pages 1-14, May.
    2. Weiwei Mao & Kaijie Xu, 2024. "Enhancement of the Classification Performance of Fuzzy C-Means through Uncertainty Reduction with Cloud Model Interpolation," Mathematics, MDPI, vol. 12(7), pages 1-13, March.

  4. Roy Cerqueti & P. d'Urso & L. de Giovanni & R. Mattera & V. Vitale, 2022. "INGARCH-based fuzzy clustering of count time series with a football application," Post-Print hal-04321538, HAL.

    Cited by:

    1. Ángel López‐Oriona & Ying Sun & Rosa María Crujeiras, 2025. "Fuzzy Clustering of Circular Time Series With Applications to Wind Data," Environmetrics, John Wiley & Sons, Ltd., vol. 36(2), March.

  5. Roy Cerqueti & L. de Giovanni & P. d'Urso & M. Giacalone & R. Mattera, 2022. "Weighted score-driven fuzzy clustering of time series with a financial application," Post-Print hal-03789065, HAL.

    Cited by:

    1. Roy Cerqueti & Raffaele Mattera & Germana Scepi, 2024. "Multiway clustering with time-varying parameters," Computational Statistics, Springer, vol. 39(1), pages 51-92, February.
    2. Luis Lorenzo & Javier Arroyo, 2023. "Online risk-based portfolio allocation on subsets of crypto assets applying a prototype-based clustering algorithm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-40, December.
    3. Ángel López‐Oriona & Ying Sun & Rosa María Crujeiras, 2025. "Fuzzy Clustering of Circular Time Series With Applications to Wind Data," Environmetrics, John Wiley & Sons, Ltd., vol. 36(2), March.
    4. Reza Mortazavi & Elham Enayati & Abdolali Basiri, 2024. "Accelerated Sequential Data Clustering," Journal of Classification, Springer;The Classification Society, vol. 41(2), pages 245-263, July.

  6. Roy Cerqueti & M. Giacalone & R. Mattera, 2021. "Model-based fuzzy time series clustering of conditional higher moments," Post-Print hal-03789115, HAL.

    Cited by:

    1. Roy Cerqueti & Raffaele Mattera & Germana Scepi, 2024. "Multiway clustering with time-varying parameters," Computational Statistics, Springer, vol. 39(1), pages 51-92, February.
    2. Roy Cerqueti & Pierpaolo D’Urso & Livia Giovanni & Raffaele Mattera & Vincenzina Vitale, 2024. "Fuzzy clustering of time series based on weighted conditional higher moments," Computational Statistics, Springer, vol. 39(6), pages 3091-3114, September.
    3. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.
    4. Giulio Mattera & Gianfranco Piscopo & Maria Longobardi & Massimiliano Giacalone & Luigi Nele, 2024. "Improving the Interpretability of Data-Driven Models for Additive Manufacturing Processes Using Clusterwise Regression," Mathematics, MDPI, vol. 12(16), pages 1-18, August.
    5. Roy Cerqueti & Antonio Iovanella & Raffaele Mattera, 2024. "Clustering networked funded European research activities through rank-size laws," Annals of Operations Research, Springer, vol. 342(3), pages 1707-1735, November.
    6. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.
    7. Luis Lorenzo & Javier Arroyo, 2023. "Online risk-based portfolio allocation on subsets of crypto assets applying a prototype-based clustering algorithm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-40, December.
    8. Vincenzo Basile & Massimiliano Giacalone & Paolo Carmelo Cozzucoli, 2022. "The Impacts of Bibliometrics Measurement in the Scientific Community A Statistical Analysis of Multiple Case Studies," Review of European Studies, Canadian Center of Science and Education, vol. 14(3), pages 1-10, November.

  7. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.

    Cited by:

