VINCENZO CANDILA | Curriculum

Curriculum (ITA)

Mar. 2022 - presente: Ricercatore (Tipo B) in Statistica Economica, Dipartimento di Scienze Economiche e Statistiche, Università di Salerno

Mag. 2021: Abilitazione Scientifica Nazionale, seconda fascia, in Statistica Economica

Ott. 2019 – Feb. 2022: Ricercatore (Tipo A) in Statistica Economica, Dipartimento di Metodi e Modelli per l’Economia, il Territorio e la Finanza, Università “La Sapienza”, Roma

Set. 2018 – Ott. 2018: Visiting scholar presso il Department of Economics, University of Konstanz, Germany

Ago. 2016 – Lug. 2019: Assegnista di ricerca, Dipartimento di Scienze Economiche e Statistiche, Università di Salerno

2013: Master of Science in Economics, major in Research in Economics (cum laude), Katholieke Universiteit Leuven, Belgium

Referee per numerose riviste internazionali, tra cui: Economic Modelling, Quantitative Finance, Energy Economics, European Journal of Finance, Journal of Economic Behavior & Organization, Econometrics and Statistics, Bulletin of Economic Research.

Recenti pubblicazioni / Recent publications

Arcagni, A., Candila, V. and R. Grassi, 2022, A new model for predicting the winner in tennis based on the eigenvector centrality, Annals of Operations Research, forthcoming, DOI: 10.1007/s10479-022-04594-7

Angelini, G., Candila, V. and L. De Angelis, 2022, Weighted Elo rating for tennis match predictions, European Journal of Operational Research, 297(1), DOI: 10.1016/j.ejor.2021.04.011

Candila, V., Maximov, D., Mikhaylov, A., Moiseev, N., Senjyu, T. and N. Tryndina, 2021, On the Relationship between Oil and Exchange Rates of Oil-Exporting and Oil-Importing Countries: From the Great Recession Period to the COVID-19 Era, Energies, 14, 8046, DOI: 10.3390/en14238046

Andreani, M., Candila, V., Morelli, G. and L. Petrella, 2021, Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach, Risks, 9(8), 1–20, DOI: 10.3390/risks9080144

Candila, V., 2021, Multivariate analysis of cryptocurrencies, Econometrics, 9(3), 1–17, DOI: 10.3390/econometrics9030028

Candila, V. and L. Petrella, 2021, Hypotheses testing in mixed–frequency volatility models: a bootstrap approach, in Book of short papers - SIS 2021, 1413–1418, ISBN: 9788891927361

Andreani, M., Candila, V. and L. Petrella, 2021, Quantile Regression Forest with mixed frequency data, in Book of short papers - SIS 2021, 1419–1424, ISBN: 9788891927361

Amendola, A., Candila, V. and G.M. Gallo, 2021, Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model, Econometrics and Statistics, 20, 12–28, DOI: 10.1016/j.ecosta.2020.11.001

Candila, V. and L. Petrella, 2020, Adding MIDAS terms to Linear ARCH models in a Quantile Regression framework, in Book of short papers - SIS 2020, 910–915, ISBN: 9788891910776

Amendola, A., Candila, V. and G.M. Gallo, 2020, Double Asymmetric GARCH–MIDAS model - new insights and results, in Book of short papers - SIS 2020, 927–932, ISBN: 9788891910776

Amendola, A., Boccia, M., Candila, V. and G.M. Gallo, 2020, Energy and non-energy commodities - Spillover effects on African stock markets, Journal of Statistical and Econometric Methods, 9(4), 91–115, DOI: 10.47260/jsem/vol947

Amendola, A., Candila, V., Sensini, L. and G. Storti, 2020, Governance, Innovation, Profitability, and Credit Risk: Evidence from Italian manufacturing firms, International Journal of Business and Social Science, 11(6), 32–42, DOI: 10.30845/ijbss.v11n6p3

Amendola, A., Candila, V. and G.M. Gallo, 2020, Choosing between weekly and monthly volatility drivers within a Double Asymmetric GARCH-MIDAS model, in Nonparametric Statistics, M. La Rocca, B. Liseo e L. Salmaso Eds., DOI: 10.1007/978-3-030-57306-5

Candila, V. and L. Palazzo, 2020, Neural Networks and Betting Strategies for Tennis, Risks, 8(3), 1–19, DOI: 10.3390/risks8030068

Amendola, A., Candila, V., Sensini, L. and G. Storti, 2020, Corporate Governance, Investment, Profitability and Insolvency Risk: Evidence from Italy, Advances in Management & Applied Economics, 10(4), 185–202

Amendola, A., Braione, M., Candila, V. and G. Storti, 2020, A Model Confidence Set approach to the combination of multivariate volatility forecasts, International Journal of Forecasting, 36(3), 873–891, DOI: 10.1016/j.ijforecast.2019.10.001

Amendola, A., Candila, V. and G.M. Gallo, 2019, On the asymmetric impact of macro–variables on volatility, Economic Modelling, 76, 135–152, DOI: 10.1016/j.econmod.2018.07.025

Candila, V. and S. Farace, 2018, On the Volatility Spillover between Agricultural Commodities and Latin American Stock Markets, Risks, 6(4), 1–16, DOI: 10.3390/risks6040116

Candila, V. and A. Scognamillo, 2018, Estimating the Implied Probabilities in the Tennis Betting Market: A New Normalization Procedure, International Journal of Sport Finance, 13, 225–242

Amendola, A. and V. Candila, 2017, Comparing multivariate volatility forecasts by direct and indirect approaches, Journal of Risk, 19(6), 33–57, DOI: 10.21314/JOR.2017.364

Amendola, A., Candila, V. and A. Scognamillo, 2017, On the influence of U.S. monetary policy on crude oil price volatility, Empirical Economics, 52(1), 155–178, DOI: 10.1007/s00181-016-1069-5

Amendola, A. and V. Candila, 2016, Evaluation of volatility predictions in a VaR framework, Quantitative Finance, 16(5), 695–709, DOI: 10.1080/14697688.2015.1062122