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Pedro Henrique Melo Albuquerque
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2020 – today
- 2022
- [j9]Pedro Henrique Melo Albuquerque, Gustavo S. Monteiro:
RMCriteria: a decision making support system package for R. Commun. Stat. Simul. Comput. 51(6): 3259-3271 (2022) - 2021
- [j8]Igor Ferreira do Nascimento, Pedro Henrique Melo Albuquerque, Yaohao Peng
:
Survey on-demand: a versatile scientific article automated inquiry method using text mining applied to asset liability management. Int. J. Bus. Intell. Data Min. 18(3): 261-290 (2021) - [j7]Pedro Alexandre Moura Barros Henrique, Pedro Henrique Melo Albuquerque, Sarah Sabino De Freitas Marcelino, Yaohao Peng
:
Portfolio selection with support vector regression: multiple kernels comparison. Int. J. Bus. Intell. Data Min. 18(4): 395-410 (2021) - 2020
- [j6]Leonardo Bosque, Pedro Henrique Melo Albuquerque, Yaohao Peng
, Cibele Da-Silva, Eduardo Yoshio Nakano
:
Probability of informed trading: a Bayesian approach. Int. J. Appl. Decis. Sci. 13(2): 183-214 (2020)
2010 – 2019
- 2019
- [j5]Yaohao Peng
, Pedro Henrique Melo Albuquerque, Igor Ferreira do Nascimento
, João Victor Freitas Machado:
Between Nonlinearities, Complexity, and Noises: An Application on Portfolio Selection Using Kernel Principal Component Analysis. Entropy 21(4): 376 (2019) - [j4]Pedro Henrique Melo Albuquerque, Denis Ribeiro do Valle, Daijiang Li:
Bayesian LDA for mixed-membership clustering analysis: The Rlda package. Knowl. Based Syst. 163: 988-995 (2019) - 2018
- [j3]Yaohao Peng
, Pedro Henrique Melo Albuquerque, Jáder Martins Camboim de Sá, Ana Julia Akaishi Padula, Mariana Rosa Montenegro:
The best of two worlds: Forecasting high frequency volatility for cryptocurrencies and traditional currencies with Support Vector Regression. Expert Syst. Appl. 97: 177-192 (2018) - 2017
- [j2]Mariana Rosa Montenegro, Pedro Henrique Melo Albuquerque:
Wealth management: Modeling the nonlinear dependence. Algorithmic Finance 6(1-2): 51-65 (2017) - [j1]Pedro Correia S. Bezerra, Pedro Henrique Melo Albuquerque:
Volatility forecasting via SVR-GARCH with mixture of Gaussian kernels. Comput. Manag. Sci. 14(2): 179-196 (2017)
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