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Pubblicazioni

Main Publications in International Journals

  1. Bernard, C., Caporin, M., Maillet, B. and Zhang, X., Omega compatibility: a meta-analysis, Compuational Economics, forthcoming;
  2. Caporin, M., Shchepeleva, M., and Stolbov, M., What drives the expansion of research on banking crises? Cross-country evidence, Applied Economics, forthcoming;
  3. Caporin, M., The role of jumps in realized volatility modeling and forecasting, Journal of Financial Econometrics, forthcoming;
  4. Billio, M., Caporin, M., Frattarolo, L., and Pelizzon, L., Networks in risk spillovers: a multivariate GARCH perspective, Econometrics and Statistics, forthcoming;
  5. Billé, A. and Caporin, M., Impact of COVID-19 on Financial Returns: A Spatial Dynamic Panel Data Model with Random Effects, Journal of Spatial Econometrics, forthcoming;
  6. Caporin, M. and Poli, F., 2022, News and intraday jumps: evidence from regularization and class imbalance”, North American Journal of Economics and Finance, 62, 101743, 1016/j.najef.2022.101743;
  7. Caporin, M., and Costola, M., 2022, Time-varying Granger causality tests in the energy markets: A study on the DCC-MGARCH Hong test, Energy Economics, 111, 106088, 1016/j.eneco.2022.106088;
  8. Bonaldo, C., Caporin, M., and Fontini, F., 2022, The relationship between day-ahead and futures prices in the electricity markets: an empirical analysis on Italy, France, Germany and Switzerland, Energy Economics, 110, 105977, 1016/j.eneco.2022.105977;
  9. Caporin, M., Jimenez-Martin, J.A. and Jorcano, L., Measuring systemic risk during the COVID-19 period: a TALIS3 approach, 2022, Finance Research Letters, 46, 102304, 1016/j.frl.2021.102304;
  10. Yu, S., Liu, J., and Caporin, M., The effect of renewable energy development on China’s energy intensity: Evidence from linear and nonlinear analyses, 2022, Journal of Cleaner Production, 350, 1016/j.jclepro.2022.131505;
  11. Caporin, M., Fontini, F., and Santucci de Magistris, P., 2022, The long-run relationship between the Italian day-ahead and balancing electricity prices, Energy Systems, 13, 111-136, 1007/s12667-020-00392-x;
  12. Bonaccolto, G., Caporin, M. and Maillet, B., 2022, Dynamic Large Financial Networks via Conditional Expected Shortfalls, European Journal of Operational Research, 298, 332-336, 1016/j.ejor.2021.06.037;
  13. Caporin, M., Costola, M., Garibal, J., and Maillet, B., 2022, Systemic Risk and Severe Real Economy Downturns: A Sparse and Targeted analysis, Journal of Banking and Finance, 134, 106339, 1016/j.jbankfin.2021.106339;
  14. Caporin, M., Costola, M., Khalifa, A., and Hammoudeh, S., 2021, Systemic risk for financial institutions of major petroleum-based economies: The role of oil, The Energy Journal, 42(6), 247-274, 5547/01956574.42.6.AKHA;
  15. Liu, S., Caporin, M., and Paterlini, S., 2021, Dynamic network analysis of North American financial institutions, Finance Research Letters, 42, 101921, 1016/j.frl.2021.101921;
  16. Al-Yahyaee, K., Caporin, M., Kang, S.H., Ko, H., and Mensi, W., 2021, Is the Korean housing market following Gangnam style? Empirical Economics, 61, 2041-2072, 1007/s00181-020-01931-2;
  17. Bonaccolto, G., Caporin, M., and Zambon, N., Multiple co-jumps in the cross-section of US equities and the identification of system(at)ic movements, 2021, European Journal of Finance, 27(11), 1098-1116, 1080/1351847X.2020.1856704;