    1. Massimiliano Giacalone & Demetrio Panarello, 2022. "A Nonparametric Approach for Testing Long Memory in Stock Returns’ Higher Moments," Mathematics, MDPI, vol. 10(5), pages 1-21, February.
    2. Andrew Spurr & Marcel Ausloos, 2020. "Challenging Practical Features of Bitcoin by the Main Altcoins," Papers 2101.03891, arXiv.org.
    3. Leonardo Ieracitano Vieira & Márcio Poletti Laurini, 2023. "Time-varying higher moments in Bitcoin," Digital Finance, Springer, vol. 5(2), pages 231-260, June.
    4. Kurosaki, Tetsuo & Kim, Young Shin, 2022. "Cryptocurrency portfolio optimization with multivariate normal tempered stable processes and Foster-Hart risk," Finance Research Letters, Elsevier, vol. 45(C).
    5. Theophilos Papadimitriou & Periklis Gogas & Athanasios Fotios Athanasiou, 2022. "Forecasting Bitcoin Spikes: A GARCH-SVM Approach," Forecasting, MDPI, vol. 4(4), pages 1-15, September.
    6. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2022. "Semi-nonparametric risk assessment with cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 59(C).
    7. Manavi, Seyed Alireza & Jafari, Gholamreza & Rouhani, Shahin & Ausloos, Marcel, 2020. "Demythifying the belief in cryptocurrencies decentralized aspects. A study of cryptocurrencies time cross-correlations with common currencies, commodities and financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    8. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.
    9. Amiri , Hossein & Najafi Nejad , Mahmood & Mousavi , Seyede Mohadese, 2021. "Estimation of Value at Risk (VaR) Based On Lévy-GARCH Models: Evidence from Tehran Stock Exchange," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(2), pages 165-186, June.
    10. Giulio Mattera & Gianfranco Piscopo & Maria Longobardi & Massimiliano Giacalone & Luigi Nele, 2024. "Improving the Interpretability of Data-Driven Models for Additive Manufacturing Processes Using Clusterwise Regression," Mathematics, MDPI, vol. 12(16), pages 1-18, August.
    11. Nick James & Max Menzies, 2023. "Collective dynamics, diversification and optimal portfolio construction for cryptocurrencies," Papers 2304.08902, arXiv.org, revised Jun 2023.
    12. Deniz Erer, 2023. "The Impact of News Related Covid-19 on Exchange Rate Volatility:A New Evidence From Generalized Autoregressive Score Model," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(38), pages 105-126, June.
    13. James, Nick & Menzies, Max & Gottwald, Georg A., 2022. "On financial market correlation structures and diversification benefits across and within equity sectors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    14. Nick James & Max Menzies, 2023. "An exploration of the mathematical structure and behavioural biases of 21st century financial crises," Papers 2307.15402, arXiv.org, revised Sep 2023.
    15. James, Nick & Menzies, Max, 2023. "An exploration of the mathematical structure and behavioural biases of 21st century financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    16. Kumar, Ashish & Iqbal, Najaf & Mitra, Subrata Kumar & Kristoufek, Ladislav & Bouri, Elie, 2022. "Connectedness among major cryptocurrencies in standard times and during the COVID-19 outbreak," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    17. Yin, Libo & Nie, Jing & Han, Liyan, 2021. "Understanding cryptocurrency volatility: The role of oil market shocks," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 233-253.
    18. Klender Cortez & Martha del Pilar Rodríguez-García & Samuel Mongrut, 2020. "Exchange Market Liquidity Prediction with the K-Nearest Neighbor Approach: Crypto vs. Fiat Currencies," Mathematics, MDPI, vol. 9(1), pages 1-15, December.
    19. Tetsuo Kurosaki & Young Shin Kim, 2020. "Cryptocurrency portfolio optimization with multivariate normal tempered stable processes and Foster-Hart risk," Papers 2010.08900, arXiv.org.
    20. Fung, Kennard & Jeong, Jiin & Pereira, Javier, 2022. "More to cryptos than bitcoin: A GARCH modelling of heterogeneous cryptocurrencies," Finance Research Letters, Elsevier, vol. 47(PA).
    21. José Antonio Núñez-Mora & Roberto Joaquín Santillán-Salgado & Mario Iván Contreras-Valdez, 2022. "COVID Asymmetric Impact on the Risk Premium of Developed and Emerging Countries’ Stock Markets," Mathematics, MDPI, vol. 10(9), pages 1-36, April.
    22. Wu, Xinyu & Yin, Xuebao & Umar, Zaghum & Iqbal, Najaf, 2023. "Volatility forecasting in the Bitcoin market: A new proposed measure based on the VS-ACARR approach," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    23. Nick James, 2021. "Evolutionary correlation, regime switching, spectral dynamics and optimal trading strategies for cryptocurrencies and equities," Papers 2112.15321, arXiv.org, revised Mar 2022.
    24. Esparcia, Carlos & Escribano, Ana & Jareño, Francisco, 2023. "Did cryptomarket chaos unleash Silvergate's bankruptcy? investigating the high-frequency volatility and connectedness behind the collapse," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).

Articles

  1. Mattera, Raffaele & Franses, Philip Hans, 2023. "Are African business cycles synchronized? Evidence from spatio-temporal modeling," Economic Modelling, Elsevier, vol. 128(C).

    Cited by:

    1. Caterina Morelli & Simone Boccaletti & Paolo Maranzano & Philipp Otto, 2024. "Multidimensional spatiotemporal clustering -- An application to environmental sustainability scores in Europe," Papers 2405.20191, arXiv.org.
    2. Caterina Morelli & Simone Boccaletti & Paolo Maranzano & Philipp Otto, 2025. "Multidimensional Spatiotemporal Clustering – An Application to Environmental Sustainability Scores in Europe," Environmetrics, John Wiley & Sons, Ltd., vol. 36(2), March.

