Massimiliano Giacalone

Personal Details

First Name:	Massimiliano
Middle Name:
Last Name:	Giacalone
Suffix:
RePEc Short-ID:	pgi298
	[This author has chosen not to make the email address public]
	https://www.docenti.unina.it/massimiliano.giacalone
	maxgiacit@yahoo.it

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)

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. 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.
      • Andrew Spurr & Marcel Ausloos, 2021. "Challenging practical features of Bitcoin by the main altcoins," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(5), pages 1541-1559, October.
   3. 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.
   4. 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).
   5. 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.
   6. 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).
   7. Leonardo Ieracitano Vieira & Márcio Poletti Laurini, 2023. "Time-varying higher moments in Bitcoin," Digital Finance, Springer, vol. 5(2), pages 231-260, June.
   8. 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).
   9. 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).
   10. Theophilos Papadimitriou & Periklis Gogas & Athanasios Fotios Athanasiou, 2022. "Forecasting Bitcoin Spikes: A GARCH-SVM Approach," Forecasting, MDPI, vol. 4(4), pages 1-15, September.
   11. 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.
   12. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2022. "Semi-nonparametric risk assessment with cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 59(C).
   13. 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.
   14. Tetsuo Kurosaki & Young Shin Kim, 2020. "Cryptocurrency portfolio optimization with multivariate normal tempered stable processes and Foster-Hart risk," Papers 2010.08900, arXiv.org.
   15. 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).
   16. 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).
   17. 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.
   18. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.
   19. 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.
   20. 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.
   21. Nick James & Max Menzies, 2023. "Collective dynamics, diversification and optimal portfolio construction for cryptocurrencies," Papers 2304.08902, arXiv.org, revised Jun 2023.
   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).

2. Carlo Capuano & Massimiliano Giacalone, 2018. "Measuring Organized Crime: Statistical Indicators and Economics Aspects," EERI Research Paper Series EERI RP 2018/11, Economics and Econometrics Research Institute (EERI), Brussels.

   Cited by:

   1. Giovanni Bernardo & Irene Brunetti & Mehmet Pinar & Thanasis Stengos, 2021. "Measuring the presence of organized crime across Italian provinces: a sensitivity analysis," European Journal of Law and Economics, Springer, vol. 51(1), pages 31-95, February.

Articles

1. Massimiliano Giacalone & Vito Santarcangelo & Vincenzo Donvito & Oriana Schiavone & Emilio Massa, 2021. "Big data for corporate social responsibility: blockchain use in Gioia del Colle DOP," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(6), pages 1945-1971, December.

   Cited by:

   1. Giuseppe Varavallo & Giuseppe Caragnano & Fabrizio Bertone & Luca Vernetti-Prot & Olivier Terzo, 2022. "Traceability Platform Based on Green Blockchain: An Application Case Study in Dairy Supply Chain," Sustainability, MDPI, vol. 14(6), pages 1-14, March.
   2. Maria Krechowicz & Katarzyna Kiliańska, 2021. "Risk and Opportunity Assessment Model for CSR Initiatives in the Face of Coronavirus," Sustainability, MDPI, vol. 13(11), pages 1-22, May.

2. 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. 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).
   2. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.

3. Giacalone, Massimiliano & Nissi, Eugenia & Cusatelli, Carlo, 2020. "Dynamic efficiency evaluation of Italian judicial system using DEA based Malmquist productivity indexes," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).

   Cited by:

   1. Tingli Liu & Xiao Chen & Jianing Liu, 2023. "Economic Policy Uncertainty and Enterprise Financing Efficiency: Evidence from China," Sustainability, MDPI, vol. 15(11), pages 1-27, May.
   2. Helu Xiao & Na Wang & Shanping Wang, 2023. "Dynamic sustainability assessment of poverty alleviation in China: evidence from both novel non-convex global two-stage DEA and Malmquist productivity index," Operational Research, Springer, vol. 23(2), pages 1-40, June.
   3. Xiaoqing Chen & Kristiaan Kerstens & Mike Tsionas, 2023. "Does Productivity Change at All in Swedish District Courts? Empirical Analysis Focusing on Horizontal Mergers," Working Papers 2023-EQM-03, IESEG School of Management.
      • Xiaoqing Chen & Kristiaan Kerstens & Mike Tsionas, 2024. "Does productivity change at all in Swedish district courts? Empirical analysis focusing on horizontal mergers," Post-Print hal-04548513, HAL.
      • Chen, Xiaoqing & Kerstens, Kristiaan & Tsionas, Mike, 2024. "Does productivity change at all in Swedish district courts? Empirical analysis focusing on horizontal mergers," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
   4. Zufeng Shang & Fenglai Wang & Xu Yang, 2022. "The Efficiency of the Chinese Prefabricated Building Industry and Its Influencing Factors: An Empirical Study," Sustainability, MDPI, vol. 14(17), pages 1-25, August.
   5. Aparicio, Juan & Santín, Daniel, 2024. "Global and local technical changes: A new decomposition of the Malmquist productivity index using virtual units," Economic Modelling, Elsevier, vol. 134(C).
   6. Yanqi Han & Minghui Hua & Malan Huang & Jin Li & Shirui Wang, 2022. "Dynamic Transition and Convergence Trend of the Innovation Efficiency among Companies Listed on the Growth Enterprise Market in the Yangtze River Economic Belt—Empirical Analysis Based on DEA—Malmquis," Sustainability, MDPI, vol. 14(9), pages 1-28, April.
   7. Giuseppe Arcuri & Nadine Levratto & Marianna Succurro, 2023. "Does commercial court organisation affect firms’ bankruptcy rate? evidence from the french judicial reform," European Journal of Law and Economics, Springer, vol. 55(3), pages 573-601, June.
   8. 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. Xiaoqing Chen & Kristiaan Kerstens & Qingyuan Zhu, 2021. "Exploring Horizontal Mergers in Swedish District Courts Using Convex and Nonconvex Technologies: Usefulness of a Conservative Approach," Working Papers 2021-EQM-05, IESEG School of Management.
   10. Chen, Jiabin & Wen, Shaobo & Liu, Yuchen, 2022. "Research on the efficiency of the mining industry in China from the perspective of time and space," Resources Policy, Elsevier, vol. 75(C).
   11. Jonas Månsson & Christian Andersson & Fredrik Bonander, 2022. "What lessons can be learned from cost efficiency? The case of Swedish district courts," European Journal of Law and Economics, Springer, vol. 54(3), pages 431-451, December.
   12. Gupta, Maansi & Bolia, Nomesh B., 2024. "Factors affecting efficient discharge of judicial functions: Insights from Indian courts," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).

4. Eugenia Nissi & Massimiliano Giacalone & Carlo Cusatelli, 2019. "The Efficiency of the Italian Judicial System: A Two Stage Data Envelopment Analysis Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 395-407, November.

   Cited by:

   1. Giacalone, Massimiliano & Nissi, Eugenia & Cusatelli, Carlo, 2020. "Dynamic efficiency evaluation of Italian judicial system using DEA based Malmquist productivity indexes," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
   2. 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).
   3. Anirban Pal & Piyush Kumar Singh, 2021. "Do socially motivated self‐help groups perform better? Exploring determinants of micro‐credit groups’ performance in Eastern India," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 92(1), pages 119-146, March.
   4. 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).
   5. Casolani, Nicola & Nissi, Eugenia & Giampaolo, Antonio & Liberatore, Lolita, 2021. "Evaluating the effects of European support measures for Italian organic farms," Land Use Policy, Elsevier, vol. 102(C).
   6. Francesco Aiello & Graziella Bonanno & Francesco Foglia, 2021. "On The Heterogeneity In The Judicial Efficiency Literature: A Meta-Regression Analysis," Working Papers 202102, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
   7. Gupta, Maansi & Bolia, Nomesh B., 2024. "Factors affecting efficient discharge of judicial functions: Insights from Indian courts," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
   8. Elisa Bonollo & Costanza Di Fabio & Lorenzo Leto & Paola Ramassa, 2024. "La rendicontazione economico-finanziaria degli Uffici giudiziari: un?analisi esplorativa," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2024(2), pages 115-139.

5. Cerqueti, Roy & Giacalone, Massimiliano & Panarello, Demetrio, 2019. "A Generalized Error Distribution Copula-based method for portfolios risk assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 687-695.

   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. 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).
   3. 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.
   4. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.
   5. 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.
   6. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.
   7. Nick James & Max Menzies, 2023. "Collective dynamics, diversification and optimal portfolio construction for cryptocurrencies," Papers 2304.08902, arXiv.org, revised Jun 2023.
   8. 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.

6. 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).

7. Carlo Cusatelli & Massimiliano Giacalone, 2018. "Evaluating the Judicial Activity: A Proposal of Indicators and Analyses of Criminal Burden," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 138(2), pages 725-746, July.

   Cited by:

   1. Giacalone, Massimiliano & Nissi, Eugenia & Cusatelli, Carlo, 2020. "Dynamic efficiency evaluation of Italian judicial system using DEA based Malmquist productivity indexes," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).

8. 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. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.
   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. 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.
   9. 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).
   10. 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).
   11. 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.
   12. 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.
   13. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.
   14. 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.

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 2 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 (1) 2020-05-11
2. NEP-GEN: Gender (1) 2020-05-11
3. NEP-LAW: Law and Economics (1) 2018-07-30
4. NEP-PAY: Payment Systems and Financial Technology (1) 2020-05-11

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, Massimiliano Giacalone 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.