  18. Caporin, M., Jimenez-Martin, J.A. and Jorcano, L., 2021, TrAffic LIght System for Systemic Stress: TALIS3, North American Journal of Economics and Finance, 57, July 2021, 101449, 1016/j.najef.2021.101449;
  19. Caporin, M., Gupta, R., and Ravazzolo, F., 2021, Contagion between Real Estate and Financial Markets: A Bayesian Quantile-on-Quantile Approach, North American Journal of Economics and Finance, 55, January 2021, 101347, 1016/j.najef.2020.101347;
  20. Naeem, M.A., Arif, M., Hasan, M., Caporin, M., and Shahzad, S.J.H., 2021, Asymmetric and time-frequency spillovers among commodities using high-frequency data, Resources Policy, 70, March 2021, 101958, 1016/j.resourpol.2020.101958;
  21. Caporin, M., and Shahzad, S.J.H., On the volatilities of tourism sotcks and oil, Annals of Tourism Research, 81, March 2020, 102705, 1016/j.annals.2019.03.011;
  22. Caporin, M. and Malik, F., 2020, Do Structural Breaks in Volatility cause Spurious Volatility Transmission? Journal of Empirical Finance, 55, 60-82, 1016/j.jempfin.2019.11.002;
  23. Caporin, M. and Rodriguez Caballero, C.V., 2019, A multilevel factor approach for the analysis of CDS commonality and risk contribution, Journal of International Financial Markets Institutions and Money, 63, November 2019, 101144, 1016/j.intfin.2019.101144;
  24. Bonaccolto, G., Caporin, M., and Paterlini, S., 2019, Decomposing and backtesting a flexible specification for CoVaR, Journal of Banking and Finance, 108, November 2019, 105659, 1016/j.jbankfin.2019.105659;
  25. Bonaccolto, G., Caporin, M., and Panzica, R., 2019, Estimation and model-based combination of causality networks among large US Banks and Insurance companies, Journal of Empirical Finance, 54, 1-21, 1016/j.jempfin.2019.08.008;
  26. Caporin, M., Natvik, G., Ravazzolo, F., and Santucci de Magistris, P., 2019, The Bank-Sovereign Nexus: Evidence from a non-Bailout Episode, Journal of Empirical Finance, 53, 181-196, 1016/j.jempfin.2019.07.001;
  27. Caporin, M., Corazzini, L., and Costola, M., 2019, Measuring the Behavioural Component of the S&P 500 and Its Relationship to Financial Stress and Aggregated Earnings Surprises, British Journal of Management, 30, 712-729, 1111/1467-8551.12285;
  28. Caporin, M., Fontini, F., and Talebbeydokhti, E., 2019, Testing Persistence of WTI and Brent Long-run Relationship after the Shale oil Supply Shock, Energy Economics, 79, 21-31, 1016/j.eneco.2018.08.022;
  29. Caporin, M., and Costola, M. 2019, Asymmetry and Leverage in GARCH models: A News Impact Curve perspective, Applied Economics, 51, 3345-3364, doi:10.1080/00036846.2019.1578853;
  30. Khalifa, A., Caporin, M., and Di Fonzo, T., 2019, Scenario-based forecast for the electricity demand in Qatar and the role of energy efficiency improvements, Energy Policy, 127, 155-164, doi:10.1016/j.enpol.2018.11.047;
  31. Caporin, M., Chang, C., McAleer, M., 2019, Are the S&P500 index and crude oil, natural gas and ethanol futures related for intra-day data?, International Review of Economics and Finance, 59, 50-70, doi:10.1016/j.iref.2018.08.003;
  32. Bonaccolto, G., Caporin, M., and Gupta, R., 2018, Oil returns conditional quantiles and uncertainty indexes: causality and forecasting implications, Physica A, 507, 446-469, doi:10.1016/j.physa.2018.05.061;