  2. Raffaele Mattera & Michelangelo Misuraca & Maria Spano & Germana Scepi, 2023. "Mixed frequency composite indicators for measuring public sentiment in the EU," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2357-2382, June.

    Cited by:

    1. Matheus Pereira Libório & Alexandre Magno Alvez Diniz & Douglas Alexandre Gomes Vieira & Petr Iakovlevitch Ekel, 2024. "Subjective–Objective Method of Maximizing the Average Variance Extracted From Sub-indicators in Composite Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 175(2), pages 613-637, November.
    2. Ahelegbey, Daniel Felix & Celani, Alessandro & Cerchiello, Paola, 2024. "Measuring the impact of the EU health emergency response authority on the economic sectors and the public sentiment," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).

  3. Raffaele Mattera, 2023. "Forecasting binary outcomes in soccer," Annals of Operations Research, Springer, vol. 325(1), pages 115-134, June.

    Cited by:

    1. 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.
    2. Llorenç Badiella & Pedro Puig & Carlos Lago-Peñas & Martí Casals, 2023. "Influence of Red and Yellow cards on team performance in elite soccer," Annals of Operations Research, Springer, vol. 325(1), pages 149-165, June.
    3. Fan Xiaoyu & Wang Shasha, 2024. "Evaluating the pinnacle of football match key statistics as in‐play information for determining the match outcome of Europe's foremost leagues," Social Science Quarterly, Southwestern Social Science Association, vol. 105(3), pages 775-799, May.

  4. Raffaele Mattera & Fabrizio Di Sciorio & Juan E. Trinidad-Segovia & Sameh S. Askar, 2022. "A Composite Index for Measuring Stock Market Inefficiency," Complexity, Hindawi, vol. 2022, pages 1-13, January.

    Cited by:

    1. Angelini, Daniele & Bianchi, Sergio, 2023. "Nonlinear biases in the roughness of a Fractional Stochastic Regularity Model," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).

  5. Juan E. Trinidad Segovia & Fabrizio Di Sciorio & Raffaele Mattera & Maria Spano & Wei Xing Zhou, 2022. "A Bibliometric Analysis on Agent-Based Models in Finance: Identification of Community Clusters and Future Research Trends," Complexity, Hindawi, vol. 2022, pages 1-11, September.

    Cited by:

    1. Emiliano Alvarez & Volker Grimm, 2024. "The added value of using the ODD Protocol for agent-based modeling in Economics: go for it!," Working Papers 307, Red Nacional de Investigadores en Economía (RedNIE).
    2. Pastushkov, A., 2025. "Evolutionary and agent-based computational finance: The new paradigms for asset pricing," Journal of the New Economic Association, New Economic Association, vol. 66(1), pages 196-222.

  6. Giacalone, Massimiliano & Mattera, Raffaele & Nissi, Eugenia, 2022. "Well-being analysis of Italian provinces with spatial principal components," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).

    Cited by:

    1. Fernández-Avilés, Gema & Mattera, Raffaele & Scepi, Germana, 2024. "Factor-Augmented Autoregressive Neural Network to forecast NOx in the city of Madrid," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    2. Paolo Postiglione & Alfredo Cartone & M. Simona Andreano & Roberto Benedetti, 2023. "Constrained optimization for addressing spatial heterogeneity in principal component analysis: an application to composite indicators," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(5), pages 1539-1561, December.
    3. Aldieri, Luigi & Gatto, Andrea & Vinci, Concetto Paolo, 2024. "Impact of environmental, energy and business efficiency on CO2 emissions: A composite indicator for emerging Asia-Pacific markets," Applied Energy, Elsevier, vol. 368(C).
    4. Kou, Po & Shi, Jianhua, 2024. "Dynamic evolution of China's government environmental regulation capability and its impact on the coupling coordinated development of the economy-environment," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).

  7. Massimiliano Giacalone & Raffaele Mattera & Eugenia Nissi, 2020. "Economic indicators forecasting in presence of seasonal patterns: time series revision and prediction accuracy," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 67-84, February.

    Cited by:

    1. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.
    2. Fernández-Avilés, Gema & Mattera, Raffaele & Scepi, Germana, 2024. "Factor-Augmented Autoregressive Neural Network to forecast NOx in the city of Madrid," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    3. Kertlly de Medeiros, Rennan & da Nóbrega Besarria, Cássio & Pitta de Jesus, Diego & Phillipe de Albuquerquemello, Vinicius, 2022. "Forecasting oil prices: New approaches," Energy, Elsevier, vol. 238(PC).

