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O. Banerjee, L. El Ghaoui, A. d’Aspremont, Model selection through sparse maximum likelihood estimation,J. Mach. Learn. Res., 9 (2008) 485—516 ⇒288Search in Google Scholar
G. E. Box, G. C. Tiao, A canonical analysis of multiple time series Biometrika, 64 (1977) 355 ⇒288, 29010.1093/biomet/64.2.355Search in Google Scholar
A. d’Aspremont, Identifying small mean reverting portfolios, Quant. Finance, 11 (2011) 351–364 ⇒288, 29010.1080/14697688.2010.481634Search in Google Scholar
N. Fogarasi, J. Levendovszky, Sparse, mean reverting portfolio selection using simulated annealing,Quant. Finance, 11 (2011) 351–364 ⇒288, 29210.1080/14697688.2010.481634Search in Google Scholar
S. Geman, D. Geman, Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images, IEEE Trans. Patt. Anal. Mach. Intellig, 6 (1984) 721–741 ⇒29210.1109/TPAMI.1984.476759622499653Search in Google Scholar
S. Hochreiter, J. Schmidhube, Long Short-Term Memories, Neural Computation, 9 (1997) 1735–1780 ⇒29310.1162/neco.1997.9.8.17359377276Search in Google Scholar
H. Lütkepohl, New Introduction to Multiple Time Series Analysis, Springer (1993) ⇒29110.1007/978-3-642-61695-2Search in Google Scholar
L. S. Ornstein, G. E. Uhlenbeck, On the theory of the Brownian motion, Phys. Rev, 36 (1930) 823 ⇒29010.1103/PhysRev.36.823Search in Google Scholar
M. Phi, Illustrated Guide to LSTM’s and GRU’s: A step by step explanation, Sep 24, 2018. https://tinyurl.com/aus2xtjx ⇒295Search in Google Scholar
A. Rácz, N. Fogarasi, Improved sparse mean reverting portfolio selection using Simulated Annealing and Extreme Learning Machine, submitted to Algorithmic Finance ⇒289Search in Google Scholar
V.-D. Ta, C.-M. Liu, D. A. Tadesse, Portfolio optimization-based stock prediction using long-short term memory network in quantitative trading, Applied Sciences, 10 (2020) 437 ⇒28910.3390/app10020437Search in Google Scholar
P. Salamon, P. Sibani, R. Frost, facts, conjectures, and improvements for simulated annealing, SIAM Monographs on Mathematical Modeling and Computation. Society for Industrial and Applied Mathematics, 36 (2002) ⇒29210.1137/1.9780898718300Search in Google Scholar
A. Yadav, C. K. Jha, A. Sharan, Optimizing LSTM for time series prediction in Indian stock market, Procedia Computer Science, 167 (2020) 2091–2100 ⇒28910.1016/j.procs.2020.03.257Search in Google Scholar
