Francesco Pattarin
Personal Details
First Name: | Francesco |
Middle Name: | |
Last Name: | Pattarin |
Suffix: | |
RePEc Short-ID: | ppa329 |
| |
http://personale.unimore.it/Rubrica/dettaglio/pattarin | |
Affiliation
Centro Studi di Banca e Finanza (CEFIN)
Dipartimento di Economia "Marco Biagi"
Università degli Studi di Modena e Reggio Emilia
Modena, Italyhttp://www.cefin.unimore.it/
RePEc:edi:cbmodit (more details at EDIRC)
Research output
Jump to: ArticlesArticles
- Francesco Pattarin & Stefano Cosma, 2012. "Psychological determinants of consumer credit: the role of attitudes," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 4(2), pages 113-129, November.
- Riccardo Ferretti & Francesco Pattarin, 2005. "Le reazioni di mercato alle operazioni di raggruppamento e frazionamento: il caso italiano," Banca Impresa Società, Società editrice il Mulino, issue 3, pages 401-444.
- Pattarin, Francesco & Paterlini, Sandra & Minerva, Tommaso, 2004. "Clustering financial time series: an application to mutual funds style analysis," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 353-372, September.
- Michele Lalla & Francesco Pattarin, 2001.
"Unemployment Duration: An Analysis of Incomplete, Completed, and Multiple Spells in Emilia-Romagna,"
Quality & Quantity: International Journal of Methodology, Springer, vol. 35(2), pages 203-230, May.
RePEc:taf:apfiec:v:14:y:2004:i:18:p:1281-1289 is not listed on IDEAS
Citations
Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.Articles
- Francesco Pattarin & Stefano Cosma, 2012.
"Psychological determinants of consumer credit: the role of attitudes,"
Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 4(2), pages 113-129, November.
Cited by:
- A. Smurygina & M. Gagarina & А. Смурыгина & М. Гагарина, 2016. "Ограниченная Рациональность: Психологический Анализ Поведения Должников // Bounded Rationality: Psychological Analysis Of Debt Behaviour," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 4(1), pages 75-84.
- Boto Ferreira, Mário & Costa Pinto, Diego & Maurer Herter, Márcia & Soro, Jerônimo & Vanneschi, Leonardo & Castelli, Mauro & Peres, Fernando, 2021. "Using artificial intelligence to overcome over-indebtedness and fight poverty," Journal of Business Research, Elsevier, vol. 131(C), pages 411-425.
- Pattarin, Francesco & Paterlini, Sandra & Minerva, Tommaso, 2004.
"Clustering financial time series: an application to mutual funds style analysis,"
Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 353-372, September.
Cited by:
- Winker, Peter & Gilli, Manfred, 2004. "Applications of optimization heuristics to estimation and modelling problems," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 211-223, September.
- Alonso, A.M. & Berrendero, J.R. & Hernandez, A. & Justel, A., 2006. "Time series clustering based on forecast densities," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 762-776, November.
- R. Gargano & E. Otranto, 2013.
"Financial Clustering in Presence of Dominant Markets,"
Working Paper CRENoS
201318, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
- Edoardo Otranto & Romana Gargano, 2015. "Financial clustering in presence of dominant markets," 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. 9(3), pages 315-339, September.
- Victor DeMiguel & Javier Gil-Bazo & Francisco J. Nogales & André A. P. Santos, 2021.
"Can machine learning help to select portfolios of mutual funds?,"
Economics Working Papers
1772, Department of Economics and Business, Universitat Pompeu Fabra.
- Victor DeMiguel & Javier Gil-Bazo & Francisco J. Nogales & André A. P. Santos, 2021. "Can Machine Learning Help to Select Portfolios of Mutual Funds?," Working Papers 1245, Barcelona School of Economics.
- Bracewell Paul J & Farhadieh Farinaz & Jowett Clint A & Forbes Don G. R. & Meyer Denny H, 2009. "Was Bradman Denied His Prime?," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(4), pages 1-26, October.
- Fabrizio Durante & Roberta Pappadà & Nicola Torelli, 2015. "Clustering of time series via non-parametric tail dependence estimation," Statistical Papers, Springer, vol. 56(3), pages 701-721, August.
- Takaya Fukui & Seisho Sato & Akihiko Takahashi, 2017. "Style analysis with particle filtering and generalized simulated annealing," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 4(02n03), pages 1-29, June.
- Liu, Shen & Maharaj, Elizabeth Ann & Inder, Brett, 2014. "Polarization of forecast densities: A new approach to time series classification," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 345-361.