  8. Massimiliano Giacalone & Raffaele Mattera & Carlo Cusatelli, 2018. "Do sustainable well-being indicators affect GDP? Evidence from a longitudinal study in Italy based on BES approach," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 72(3), pages 125-148, July-Sept.

    Cited by:

    1. Giacalone, Massimiliano & Mattera, Raffaele & Nissi, Eugenia, 2022. "Well-being analysis of Italian provinces with spatial principal components," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).

  9. Massimiliano Giacalone & Demetrio Panarello & Raffaele Mattera, 2018. "Multicollinearity in regression: an efficiency comparison between Lp-norm and least squares estimators," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1831-1859, July.

    Cited by:

    1. Claudia García-García & Catalina B. García-García & Román Salmerón, 2021. "Confronting collinearity in environmental regression models: evidence from world data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 895-926, September.
    2. Al Kez, Dlzar & Foley, Aoife & Abdul, Zrar Khald & Del Rio, Dylan Furszyfer, 2024. "Energy poverty prediction in the United Kingdom: A machine learning approach," Energy Policy, Elsevier, vol. 184(C).
    3. Massimiliano Giacalone & Demetrio Panarello, 2022. "A Nonparametric Approach for Testing Long Memory in Stock Returns’ Higher Moments," Mathematics, MDPI, vol. 10(5), pages 1-21, February.
    4. Alexander Robitzsch, 2020. "L p Loss Functions in Invariance Alignment and Haberman Linking with Few or Many Groups," Stats, MDPI, vol. 3(3), pages 1-38, August.
    5. Panarello, Demetrio, 2021. "Economic insecurity, conservatism, and the crisis of environmentalism: 30 years of evidence," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
    6. Alexander Robitzsch, 2025. "Comparing Robust Haberman Linking and Invariance Alignment," Stats, MDPI, vol. 8(1), pages 1-15, January.
    7. Massimiliano Giacalone & Raffaele Mattera & Eugenia Nissi, 2020. "Economic indicators forecasting in presence of seasonal patterns: time series revision and prediction accuracy," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 67-84, February.
    8. Panarello, Demetrio & Gatto, Andrea, 2023. "Decarbonising Europe – EU citizens’ perception of renewable energy transition amidst the European Green Deal," Energy Policy, Elsevier, vol. 172(C).
    9. Jinse Jacob & R. Varadharajan, 2023. "Simultaneous raise regression: a novel approach to combating collinearity in linear regression models," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(5), pages 4365-4386, October.
    10. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.
    11. Giulio Mattera & Gianfranco Piscopo & Maria Longobardi & Massimiliano Giacalone & Luigi Nele, 2024. "Improving the Interpretability of Data-Driven Models for Additive Manufacturing Processes Using Clusterwise Regression," Mathematics, MDPI, vol. 12(16), pages 1-18, August.
    12. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.
    13. Vincenzo Basile & Massimiliano Giacalone & Paolo Carmelo Cozzucoli, 2022. "The Impacts of Bibliometrics Measurement in the Scientific Community A Statistical Analysis of Multiple Case Studies," Review of European Studies, Canadian Center of Science and Education, vol. 14(3), pages 1-10, November.
    14. Panarello, Demetrio & Tassinari, Giorgio, 2022. "One year of COVID-19 in Italy: are containment policies enough to shape the pandemic pattern?," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    15. Gennaro Punzo & Demetrio Panarello & Rosalia Castellano, 2022. "Sustainable urban mobility: evidence from three developed European countries," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(5), pages 3135-3157, October.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ETS: Econometric Time Series (2) 2020-05-11 2023-04-17. Author is listed
  2. NEP-FMK: Financial Markets (2) 2023-04-17 2023-12-11. Author is listed
  3. NEP-FOR: Forecasting (2) 2023-04-17 2023-12-11. Author is listed
  4. NEP-BIG: Big Data (1) 2023-12-11. Author is listed
  5. NEP-CMP: Computational Economics (1) 2023-12-11. Author is listed
  6. NEP-DES: Economic Design (1) 2023-04-17. Author is listed
  7. NEP-ECM: Econometrics (1) 2023-04-17. Author is listed
  8. NEP-GEN: Gender (1) 2020-05-11. Author is listed
  9. NEP-MAC: Macroeconomics (1) 2023-04-17. Author is listed
  10. NEP-NET: Network Economics (1) 2023-04-17. Author is listed
  11. NEP-PAY: Payment Systems and Financial Technology (1) 2020-05-11. Author is listed
  12. NEP-RMG: Risk Management (1) 2023-04-17. Author is listed

Corrections

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

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

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

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

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

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