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Finally, some properties of stock market are described by measuring the change of structure entropy of the stock networks. The proposed method is applied to assess performance of six market indices of six countries (China, America, Germany, France, Japan, Britain) for 28 years. Meanwhile, some...
小成图股市预测法(Small graph stock market prediction method).doc,小成图股市预测法(Small graph stock market prediction method) Small graph stock market prediction method First, the origin of the method A small map for the Chongqing folk scientist Huo
Graph-based approaches are revolutionizing the analysis of different real-life systems, and the stock market is no exception. Individual stocks and stock market indices are connected, and interesting patterns appear when the stock market is considered as a graph. Researchers are analyzing the stock ...
Exploring Graph Neural Networks for Stock Market.pdf 388.5K· 百度网盘 TIps: this model structure can also be used in other situation, and we can add other kinds of information embedding, using different kinds of feature extraction method which include GAT to do the relationship embedding. ...
Quantitative trading and investment decision making are intricate financial tasks in the ever-increasing sixty trillion dollars global stock market. Despite advances in stock forecasting, a limitation of most existing neural methods is that they treat stocks independent of each other, ignoring the valuabl...
The main goal of this work is to test the validity of this approach across different markets and longer time horizons for backtesting using rolling window analysis. In this work, we concentrate on the prediction of individual stock prices in the Japanese Nikkei 225 market over a period of ...
现代机器学习:with the booming of artificial intelligence technology, machine learning techniques have been introduced to handle complex financial market data and proved to be useful for making stock trendpredictions。 第三段:CNN简介 —— 近些年来使用图像特征的研究 —— 指出现在的不足就是欠缺考虑整个...