Neural networks in finance : gaining predictive edge in the market

By P. McNelis. 2005

194 citations recorded by the source corpus.

How researchers see this paper

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Forecasting stock market short-term trends using a neuro-fuzzy based methodology (2009, background): “To approximate the real stock market process model requires, among other factors, taking into consideration how traders – human beings – actually learn, process information, and make decisions (McNelis, 2005).”
CAN DEEP MACHINE LEARNING OUTSMART THE MARKET? A COMPARISON BETWEEN ECONOMETRIC MODELLING AND LONG- SHORT TERM MEMORY (2016, background): “Paul D. McNelis, 2005, Neural Networks in Finance - Gaining Predictive Edge in the Market, Elsevier Academic Press.”
Neural network Trojan (2013, unknown): “They have seen its use in many application areas such as gaming [9,20,33], ﬁnance [28,55] and health care [3], among many other ﬁelds.”
A dynamically configurable coprocessor for convolutional neural networks (2010, background): “Feed-forward multilayer neural networks [12] are computational models that are widely used in diverse domains such as video and image processing [22], medical diagnosis systems [14] and financial forecasting [15].”
Using artificial neural network models in stock market index prediction (2011, background): “Forecasting simply means understanding which variables lead to predict other variables (Mcnelis, 2005).”