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English Information

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Authors
# Name
1 Tatiane Cazarin da Silva(tatianecazarin@utfpr.edu.br)
2 Gislaine Aparecida Periçaro(gislaine.pericaro@ies.unespar.edu.br)
3 Eduardo Henrique Monteiro Pena(eduardopena@utfpr.edu.br)
4 Ademir Alves Ribeiro(ademir.ribeiro@ufpr.br)

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Reference
# Reference
1 Ben-Tal, A. and Nemirovski, A. (1998). Robust convex optimization. Mathematics of Operations Research, 23:769–805
2 Ben-Hur, A., Horn, D., Siegelmann, H., and Vapnik, V. (2000). A support vector method for clustering. In Advances in Neural Information Processing Systems, pages 346–352
3 Bertsimas, D., Gupta, V., and Kallus, N. (2018). Data-driven robust optimization. Mathematical Programming, 167(2):235–292
4 Bertsimas, D. and Pachamanova, D. (2008). Robust multiperiod portfolio management in the presence of transaction costs. Computers & Operations Research, 35:3–17
5 Ben-Tal, A., Ghaoui, L., and Nemirovski, A. (2009). Robust Optimization. Princeton, NJ.
6 Bertsimas, D. and Sim, M. (2004). The price of robustness. Operations Research, 52:35–53
7 Ben-Tal, A. and Nemirovski, A. (1998). Robust convex optimization. Mathematics of Operations Research, 23:769–805
8 Bertsimas, D. and Thiele, A. (2006). A robust optimization approach to inventory theory. Operations Research, 54:150–168
9 Bertsimas, D., Gupta, V., and Kallus, N. (2018). Data-driven robust optimization. Mathematical Programming, 167(2):235–292
10 Bomfim, U. and Nascimento, F. (2024). Monitoramento do mercado de ativos brasileiro: uma proposta de pipeline de dados para detecção de bolhas financeiras. In Anais Estendidos do XXXIX Simpósio Brasileiro de Bancos de Dados, pages 58–64, Porto Alegre, RS, Brasil. SBC
11 Bertsimas, D. and Pachamanova, D. (2008). Robust multiperiod portfolio management in the presence of transaction costs. Computers & Operations Research, 35:3–17
12 Borgards, O., Czudaj, R. L., and Hoang, T. H. V. (2021). Price overreactions in the commodity futures market: An intraday analysis of the covid-19 pandemic impact. Resources Policy, 71:101966
13 Bertsimas, D. and Sim, M. (2004). The price of robustness. Operations Research, 52:35–53
14 Chenreddy, A. R., Bandi, N., and Delage, E. (2022). Data-driven conditional robust optimization. In Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K., and Oh, A., editors, Advances in Neural Information Processing Systems, volume 35, pages 9525–9537. Curran Associates, Inc
15 Bertsimas, D. and Thiele, A. (2006). A robust optimization approach to inventory theory. Operations Research, 54:150–168
16 Chopra, V. and Ziemba, W. (1993). The effect of errors in means, variances, and covariances on optimal portfolio choice. Journal of Portfolio Management - J PORTFOLIO MANAGE, 19:6–11
17 Bomfim, U. and Nascimento, F. (2024). Monitoramento do mercado de ativos brasileiro: uma proposta de pipeline de dados para detecção de bolhas financeiras. In Anais Estendidos do XXXIX Simpósio Brasileiro de Bancos de Dados, pages 58–64, Porto Alegre, RS, Brasil. SBC
18 Danesh, S., Mohammadi, E., Makui, A., and Jafari, M. (2024). Data-driven robust optimization based on position-regulated support vector clustering. Journal of Computational Science, 76:102210
19 Borgards, O., Czudaj, R. L., and Hoang, T. H. V. (2021). Price overreactions in the commodity futures market: An intraday analysis of the covid-19 pandemic impact. Resources Policy, 71:101966
20 Delage, E. and Ye, Y. (2010). Distributionally robust optimization under moment uncertainty with application to data-driven problems. Operations Research, 58:595–612