  33. Blasi, S., Caporin, M., and Fontini, F., 2018, A multidimensional analysis of the relationship between firms’ Corporate Social Responsibility activities and their economic performance, Ecological Economics, 147, 218-229, doi:10.1016/j.ecolecon.2018.01.014;
  34. Caporin, M., Pelizzon, L., Ravazzolo, F., and Rigobon, R., 2018, Sovereign contagion in Europe, Journal of Financial Stability, 34, 150-181, doi:10.1016/j.jfs.2017.12.004;
  35. Bonaccolto, G., Caporin, M., and Paterlini, S., 2018, Asset allocation with penalized quantile regression, Computational Management Science, 15, 1-32, doi:10.1007/s10287-017-0288-3;
  36. Caporin, M., Costola, M, Jannin, J., and Maillet, B., 2018, On the (Ab)Use of Omega?, Journal of Empirical Finance, 46, 11-33, doi:10.1016/j.jempfin.2017.11.007;
  37. Caporin, M., Kolokolov, A., and Renò, R., 2017, Systemic co-jumps, Journal of Financial Economics, 126, 563-591, doi:10.1016/j.jfineco.2017.06.016;
  38. Caporin, M., and Gupta, R., 2017, Time-varying persistence in US inflation, Empirical Economics, 53-2, 423-439, doi:10.1007/s00181-016-1144-y;
  39. Caporin, M., and Fontini, F., 2017, The Long-Run Oil-Natural Gas Price Relationship and the Shale Gas Revolution, Energy Economics, 64, 511-519, doi:10.1016/j.eneco.2016.07.024;
  40. Caporin, M., Rossi, E, and Santucci de Magistris, P., 2017, Chasing volatility: a persistent multiplicative error component model with jumps, Journal of Econometrics, 198-1, 122-145, doi:10.1016/j.jeconom.2017.01.005;
  41. Caporin, M., Khalifa, A., and Hammoudeh, S., 2017, The relationship between oil prices and rig counts: The importance of lags, Energy Economics, 63, 213-226, doi:10.1016/j.eneco.2017.01.015;
  42. Caporin, M., and Paruolo, P., 2017, A correction of Caporin and Paruolo (2015), Econometric Reviews, 36(4), 493, doi:10.1080/07474938.2016.1275203;
  43. Caporin, M., Rossi, E., and Santucci de Magistris, P., 2016, Volatility jumps and their economic determinants, Journal of Financial Econometrics, 14-1, 29-80, doi:10.1093/jjfinec/nbu028;
  44. Billio, M., Caporin, M., and Costola, M., 2015, Backward/Forward optimal combination of performance measures, North American Journal of Economics and Finance, 34, C, 63-83, doi:10.1016/j.najef.2015.08.002;
  45. Asai, M., Caporin, M., and McAleer, M., 2015, Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models, International Review of Economics and Finance, 40, C, 40-50, doi:10.1016/j.iref.2015.02.004;
  46. Caporin, M., and Velo, G., 2015, Forecasting realized range volatility: dynamic features and predictive variables, International Review of Economics and Finance, 40, C, 98-112 doi:10.1016/j.iref.2015.02.021;
  47. Caporin, M., Hammoudeh, S., and Khalifa, A., 2015, Spillovers between energy and FX markets: The importance of asymmetry, uncertainty and business cycle, Energy Policy, 87, 72-82, doi:10.1016/j.enpol.2015.08.039;
  48. Baldovin, F., Caporin, M., Caraglio, M., Stella, A., and Zamparo, M., 2015, Option pricing with non-Gaussian scaling and infinite-state switching volatility, Journal of Econometrics, 187, 486-497, doi:10.1016/j.jeconom.2015.02.033;
  49. Caporin, M., Ranaldo, A., and Velo, G., 2015, Precious metals under the microscope: A high-frequency analysis, Quantitative Finance, 15, 743-759, doi:10.1080/14697688.2014.947313;
  50. Baldovin, F., Camana, F., Caporin, M., Caraglio, M., and Stella, A., 2015, Ensemble properties of high frequency data and intraday trading rules, Quantitative Finance, 15, 231-245, doi:10.1080/14697688.2013.867454;
