Leopoldo Catania
Leopoldo Catania is Associate Professor at Aarhus University and CREATES.
Leopoldo’s research interests focus on Financial Econometrics and Time Series Analysis. His works concern the development and estimation of univariate and multivariate econometrics models applied to quantitative risk management, density predictions of financial returns, time-varying dependence, and volatility.
Belotti, F., Casini, A., Catania, L., Grassi, S. & Perron, P. (2023). Simultaneous Bandwidths Determination for DK-HAC Estimators and Long-Run Variance Estimation in Nonparametric Settings. Econometric Reviews, 42(3), 281-306. https://doi.org/10.1080/07474938.2023.2178138
Catania, L. (2022). A Stochastic Volatility Model with a General Leverage Specification. Journal of Business and Economic Statistics, 40(2), 678-689. https://doi.org/10.1080/07350015.2020.1855187
Catania, L., Di Mari, R. & Santucci de Magistris, P. (2022). Dynamic Discrete Mixtures for High Frequency Prices. Journal of Business and Economic Statistics, 40(2), 559-577. https://doi.org/10.1080/07350015.2020.1840994
Catania, L. & Grassi, S. (2022). Forecasting cryptocurrency volatility. International Journal of Forecasting, 38(3), 878-894. https://doi.org/10.1016/j.ijforecast.2021.06.005
Catania, L. (2021). Dynamic Adaptive Mixture Models with an Application to Volatility and Risk. Journal of Financial Econometrics, 19(4), 531-564. https://doi.org/10.1093/jjfinec/nbz018
Catania, L., Luati, A. & Vallarino, P. (2021). Economic vulnerability is state dependent. Institut for Økonomi, Aarhus Universitet. CREATES Research Paper No. 2021-09
Catania, L. & Di Mari, R. (2021). Hierarchical Markov-Switching Models for Multivariate Integer-valued Time-series. Journal of Econometrics, 221(1), 118-137. http://10.1016/j.jeconom.2020.02.002
Catania, L. & Nonejad, N. (2020). Density Forecasts and the Leverage Effect: Evidence from Observation and Parameter–Driven Volatility Models. The European Journal of Finance, 26(2-3), 100-118. https://doi.org/10.1080/1351847X.2019.1586744
Tranberg, B., Hansen, R. T. & Catania, L. (2020). Managing Volumetric Risk of Long-term Power Purchase Agreements. Energy Economics, 85, [104567]. https://doi.org/10.1016/j.eneco.2019.104567
Catania, L. & Luati, A. (2020). Robust Estimation of a Location Parameter with the Integrated Hogg Function. Statistics & Probability Letters, 164, [108812]. https://doi.org/10.1016/j.spl.2020.108812
Catania, L. & Sandholdt, M. (2019). Bitcoin at High Frequency. Journal of Risk and Financial Management, 12(1), [36]. https://doi.org/10.3390/jrfm12010036
Catania, L., Grassi, S. & Ravazzolo, F. (2019). Forecasting Cryptocurrencies Under Model and Parameter Instability. International Journal of Forecasting, 35(2), 485-501. https://doi.org/10.1016/j.ijforecast.2018.09.005
Catania, L., Ardia, D. & Boudt, K. (2019). Generalized Autoregressive Score Models in R: The GAS Package. Journal of Statistical Software, 88(6). https://doi.org/10.18637/jss.v088.i06
Ardia, D., Bluteau, K., Boudt, K., Catania, L. & Trottier, D-A. (2019). Markov–Switching GARCH Models in R: The MSGARCH Package. Journal of Statistical Software, 91(4). https://doi.org/10.18637/jss.v091.i04
Bernardi, M. & Catania, L. (2019). Switching generalized autoregressive score copula models with application to systemic risk. Journal of Applied Econometrics, 34(1), 43-65. https://doi.org/10.1002/jae.2650
Ardia, D., Boudt, K. & Catania, L. (2018). Downside Risk Evaluation with the R Package GAS. The R Journal, 10(2), 410-421. https://doi.org/10.32614/RJ-2018-064
Catania, L. & Nonejad, N. (2018). Dynamic Model Averaging for Practitioners in Economics and Finance: The eDMA Package. Journal of Statistical Software, 84(11). https://doi.org/10.18637/jss.v084.i11
Ardia, D., Bluteau, K., Boudt, K. & Catania, L. (2018). Forecasting Risk with Markov-Switching GARCH Models: A large-scale performance study. International Journal of Forecasting, 34(4), 733-747. https://doi.org/10.1016/j.ijforecast.2018.05.004
Catania, L. & Bernardi, M. (2018). Portfolio Optimisation Under Flexible Dynamic Dependence Modelling. Journal of Empirical Finance, 48(September), 1-18. https://doi.org/10.1016/j.jempfin.2018.05.002
Catania, L., Grassi, S. & Ravazzolo, F. (2018). Predicting the Volatility of Cryptocurrency Time–Series. In M. Corazza, M. Durbán, A. Grané, C. Perna & M. Sibillo (Eds.), Mathematical and Statistical Methods for Actuarial Sciences and Finance (pp. 203-207). Springer. https://brage.bibsys.no/xmlui/bitstream/handle/11250/2482825/WP_CAMP_3_2018.pdf
Bernardi, M. & Catania, L. (2018). The Model Confidence Set package for R. International Journal of Computational Economics and Econometrics, 8(2), 144 - 158. https://doi.org/10.1504/IJCEE.2018.091037
Bernardi, M., Catania, L. & Petrella, L. (2017). Are News Important to Predict the Value–at–Risk? European Journal of Finance, 23(6), 535-572. https://doi.org/10.1080/1351847X.2015.1106959
Catania, L. & Billé, A. G. (2017). Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances. Journal of Applied Econometrics, 32(6), 1178–1196. https://doi.org/10.1002/jae.2565
Bernardi, M. & Catania, L. (2016). Comparison of Value-at-Risk models using the MCS approach. Computational Statistics, 31(2), 579-608. https://doi.org/10.1007/s00180-016-0646-6