- Juan C. Duque & Xinyue Ye & David C. Folch, 2015. "spMorph: An exploratory space-time analysis tool for describing processes of spatial redistribution," Papers in Regional Science, Wiley Blackwell, vol. 94(3), pages 629-651, August.
- Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.
- DeMiguel, Victor & Gil-Bazo, Javier & Nogales, Francisco J. & Santos, André A.P., 2023. "Machine learning and fund characteristics help to select mutual funds with positive alpha," Journal of Financial Economics, Elsevier, vol. 150(3).
- James Ming Chen & Mira Zovko & Nika Šimurina & Vatroslav Zovko, 2021. "Fear in a Handful of Dust: The Epidemiological, Environmental, and Economic Drivers of Death by PM 2.5 Pollution," IJERPH, MDPI, vol. 18(16), pages 1-59, August.
- 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.
- Maharaj, Elizabeth A. & Alonso, Andres M., 2007. "Discrimination of locally stationary time series using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 879-895, October.
- Firat, Aykut & Chatterjee, Sangit & Yilmaz, Mustafa, 2007. "Genetic clustering of social networks using random walks," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6285-6294, August.
- Jin Zhang & Dietmar Maringer, 2010. "Asset Allocation under Hierarchical Clustering," Working Papers 036, COMISEF.
- Liu, Shen & Maharaj, Elizabeth Ann, 2013. "A hypothesis test using bias-adjusted AR estimators for classifying time series in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 60(C), pages 32-49.
- E. Otranto, 2008.
"Clustering Heteroskedastic Time Series by Model-Based Procedures,"
Working Paper CRENoS
200801, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
- Otranto, Edoardo, 2008. "Clustering heteroskedastic time series by model-based procedures," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4685-4698, June.
- 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.
- Giovanni De Luca & Paola Zuccolotto, 2011. "A tail dependence-based dissimilarity measure for financial time series clustering," 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. 5(4), pages 323-340, December.
- De Luca Giovanni & Zuccolotto Paola, 2017. "A double clustering algorithm for financial time series based on extreme events," Statistics & Risk Modeling, De Gruyter, vol. 34(1-2), pages 1-12, June.
- Stephanos Papadamou & Nikolaos A. Kyriazis & Lydia Mermigka, 2017. "Japanese Mutual Funds before and after the Crisis Outburst: A Style- and Performance-Analysis," IJFS, MDPI, vol. 5(1), pages 1-20, March.
- Pierpaolo D’Urso & Livia Giovanni & Riccardo Massari, 2021. "Trimmed fuzzy clustering of financial time series based on dynamic time warping," Annals of Operations Research, Springer, vol. 299(1), pages 1379-1395, April.
- Dhagash Mehta & Dhruv Desai & Jithin Pradeep, 2020. "Machine Learning Fund Categorizations," Papers 2006.00123, arXiv.org.
- Pinar OKAN GOKTEN & Furkan BASER & Soner GOKTEN, 2017. "Using fuzzy c-means clustering algorithm in financial health scoring," The Audit Financiar journal, Chamber of Financial Auditors of Romania, vol. 15(147), pages 385-385.
- E. Otranto, 2011. "Classification of Volatility in Presence of Changes in Model Parameters," Working Paper CRENoS 201113, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
- F. Lisi & E. Otranto, 2008. "Clustering Mutual Funds by Return and Risk Levels," Working Paper CRENoS 200813, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
- James Ming Chen & Mobeen Ur Rehman, 2021. "A Pattern New in Every Moment: The Temporal Clustering of Markets for Crude Oil, Refined Fuels, and Other Commodities," Energies, MDPI, vol. 14(19), pages 1-58, September.
- Chen, James Ming & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2021. "Clustering commodity markets in space and time: Clarifying returns, volatility, and trading regimes through unsupervised machine learning," Resources Policy, Elsevier, vol. 73(C).
- Mahmoudi, Mohammad Reza, 2021. "A computational technique to classify several fractional Brownian motion processes," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
- Corduas, Marcella & Piccolo, Domenico, 2008. "Time series clustering and classification by the autoregressive metric," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1860-1872, January.
- Michele Lalla & Francesco Pattarin, 2001.
"Unemployment Duration: An Analysis of Incomplete, Completed, and Multiple Spells in Emilia-Romagna,"
Quality & Quantity: International Journal of Methodology, Springer, vol. 35(2), pages 203-230, May.
Cited by:
- Michele Lalla & Tommaso Minerva, 2001. "Duration models and neural networks to analyse unemployment spells," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 199-216.
- Chiara Gigliarano & Francesco Chelli, 2016. "Measuring inter-temporal intragenerational mobility: an application to the Italian labour market," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(1), pages 89-102, January.
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