  51. Caporin, M., and Paruolo, P., 2015, Proximity-Structured Multivariate Volatility Models, Econometric Reviews, 34, 559-593, doi:10.1080/07474938.2013.807102;
  52. Caporin, M., Jannin, G.M., Lisi, F., and Maillet, B.B., 2014, A survey of the four families of performance measures, Journal of Economic Surveys, 28, 917-942, doi:10.1111/joes.12041;
  53. Aielli, G.P., and Caporin, M., 2014, Variance clustering improved dynamic conditional correlation estimators, Computational Statistics and Data Analysis, 76, 556-576, doi:10.1016/j.csda.2013.01.029;
  54. Caporin, M., and McAleer, M., 2014, Robust ranking of multivariate GARCH models by problem dimension, Computational Statistics and Data Analysis, 76, 172-185, doi:10.1016/j.csda.2012.05.012;
  55. Caporin, M., Jimenez-Martin, J.A., and Gonzales-Serrano, L., 2014, Currency hedging strategies and strategic benchmarks and the Global and Euro Sovereign financial crises, Journal of International Financial Markets Institutions and Money, 31, 159-177, doi:10.1016/j.intfin.2014.03.015;
  56. Caporin, M., and Lisi, F., 2013, A conditional single index model with local covariates for detecting and evaluating active portfolio management, North American Journal of Economics and Finance, 26, 236-249, doi:10.1016/j.najef.2013.02.003;
  57. Aielli, G.P., and Caporin, M., 2013, Fast Clustering of GARCH Processes Via Gaussian Mixture Models, Mathematics and Computers in Simulations, 94, 205-222, doi:10.1016/j.matcom.2012.09.015;
  58. Bonato, M., Caporin, M., and Ranaldo, A., 2013, Risk spillovers in international equity portfolios, Journal of Empirical Finance, 24, 121-137, doi:10.1016/j.jempfin. 2013.09.005;
  59. Caporin, M., Ranaldo, A., and Santucci de Magistris, P., 2013, On the Predictability of Stock Prices: a Case for High and Low Prices, Journal of Banking and Finance, 37, 5132-5146, doi:10.1016/j.jbankfin.2013.05.24;
  60. Kasch, M., and Caporin, M., 2013, Volatility threshold dynamic conditional correlations: an International analysis, Journal of Financial Econometrics, 11, 706-742, doi:10.1093/jjfinec/nbs028;
  61. Caporin, M., 2013, Equity and CDS sector indices: dynamic models and risk hedging, North American Journal of Economics and Finance, 25, 261-275, doi:10.1016/j.najef.2012.06.004;
  62. Caporin, M., and Preś, J., 2013, Forecasting temperature indices density with time-varying long-memory models, Journal of Forecasting, 32, 339-352, doi:10.1002/for.1272;
  63. Bonato, M., Caporin, M., and Ranaldo, A., 2012, A forecast based comparison of restricted Wishart Auto Regressive models for realized covariance matrices, European Journal of Finance, 18, 761-774, doi:10.1080/1351847X.2011.601629;
  64. Caporin, M., and Lisi, F., 2012, On the role of risk in the Morningstar rating for funds, Quantitative Finance, 12, 1477-1486, doi:10.1080/14697688.2012.665999;
  65. Caporin, M., Preś, J. and Torro, H., 2012, Model Based Monte Carlo Pricing of Energy and Temperature Quanto Options, Energy Economics, 34, 1700-1712, doi:10.1016/j.eneco.2012.02.008;
  66. Caporin, M., and McAleer, M., Do we really need both BEKK and DCC? A tale of two covariance models, 2012, Journal of Economic Surveys, 26, 736-751, doi:10.1111/j.1467-6419.2011.00683.x;
  67. Caporin, M., and Pres, J., 2012, Modeling and forecasting wind speed intensity for weather risk management, Computational Statistics and Data Analysis, 56, 3459-3476, doi:10.1016/j.csda.2010.06.019;
