Lin 等人在论文《An SVM-based approach for stock market trend prediction》中提出一种基于支持向量机的股票预测方法,建立两部分特征选择和预测模型,并证明该方法比传统方法具有更好的泛化能力。 2014 年 Wanjawa 等人在论文《ANN Model to Predict Stock Prices at Stock Exchange Markets》中,提出一种利用误差...
Lin 等人在论文《An SVM-based approach for stock market trend prediction》中提出一种基于支持向量机的股票预测方法,建立两部分特征选择和预测模型,并证明该方法比传统方法具有更好的泛化能力。 2014 年 Wanjawa 等人在论文《ANN Model to Predict Stock Prices at Stock Exchange Markets》中,提出一种利用误差反向...
Lin 等人在论文《An SVM-based approach for stock market trend prediction》中提出一种基于支持向量机的股票预测方法,建立两部分特征选择和预测模型,并证明该方法比传统方法具有更好的泛化能力。 2014 年 Wanjawa 等人在论文《ANN Model to Predict Stock Prices at Stock Exchange Markets》中,提出一种利用误差反向...
Lin 等人在论文《An SVM-based approach for stock market trend prediction》中提出一种基于支持向量机的股票预测方法,建立两部分特征选择和预测模型,并证明该方法比传统方法具有更好的泛化能力。 2014 年 Wanjawa 等人在论文《ANN Model to Predict Stock Prices at Stock Exchange Markets》中,提出一种利用误差反向...
在《Knowledge-Driven Stock Trend Prediction and Explanation via Temporal Convolutional Network》中,Shumin 等人提出一种基于时间卷积网络的知识驱动方法(KDTCN),来进行股票趋势预测与解释。 他们首先从财经新闻中提取结构化事件,并利用知识图谱获取事件嵌入。然后,将事件嵌入和股票价格结合起来预测股票走势。实验表明,该...
Green price bars show that the bulls are in control of both trend and momentum as both the 13-day EMA and MACD-Histogram are rising. A red price bar indicates that the bears have taken control because the 13-day EMA and MACD-Histogram are falling. A blue price bar indicates mixed techni...
For example, if the price is above the moving average of the security then this is generally considered an upward trend or a buy.Note: A security needs to have more than 200 active trading days in order to generate an Opinion reading; for futures, the contract must have more than 100 ...
在《Knowledge-Driven Stock Trend Prediction and Explanation via Temporal Convolutional Network》中,Shumin 等人提出一种基于时间卷积网络的知识驱动方法(KDTCN),来进行股票趋势预测与解释。 他们首先从财经新闻中提取结构化事件,并利用知识图谱获取事件嵌入。然后,将事件嵌入和股票价格结合起来预测股票走势。实验表明,该...
在《Knowledge-Driven Stock Trend Prediction and Explanation via Temporal Convolutional Network》中,Shumin 等人提出一种基于时间卷积网络的知识驱动方法(KDTCN),来进行股票趋势预测与解释。 他们首先从财经新闻中提取结构化事件,并利用知识图谱获取事件嵌入。然后,将事件嵌入和股票价格结合起来预测股票走势。实验表明,该...
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