L.S. Duke and Long, J., "Neural network futures trading - A feasibility study," Adaptive Intelligent Systems, Elsevier Science Publishers, 1993.Neural network futures trading - A feasibility study,” Adaptive Intelligent Systems - Duke, Long - 1993 () Citation Context ...as long or short ...
Incorporating sentiment indicators ensures that the model provides a more comprehensive view of market dynamics. Using a neural network to solve the Bitcoin option PDE demonstrates the integration of advanced machine learning techniques in financial modelling. These network structures can handle non-...
They concluded that using the stochastic neural network can significantly improve the set of skills that a model acquires. Table 1 shows the relative comparison of state-of-the-art work in the field of trading of cryptocurrencies with the proposed approach....
A more complex type of neural network, recurrent neural networks take the output of a processing node and transmit the information back into the network. This results in theoretical "learning" and improvement of the network. Each node stores historical processes, and these historical processes are ...
Integration of a neural network and the trading terminal is not difficult. I solved this question by passing data via files created by the terminal and the neural network program. One may say that this may slow down decision making by the system. However, this method has its advantages. Firs...
However, the data collected by these networks have to be paired with human-generated predictions. With the help of neural networks, investors can get a comprehensive view of their long-term goals. The term A neural network is an artificial intelligence system that uses a variety of data points...
From a technical point of view, we prove that a single neural network can approximately solve a class of convex semi-infinite programs, which is the key result in order to derive our theoretical results that neural networks can detect model-free static arbitrage strategies whenever the financial ...
Felix (2005), reported that the technical trading strategy guided by feedforward neural network model was superior to buy-and-hold strategy. However, previous efforts on stock market prediction have engaged predominantly the variables of technical analysis.In our view, taking into account the long ...
This paper explores Bitcoin intraday technical trading based on artificial neural networks for the return prediction. In particular, our deep learning method successfully discovers trading signals through a seven layered neural network structure for given input data of technical indicators, which are calcul...
A more biologically realistic PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.1008215 October 2, 2020 18 / 27 PLOS COMPUTATIONAL BIOLOGY Recurrent networks can explain flexible trading of speed and accuracy in biological vision Fig 8. Network unrolling through tim...