  68. Caporin, M. and Santucci de Magistris, P., 2012, On the evaluation of Marginal Expected Shortfall, Applied Economics Letters, 19, 175-179 doi:10.1080/ 13504851.2011.570704;
  69. Caporin, M., and McAleer, M., 2011, Thresholds, news impact surfaces and dynamic asymmetric multivariate GARCH, Statistica Neerlandica, 65-2, 125-163, doi:10.1111/j.1467-9574.2010.00479.x;
  70. Billio, M., and Caporin, M., 2010, Market linkages, variance spillovers and correlation stability: empirical evidences of financial market contagion, Computational Statistics and Data Analysis, 54-11, 2443-2458, doi:10.1016/j.csda.2009.03.018;
  71. Caporin, M., and McAleer, M., 2010, A Scientific Classification of Volatility Models, Journal of Economic Surveys, 2010, 24-1, 192-195, doi:10.1111/j.1467-6419.2009.00584.x;
  72. Caporin, M., and McAleer, M., 2010, The Ten Commandments for Investment Management, Journal of Economic Surveys, 24,-1, 196-200, doi:10.1111/j.1467-6419.2009.00585.x;
  73. Caporin, M. and Lisi, F., 2010, Misspecification tests for periodic long memory GARCH models, Statistical Methods and Applications, 19-1, 47-62, doi:10.1007/s10260-009-0118-z;
  74. Billio, M., and Caporin, M., 2009, A generalised dynamic conditional correlation model for portfolio risk evaluation, Mathematics and Computer in Simulation, 79-8, 2566-2578, doi:10.1016/j.matcom.2008.12.011;
  75. Bordignon, S., Caporin, M., and Lisi, F., 2009, Periodic Long Memory GARCH models, Econometric Reviews, 28-(1-3), 60-82, doi:10.1080/07474930802387860;
  76. Caporin, M., and McAleer, M., 2008, Scalar BEKK and Indirect DCC, Journal of Forecasting, 27-6, 537-549, doi:10.1002/for.1074;
  77. Caporin, M., 2008, Evaluating value-at-risk measures in presence of long memory conditional volatility, Journal of Risk, 10-3, 79-110;
  78. Billio, M., and Caporin, M., and Cazzavillan, G., 2007, Dating Euro15 monthly business cycle jointly using GDP and IPI, Journal of Business Cycle Analysis and Measurement, 3-3, 336-366, doi:10.1787/17293626;
  79. Bordignon, S., Caporin, M., and Lisi, F., 2007, Generalised Long Memory GARCH models for intra-daily volatility, Computational Statistics and Data Analysis, 51-12, 5900-5912, doi:10.1016/j.csda.2006.11.004;
  80. Caporin, M., 2007, Variance (Non-)Causality in multivariate GARCH: a new model, Econometric Reviews, 26(1), 1-24, doi:10.1080/07474930600972178;
  81. Caporin, M., and McAleer, M., 2006, Dynamic Asymmetric GARCH, Journal of Financial Econometrics, 4(3), 385-412, doi:10.1093/jjfinec/nbj011;
  82. Billio, M., and Caporin, M., and Gobbo, M., 2006, Flexible Dynamic Conditional Correlation Multivariate GARCH for asset allocation, Applied Financial Economic Letters, 2(2), 123-130, doi:10.1080/17446540500428843;
  83. Billio, M., and Caporin, M., 2005, Dynamic conditional correlations: block structures and Markov switches for contagion analysis, Statistical Methods and Applications, 2005-14, 145-161, doi:10.1007/s10260-005-0108-8;
  84. Caporin, M., 2003, Identification of Long memory in GARCH models, Statistical Methods and Applications, 12, 133-151, doi:10.1007/s10260-003-0056-0;
  85. Bertelli, S. and Caporin, M., 2002, A note on calculating autocovariances of long memory processes, Journal of Time Series Analysis, 23(5), 503-508, doi:10.1111/1467-9892.00275.

