Improved Prediction of Financial Market Cycles with Artificial Neural Network and Markov Regime Switching

Author(s):  
David Liu ◽  
Lei Zhang
2021 ◽  
Author(s):  
Paula Campigotto ◽  
Omir Correia Alves Junior

In the financial market there are several types of investors, from the most conservative to the most daring, who are subject to greater risks in the expectation of greater returns on their investments. However, the concept of risk, in investment portfolios, makes it possible to measure it in different ways. This paper aims to present a method created to select portfolios for Day Trade financial investments using different metric risks, such as CVaR, EWMA and GARCH, and the ensemble of Genetic Algorithm NSGA-II and LSTM Artificial Neural Network, comparing it’s selected portfolios’ performance with another method which uses only NSGA-II and Buy and Hold financial strategy. The results show that the proposed method, with LSTM ANN achieved better returns in the year of 2019.


2006 ◽  
Vol 11 (4) ◽  
pp. 371-383 ◽  
Author(s):  
Eleni Constantinou ◽  
Robert Georgiades ◽  
Avo Kazandjian ◽  
Georgios P. Kouretas

2000 ◽  
Vol 25 (4) ◽  
pp. 325-325
Author(s):  
J.L.N. Roodenburg ◽  
H.J. Van Staveren ◽  
N.L.P. Van Veen ◽  
O.C. Speelman ◽  
J.M. Nauta ◽  
...  

2004 ◽  
Vol 171 (4S) ◽  
pp. 502-503
Author(s):  
Mohamed A. Gomha ◽  
Khaled Z. Sheir ◽  
Saeed Showky ◽  
Khaled Madbouly ◽  
Emad Elsobky ◽  
...  

1998 ◽  
Vol 49 (7) ◽  
pp. 717-722 ◽  
Author(s):  
M C M de Carvalho ◽  
M S Dougherty ◽  
A S Fowkes ◽  
M R Wardman

2019 ◽  
Author(s):  
Johannes Thüring ◽  
Kevin Linka ◽  
Christiane Kuhl ◽  
Sven Nebelung ◽  
Daniel Truhn

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