Address book

Contacts

Staff Structures

MASSIMILIANO CAPORIN

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Position

Professore Ordinario

Structure

Dipartimento di Scienze Statistiche

Address

VIA CESARE BATTISTI, 241/243 - PADOVA

Telephone

0498274199

E-mail

massimiliano.caporin@unipd.it

Notices

Students are invited to control for possible notices and communications on the Moodle STEM https://stem.elearning.unipd.it/ before showing up during office hours.

Office hours

  • Monday from 10:00 to 12:00
    at Dipartimento di Scienze Statistiche - Via Battisti 241 - Stanza 133
    L'orario di ricevimento è valido durante il periodo didattico (rimane escluso il periodo delle sessioni d'esame). Gli studenti sono invitati ad anticipare via email al docente la presenza a ricevimento. Ricevimenti in altri periodi, o in altro orario, dovranno essere preventivamente concordati con il docente via email. Office hours are valid during the teaching period (excluding exam sessions). Students are invited to inform the professor in advance of their presence at the office hours via email. Meetings in other periods, or at other times, must be agreed in advance with the professor via email.

  • Friday from 10:00 to 12:00
    at Dipartimento di Scienze Statistiche - Via Battisti 241 - Stanza 133
    L'orario di ricevimento è valido durante il periodo didattico (rimane escluso il periodo delle sessioni d'esame). Gli studenti sono invitati ad anticipare via email al docente la presenza a ricevimento. Ricevimenti in altri periodi, o in altro orario, dovranno essere preventivamente concordati con il docente via email. Office hours are valid during the teaching period (excluding exam sessions). Students are invited to inform the professor in advance of their presence at the office hours via email. Meetings in other periods, or at other times, must be agreed in advance with the professor via email.

Teachings

Publications

Recent selected publications

- Caporin, M., Corazzini, L., and Costola, M., 2018, Measuring the Behavioural Component of the S&P 500 and Its Relationship to Financial Stress and Aggregated Earnings Surprises, British Journal of Management, forthcoming;
- 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, doi:10.1016/j.ecolecon.2018.01.014;
- Caporin, M., Pelizzon, L., Ravazzolo, F., and Rigobon, R., 2018, Sovereign contagion in Europe, Journal of Financial Stability, doi:10.1016/j.jfs.2017.12.004;
- Bonaccolto, G., Caporin, M., and Paterlini, S., 2018, Asset allocation with penalized quantile regression, Computational Management Science, doi:10.1007/s10287-017-0288-3;
- Caporin, M., Costola, M, Jannin, J., and Maillet, B., 2018, On the (Ab)Use of Omega?, Journal of Empirical Finance, doi:10.1016/j.jempfin.2017.11.007;
- Caporin, M., Kolokolov, A., and Renò, R., 2017, Systemic co-jumps, Journal of Financial Economics, doi:10.1016/j.jfineco.2017.06.016;
- 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;
- 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;
- 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;
- 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;
- 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;
- 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;
- 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;
- 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;
- 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.

Thesis proposals

For master students (Laurea Magistrale)
- A comparison of current implementations of GARCH models: contrasting Python, R and Matlab
- Realized interdependences: i) simulation on the iterated OLS approach; ii) multiple Gamma measures
- Matrix-valued autoregression on HF data: 1) comparison to tensor-based factor models; 2) cointegration in matrix-valued autoregression
- Analysis of durations: day-by-day ACD models and unconditional duration tail index
- Testing misspecification in DCC-MGARCH models by simulations
- High frequency realized eigenvectors and eigenvalues, the construciton of biplots, and the development of market monitoring indicators based on polar coordinates of the movement of biplots in a rolling scheme with the aid of clustering methods;
- realized skewness and kurtosis: PCA on high frequency data; modelling for detecting higher order interdependence;
- OK (candlestick) estimator of volatility in the presence of jumps and staleness
- Multivariate Marked Hawkes processes for signed best quote movements
- Principal portfolios and an application to European Markets
- Quantile regression methods and applications in finance for style analysis and market timing
- Systemic co-jumps in the currency market around the clock
- Dynamic Network models for applications in finance
- Dynamic models for Interval Valued time series and applications in finance