Other publications in international, national and open access journals

  1. Caporin, M., and Elseidi M., Quantile regression based seasonal adjustment, International Journal of Computational Economics and Econometrics, forthcoming;
  2. Caporin, M., Fontini, F., and Segato, S., 2021, Has the EU-ETS financed the energy transition of the Italian power system?, International Journal of Financial Studies, 9-71;
  3. Caporin, M., and Storti, G., 2020, (Editorial) Financial Time Series Methods and Models, Journal of Risk and Financial Management, 13-(5), 86, 3390/jrfm13050086;
  4. Caporin, M., R.J. Lucchetti, and G. Palomba, 2020, Analytical gradient of dynamic conditional correlation models, Journal of Risk and Financial Management, 13-(3), 49 3390/jrfm13030049;
  5. Khalifa, A., A.A.S.A. Al-Maadid, and M. Caporin, 2019, Water demand in Qatar: future trends and conservation scenarios, Water Utility Journal, 22, 27-42;
  6. Caporin, M., and Poli, F., 2017, Building News Measures from Textual Data and an Application to Volatility Forecasting, Econometrics, doi:10.3390/econometrics5030035;
  7. Bonaccolto, G., and Caporin, M., 2016, The determinants of equity risk and their forecasting implications: a quantile regression perspective, Journal of Risk and Financial Management, 2016, 9, 8, doi:10.3390/jrfm9030008;
  8. Costola, M., and Caporin, M., 2016, Rational learning for risk-averse investors by conditioning on behavioral choices, 11-1, 1650003, Annals of Financial Economics, doi:10.1142/S2010495216500032;
  9. Caporin, M., and McAleer,M., 2013, Ten Things You Should Know about the Dynamic Conditional Correlation Representation, Econometrics, 1, 115-126, doi:10.3390/econometrics1010115
  10. Caporin, M., Lanzavecchia, A., Lippoli, 2013, I fondi immobiliari italiani: NAV discount e valutazioni degli esperti indipendenti, Finanza Produzione e Marketing, 3-2013.
  11. Caporin, M. and Lisi, F., 2011, Comparing and selecting performance measures using rank correlations, Economics: The Open-Access, Open-Assessment E-Journal, Vol. 5, 10, doi:10.5018/economics-ejournal.ja.2011-10;

