In this study, we generate 50 Multi-layer Perceptons, 50 Radial Basis Functions, 50 Higher Order Neural Networks and 50 Recurrent Neural Network and we explore their utility in forecasting and trading the DJIA, NASDAQ 100 and the NIKKEI 225 stock indices. The statistical significance of the ...
When studying the possibilities of neural network application in financial markets, I came to the conclusion that neural networks can be used not only as the main signal generator, but also as an option for unloading the software part of the trading Expert Advisor. Imagine that you decide to w...
When applied to trading, I want to use convolutional neural networks to improve the recognition of trading patterns on a price chart. 1. Distinctive features of convolutional neural networks Convolutional networks, in comparison with a fully connected perceptron, have two new layer types: ...
In this work, a high-frequency trading strategy using Deep Neural Networks (DNNs) is presented. The input information consists of: (i). Current time (hour and minute); (ii). The last n one-minute pseudoi:10.1007/978-3-319-66963-2_14Andrés Arévalo...
In the present study, evolved neural network is applied to construct a new intelligent stock trading system. First, heterogeneous double populations based hybrid genetic algorithm is adopted to optimize the connection weights of feedforward neural networks. Second, a new intelligent stock trading system...
“Application of neural networks to an emerging financial market: forecasting and trading the Taiwan Stock Index”, Computers & Operations Research, 30 (2003), pp. 901-923 View PDFView articleView in ScopusGoogle Scholar 3 J.Z. Wang, J.J. Wang, Z.G. Zhang, S.P. Guo “Forecasting stock...
In the era of digital technology and artificial intelligence, algorithmic trading is transforming financial markets, offering innovative strategies. The book "Neural Networks for Algorithmic Trading with MQL5" serves as a unique guide that combines advanced technological knowledge with practical guidance on...
Empirical results show that the PNN-based investment strategies obtain higher returns than other investment strategies examined in this study. Influences of length of investment horizon and commission rate are also considered. 展开 关键词: Emerging economy Forecasting Trading strategy Neural networks ...
Financial Volatility Trading Using Recurrent Neural Networks.Presents a study on recurrent neural networks. Trading of options; Predictive models; Elman recurrent neural network; Discussion on data, volatility measures and trading strategy.TinoPeterSchittenkopfChristianDorffnerGeorg...
Neural networks, in the world of finance, assist in the development of such processes as time-series forecasting,algorithmic trading, securities classification, credit risk modeling, and constructing proprietary indicators and pricederivatives. A neural network works similarly to the human brain’s neural...