Financial markets emanate massive amounts of data from which machines can, in principle, learn to invest with minimal initial guidance from humans. I contrast human and machine strengths and weaknesses in making investment decisions. The analysis rev...
Isis; an international review devoted to the history of science and its cultural influences
26685525
Even in its extended usage, the concept of bounded rationality bears the birthmark of its origins in economics. First and most obviously, it is about seeking the most efficient (not necessarily the best) means toward a given end, whether that is curi...
Computational intelligence and neuroscience
27974883
This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an...
In this paper, control of uncertain fractional-order financial chaotic system with input saturation and external disturbance is investigated. The unknown part of the input saturation as well as the system's unknown nonlinear function is approximated ...
Financial time series forecasting is a crucial measure for improving and making more robust financial decisions throughout the world. Noisy data and non-stationarity information are the two key factors in financial time series prediction. This paper ...
Existing research shows that people can improve their decision skills by learning what experts paid attention to when faced with the same problem. However, in domains like financial education, effective instruction requires frequent, personalized fee...
Significant research in reservoir computing over the past two decades has revived interest in recurrent neural networks. Owing to its ingrained capability of performing high-speed and low-cost computations this has become a panacea for multi-variate ...