Book chapters

  1. Bernardi, M., Bonaccolto, G., Caporin, M. and Costola, M., 2020, Volatility forecasting in a data-rich environment, Ch. 5 in Fuleky, P. (ed.), Macroeconomic Forecasting in the Era of Big Data: Theory and Practice, Advanced Studies in Theoretical and Applied Econometrics, Volume 52, Springer, ISBN 978-3030311490;
  2. Bonato, M., Caporin M., and Ranaldo A., 2016, A forecast-based comparison of restricted Wishart autoregressive models for realized covariance matrices, in Nolte I., Salmon M. and Adcock C. (eds.), High Frequency Trading and Limit Order Book Dynamics, Routledge, ISBN  978-1138829381, reprinted from European Journal of Finance (2012);
  3. Caporin, M. and Fontini, F., 2015, Damages Evaluation, Periodic Floods, and Local Sea Level Rise: The Case of Venice, Italy, in Ramiah, W. and Gregoriou, G.N. (eds.), The Handbook of Environmental and Sustainable Finance, Academic Press – Elsevier, ISBN 978-0-128-03615-0, doi:10.1016/B978-0-12-803615-0.00005-4;
  4. Caporin, M., and Velo, G.G., 2013, Modeling and forecasting realized range volatility, in Torelli, N. and Pesarin, F., (eds.), Advances in Theoretical and Applied Statistics, Springer, ISBN 978-3-642-35587-5;
  5. Billio, M., Caporin, M., Pelizzon, L., and Sartore, D., 2013, CDS Industrial Sector Indices, Credit and Liquidity Risk, in Rösch, D., and Scheule, H. (eds.), Credit Securities and Derivatives – Challenges for the Global Markets, John Wiley & Sons, Inc., New Jersey, US, ISBN 978-1-119-96396-7, doi:10.1002/9781118818503.ch15;
  6. Caporin, M., and Pelizzon, L., 2012, Market volatility, optimal portfolios and naive asset allocations, in Wehn, C., Hoppe, C., and Gregoriou, G.N. (eds.), Rethinking Valuation and Pricing Models: Lessons Learned from the Crisis and Future Challenges, Handbooks in Economics, Academic Press – Elsevier, ISBN 978-0124158757, doi:10.1016/B978-0-12-415875-7.00025-7;
  7. Caporin, M. and McAleer, M., 2012, Model selection and testing of conditional and stochastic volatility models, with M. McAleer (Erasmus University Rotterdam), in Bauwens, L., Hafner, C., and Laurent, S. (eds.) Handbook of Volatility Models and Their Applications (Wiley Handbooks in Financial Engineering and Econometrics), John Wiley & Sons, Inc., New Jersey, US, ISBN 978-0470872512, doi:10.1002/9781118272039.ch8;
  8. Billio, M. and Caporin, M., 2011, Contagion dating through market interdependence analysis and correlation stability, in Robert W. Kolb (eds.) Financial Contagion: The Viral Threat to the Wealth of Nations, February 2011, John Wiley & Sons, Inc., New Jersey, US, ISBN 978-0470922385, doi:10.1002/9781118267646.ch4.

 

Book reviews

  1. Caporin, M., 2022, review of Gentle, James; Statistical Analysis of Financial Data: with Examples In R; Chapman and Hall/CRC Press ISBN: 9781138599499646, Journal of the Royal Statistical Society: Series A (Statistics in Society), 185-1, 432-433.

Papers submitted or under revision

  1. “Sign effects of volatility and jumps in forex markets and a reappraisal of meteor showers and heat waves”, with S.J.H. Shahzad (Montpellier Business School) (submitted, second round);
  2. “The Impact of Network Connectivity on Factor Exposures, Asset Pricing and Portfolio Diversification”, with M. Billio (University Ca’ Foscari Venezia), R. Panzica (Goethe University Frankfurt), and L. Pelizzon (University Ca’ Foscari Venezia and Goethe University Frankfurt (submitted, second round);
  3. “Asymmetric and frequency volatility spillover in the Forex market and the role of quantitative easing”, with S.J.H. Shahzad (Montpellier Business School) and T.H.V. Hoang (Montpellier Business School) (submitted);
  4. “The Asymmetric Relationship between Conventional/Shale Rig Counts and WTI Oil Prices”, with F. Fontini (University of Padova) and R. Romaniello (submitted);
  5. “Monitoring financial stress with high-frequency principal components”, with J.A. Jimenez Martin (Complutense University of Madrid) and L. Jorcano (University of Castilla-La Mancha) (submitted);
  6. “The conditional autoregressive G model for common factor detection in the stock market”, with M. Girardi (University of Padova) (submitted);
  7. “Does Monetary Policy Impact Market Integration? Evidence from Developed and Emerging Markets”, with L. Pelizzon (Goethe University Frankfurt) and A. Plazzi (Università della Svizzera Italiana) (submitted);
  8. “Oil Price Uncertainty and Inter-State Conflicts: Evidence from Middle East and North Africa Countries(MENA)”, with Z. Nikpour (University of Padova) and P. Valbonesi (University of Padova) (submitted);
  9. “Estimating time-varying networks with a state space model”, with S. Liu (University of Padova) and S. Paterlini (University of Trento) (submitted);
  10. “On the ordering of dynamic principal components and the implications for portfolio analysis”, with G. Bonaccolto (Kore University of Enna) (submitted);
  11. “The systemic risk of US oil and natural gas companies”, with R. Panzica (JRC, Ispra) and F. Fontini (University of Padova) (submitted);
  12. “Estimating financial networks by realized interdependence: a restricted vector autoregressive approach”, with S. Nasini (IESEG Business School, Lille) and D. Erdemlioglu (IESEG Business School, Lille) (submitted, under revision);