21 Chenreddy, A. R., Bandi, N., and Delage, E. (2022). Data-driven conditional robust optimization. In Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K., and Oh, A., editors, Advances in Neural Information Processing Systems, volume 35, pages 9525–9537. Curran Associates, Inc
22 Fabozzi, F., Kolm, P., Pachamanova, D., and Focardi, S. (2007). Robust portfolio optimization - recent trends and future directions. The Journal of Portfolio Management, 33:40–48
23 Chopra, V. and Ziemba, W. (1993). The effect of errors in means, variances, and covariances on optimal portfolio choice. Journal of Portfolio Management - J PORTFOLIO MANAGE, 19:6–11
24 Gurobi Optimization, LLC (2026). Gurobi optimizer reference manual. https://www.gurobi.com/documentation/. Acesso em: 23 fev. 2026
25 Ledoit, O. and Wolf, M. (2008). Robust performance hypothesis testing with the sharpe ratio. Journal of Empirical Finance, 15
26 Danesh, S., Mohammadi, E., Makui, A., and Jafari, M. (2024). Data-driven robust optimization based on position-regulated support vector clustering. Journal of Computational Science, 76:102210
27 Markowitz, H. (1952). Portfolio Selection. Journal of Finance, 7(1):77–91
28 Delage, E. and Ye, Y. (2010). Distributionally robust optimization under moment uncertainty with application to data-driven problems. Operations Research, 58:595–612
29 Sehgal, R. and Jagadesh, P. (2023). Data-driven robust portfolio optimization with semi mean absolute deviation via support vector clustering. Expert Systems with Applications, 224:120000
30 Fabozzi, F., Kolm, P., Pachamanova, D., and Focardi, S. (2007). Robust portfolio optimization - recent trends and future directions. The Journal of Portfolio Management, 33:40–48
31 Shang, C., Huang, X., and You, F. (2017). Data-driven robust optimization based on kernel learning. Computers & Chemical Engineering, 106:464–479.
32 Gurobi Optimization, LLC (2026). Gurobi optimizer reference manual. https://www.gurobi.com/documentation/. Acesso em: 23 fev. 2026
33 Soares, I. R. and Canuto, S. (2025). Criando portfólios de alto desempenho: Otimização de portfólios de ativos de alta volatilidade através da previsão de retorno baseada em cnn+bilstm. In Anais do XL Simpósio Brasileiro de Bancos de Dados, pages 685–698, Porto Alegre, RS, Brasil. SBC
34 Umar, Z., Gubareva, M., and Teplova, T. (2021). The impact of covid-19 on commodity markets volatility: Analyzing time-frequency relations between commodity prices and coronavirus panic levels. Resources Policy, 73:102164
35 Ledoit, O. and Wolf, M. (2008). Robust performance hypothesis testing with the sharpe ratio. Journal of Empirical Finance, 15
36 Zhang, C., Wang, Z., and Wang, X. (2022). Machine learning-based data-driven robust optimization approach under uncertainty. Journal of Process Control, 115:1–11
37 Markowitz, H. (1952). Portfolio Selection. Journal of Finance, 7(1):77–91
38 Sehgal, R. and Jagadesh, P. (2023). Data-driven robust portfolio optimization with semi mean absolute deviation via support vector clustering. Expert Systems with Applications, 224:120000
39 Shang, C., Huang, X., and You, F. (2017). Data-driven robust optimization based on kernel learning. Computers & Chemical Engineering, 106:464–479.
40 Soares, I. R. and Canuto, S. (2025). Criando portfólios de alto desempenho: Otimização de portfólios de ativos de alta volatilidade através da previsão de retorno baseada em cnn+bilstm. In Anais do XL Simpósio Brasileiro de Bancos de Dados, pages 685–698, Porto Alegre, RS, Brasil. SBC
41 Umar, Z., Gubareva, M., and Teplova, T. (2021). The impact of covid-19 on commodity markets volatility: Analyzing time-frequency relations between commodity prices and coronavirus panic levels. Resources Policy, 73:102164
42 Zhang, C., Wang, Z., and Wang, X. (2022). Machine learning-based data-driven robust optimization approach under uncertainty. Journal of Process Control, 115:1–11