An increasing hybrid morphological-linear perceptron with pseudo-gradient-based learning and phase adjustment for financial time series prediction

@article{Arajo2010AnIH,
  title={An increasing hybrid morphological-linear perceptron with pseudo-gradient-based learning and phase adjustment for financial time series prediction},
  author={Ricardo de A. Ara{\'u}jo and Peter Sussner},
  journal={The 2010 International Joint Conference on Neural Networks (IJCNN)},
  year={2010},
  pages={1-8}
}
Financial time series exhibit a mixture of linear and nonlinear components as indicated by the corresponding lagplots. As we will explain in this paper, certain financial time series can be approximated by increasing functions of a fixed number of time lags or antecedents. This work presents a suitable model for dealing with financial prediction problems, called increasing hybrid morphological-linear perceptron (IHMP). A pseudo-gradient steepest descent method is presented to design the IHMP… CONTINUE READING