Papers in progress (at different stages of development)

  1. “The nexus between economic activities and CO2 emissions: The case of Qatar”, with A. Khalifa (Qatar University), A.A. Al-Maadid (Qatar University), and T. Di Fonzo (University of Padova);
  2. “Jump risk and pricing implicatons”, with N. Zambon (University of Padova) and W. Distaso (Imperial College London);
  3. “The Evolution of Shadow Banking System in Emerging Economies: The Role of Entrusted Loans in China’s Capital Market”, with M. Gupta (Bennet University, India);
  4. “Dynamic Principal Component: a new class of Multivariate GARCH models”, with G.P. Aielli;
  5. “A Capital Asset Pricing Model with Systemic Risk: Some Evidence on the French Market”, with M. Costola (University Ca’ Foscari Venezia), B. Maillet (EMLyon Business School) and J.C. Garibal (University of Grenoble);
  6. “The economic value of long term care insurances”, with V. Rebba and N. Zambon (University of Padova);
  7. “Vector Random Coefficients and Multivariate GARCH models”;
  8. “A misspecification test for DCC models”, with R.J. Lucchetti (Polytechnic University of March) and G. Palomba (Polytechnic University of March);
  9. “Contagion and volatility jumps”, with F. Lilla (Bank of Italy) and P. Zoi (Bank of Italy);
  10. “Penalized CAW models for systemic risk monitoring”, with G. Storti (University of Salerno);
  11. “The nexus between currencies and commodities intraday price movements and US macroeconomic news”, with S. Hammodeh (Drexel University), W. Mensi (University of Tunis El-Manar) and A. Sensoy (Bilkent University);
  12. “Not all words are equal: sentiment and jumps in cryptocurrency markets”, with F. Poli (University of Padova), O. Cepni (Copenhagen Business School), and A.F. Aysan (Hamad bin Khalifa University)

 

 Other publications

  1. Quarterly Newsletter “Nuova Previdenza”, IAMA Consulting, Milano; methodology boxes: “Gestioni a benchmark: vincoli e flessibilità”; “Manager diversification or manager competition?”; “Misure di performance innovative basate sui drawdown”; “Misure di performance in presenza di un target return”; “Il ruolo del gestore overlay nei fondi pensione”; “Performance attribution e scelte di gestione”; “Il ruolo e l’indipendenza dell’advisor”; “Le competenze della funzione finanza”;
  2. “Analisi delle transizioni nel mercato del lavoro”, with D. Favaro, 2006, Il mercato del lavoro nel Friuli Venezia Giulia, Rapporto 2006, Regione Autonoma Friuli Venezia Giulia, Direzione centrale lavoro, formazione, università e ricerca, Osservatorio regionale sul mercato del lavoro;
  3. “Il mercato del lavoro nel Friuli Venezia Giulia: un’analisi empirica basata su dati amministrativi”, 2005, Il mercato del lavoro nel Friuli Venezia Giulia, Rapporto 2005, Regione Autonoma Friuli Venezia Giulia, Direzione centrale lavoro, formazione, università e ricerca, Osservatorio regionale sul mercato del lavoro;

Citations and bibliographic metrics

(last access: July 2022)

Scopus: 93 listed research products, 1214 citations and h-index equal to 20 (1035 citations and h-index 19 if excluding self-citations of all authors)

ISI web of science: 88 listed research products, 970 citations and h-index equal to 17 (770 citations excluding self-citations)

Dipartimento di Scienze Statistiche | Università degli studi di Padova