Trading activities are based on technical analysis, market sentiment (asymmetric information, rumours, noise trading) and imitative behavoiur. This leads to unjustified biasness in decision making. To remove such subjectivity, this paper suggests a neural network model for the investors to decide ...
作者使用了 Apache Spark 大数据框架用于训练过程,最后利用从 2007 年到 2017 年的数据进行模型测试。结果表明,通过选择最合适的技术指标,在大多数情况下,神经网络模型可以实现比较好的策略结果。此外,微调技术指标和(或)优化策略可以提升整体的交易表现。 2. 数据处理 股票市场上面有许多的技术指标,在这里我们主要选择...
(2017) “An Artificial Neural Network-based Stock Trading System Using Technical Analysis and Big Data Framework”, Proceedings of the SouthEast Conference. ACM, 2017. p. 223-226. Google Scholar Cited by (82) Deep learning for financial applications: A survey 2020, Applied Soft Computing Journal...
The financial markets, particularly stock trading, offer a variety of profit-generating opportunities based on complex and volatile behaviour. Investors seek strategies to maximise returns, leading to an investigation of inherent market patterns. Converting OHLC (Open, High, Low, Close) data into trans...
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...
Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock ...
neural network", we provide an in-depth discussion of the methodology, including enhanced SGP for new features, the proposed architecture of the Symbolic Genetic Programming (SGP-DNN model), input data descriptions, forecasting horizon, segmentation predictions method and the trading strategy setting. ...
This paper presents a novel application of ridge polynomial neural network to forecast the future trends of financial time series data. The prediction capa... R Ghazali,AJ Hussain,W El-Deredy - IEEE 被引量: 40发表: 2006年 Neural Networks and Wavelet De-Noising for Stock Trading and Predictio...
(cxq@ ict.ac.cn) Trading Network Predicts Stock Price Xiao-Qian Sun, Hua-Wei Shen & Xue-Qi Cheng Institute of Computing Technology, Chinese Academy of Sciences, No.6 Kexueyuan South Road Zhongguancun, Haidian District, 100190, Beijing, China. Stock price prediction is an important and ...
yacoubb/stock-trading-ml Star625 A stock trading bot that uses machine learning to make price predictions. machine-learningdeep-learningtime-seriesneural-networklstmstock-tradingprice-predictions UpdatedMay 18, 2022 Python Alpaca Trading API integrated with backtrader ...