Publications

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Submitted
An adaLASSO variation for seasonal time series, Rangel, L. N., Ziegelmann F. A., and Konzen E. , Journal of Forecasting, (Submitted)
Forecasting Tail Risk for Energy Markets via Dynamic GAS Vine Copulas, Abreu, L., Tofoli P., and Ziegelmann F. A. , Computational Economics, (Submitted)
Predicting Football Matches with PARX-Copula Models: an Application to the Premier League, Damiani, Leonardo, and Ziegelmann Flavio A. , Journal of the Royal Statistical Society: Series A, (Submitted)
2025
Measuring and explaining efficiency of pre-vaccine country responses to COVID-19 pandemic: a conditional robust nonparametric approach, Kuchenbecker, A. S., Torrent H. S., and Ziegelmann F. A. , Empirical Economics, Volume 68, p.107-137, (2025)
2024
Combining LASSO-Type Methods with a Smooth Transition Random Forest, Gandini, A., and Ziegelmann F. A. , Annals of Data Science, (2024)
Dynamic Factor Copulas for Minimum-CVaR Portfolio Optimization, Alovisi, G., and Ziegelmann F. A. , Time Series and Wavelets Analysis: Festschrift in Honor of Pedro A. Morettin, p.175--195, (2024) Abstract

Copula models have become popular for minimum conditional value-at-risk (CVaR) portfolio optimization, especially due to their ability to deal with nonlinear dependencies. Nevertheless, as the number of assets in a portfolio increases, the estimation of copulas, particularly dynamic ones, becomes computationally burdensome. In this work, our novel contribution is to adapt and implement a dynamic factor copula model for the asset returns dependencies and find an optimal, potentially high dimensional, portfolio via minimizing its CVaR. The resulting model is capable of addressing the ``curse of dimensionality'' for the dependencies, while maintaining enough complexity and flexibility. The factor copula dynamics are described by a generalized autoregressive scores (GAS) model for the factor loadings. Using data consisting of B3 Brazilian stocks from January 2013 to December 2020, we find the optimal portfolio and evaluate its out of sample economic performance. Empirical results suggest that our min-CVaR-factor-copula strategy has either equal or better risk/return metrics when compared to a traditional Gaussian copula, while being considerably superior than both Markowitz mean-variance and equal weights portfolios as well as the IBRX50 index.

2023
(Portuguese) O Impacto do Comércio Internacional sobre as Condições de Saúde: uma Abordagem Estrutural, Souza, W. P. S. F., Ziegelmann F. A., and Figueiredo E. A. , Revista Brasileira de Economia, Volume 77, Issue 2, p.e122023, (2023)
A Pairs Trading Strategy based on Mixed Copulas, Silva, F. B. S., Ziegelmann F. A., and Caldeira J. F. , The Quarterly Review of Economics and Finance, Volume 87, p.16-34, (2023)
Realized Semicovariances: Empirical Applications to Volatility Forecasting and Portfolio Optimization, Ricco, R., and Ziegelmann F. A. , Brazilian Review of Finance, Volume 21, Issue 33, p.99-122, (2023)
Robust Nonparametric Frontier Estimation in Two Steps, Chen, Y., Torrent H. S., and Ziegelmann F. A. , Econometric Reviews, Volume 42, Issue 7, p.612-634, (2023)
2021
Measuring systemic risk via GAS models and extreme value theory: Revisiting the 2007 financial crisis, Gavronski, P., and Ziegelmann F. A. , Finance Research Letters, Volume 38, p.101498, (2021)
2020
(Portuguese) Uma nota sobre o prêmio salarial em empresas exportadoras brasileiras, Souza, W., Ziegelmann F. A., and Figueiredo E. , Revista Brasileira de Economia, Volume 74, p.221-232, (2020)
2019
Dynamic D-Vine Copula Model with Applications to Value-at-Risk (VaR), Tófoli, P., Ziegelmann F. A., Silva Filho O. C., and Pereira P. L. V. , Journal of Time Series Econometrics, Volume 11, Issue 2, p.20170016, (2019)
Mixing conditions of conjugate processes, Horta, E., and Ziegelmann F. A. , Chilean Journal of Statistics, Volume 10, Issue 2, p.123-129, (2019)
Robust factor modelling for high-dimensional time series: An application to air pollution data, Reisen, V. A., Sgrancio A. M., Levy-Leduc C., Bondon P., Monte E. Z., Cotta H., and Ziegelmann F. A. , Applied Mathematics and Computation, Volume 346, p.842-852, (2019)
2018
(Portuguese) As Condições de Saúde Afetam os Rendimentos do Trabalho? Evidências para o Mercado de Trabalho no Brasil, Souza, W., Ziegelmann F. A., and Figueiredo E. , Economia Aplicada, Volume 22, p.113-150, (2018)
Conjugate processes: Theory and application to risk forecasting, Horta, E., and Ziegelmann F. A. , Stochastic Processes and their Applications, Volume 128, p.727-755, (2018)
Dynamics of financial returns densities: A functional approach applied to the Bovespa intraday index, Horta, E., and Ziegelmann F. A. , International Journal of Forecasting, Volume 34, p.75-88, (2018)
Robust estimation of fractional seasonal processes: Modeling and forecasting daily average SO 2 concentrations, Reisen, V. A., Monte E. Z., Franco G. C., Sgrancio A. M., Molinares F. A. F., Bondon P., and Ziegelmann F. A. , Mathematics and Computers in Simulation, Volume 146, p.27-43, (2018)
2017
A Comparison Study of Copula Models for European Financial Index Returns, Tofoli, P., Ziegelmann F. A., and Filho Silva O. C. , International Journal of Economics and Finance, Volume 9, p.155-178, (2017)
2016
Identifying the spectral representation of Hilbertian time series, Horta, E., and Ziegelmann F. A. , Statistics & Probability Letters, Volume 118, p.45-49, (2016)
LASSO-Type Penalties for Covariate Selection and Forecasting in Time Series, Konzen, E., and Ziegelmann F. A. , Journal of Forecasting, Volume 35, p.592-612, (2016)
Market risk forecasting for high dimensional portfolios via factor copulas with GAS dynamics, Bartels, M., and Ziegelmann F. A. , Insurance Mathematics & Economics, Volume 70, p.66-79, (2016)
2015
Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data, Borges, B. K., Caldeira J. F., and Ziegelmann F. A. , Brazilian Review of Econometrics, Volume 35, p.23-46, (2015)