4.6 Article

Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Mathematics, Interdisciplinary Applications

Application of artificial neural network for the prediction of stock market returns: The case of the Japanese stock market

Mingyue Qiu et al.

CHAOS SOLITONS & FRACTALS (2016)

Article Computer Science, Interdisciplinary Applications

Proximal support vector machine based hybrid prediction models for trend forecasting in financial markets

Deepak Kumar et al.

JOURNAL OF COMPUTATIONAL SCIENCE (2016)

Article Physics, Multidisciplinary

Application of artificial neural network models and principal component analysis method in predicting stock prices on Tehran Stock Exchange

Javad Zahedi et al.

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS (2015)

Article Multidisciplinary Sciences

Quantifying Trading Behavior in Financial Markets Using Google Trends

Tobias Preis et al.

SCIENTIFIC REPORTS (2013)

Article Economics

Predicting the Present with Google Trends

Hyunyoung Choi et al.

ECONOMIC RECORD (2012)

Article Computer Science, Artificial Intelligence

Stock trend prediction based on fractal feature selection and support vector machine

Li-Ping Ni et al.

EXPERT SYSTEMS WITH APPLICATIONS (2011)

Article Computer Science, Artificial Intelligence

Using artificial neural network models in stock market index prediction

Erkam Guresen et al.

EXPERT SYSTEMS WITH APPLICATIONS (2011)

Article Business, Finance

In Search of Attention

Zhi Da et al.

JOURNAL OF FINANCE (2011)

Article Management

A hybrid ARIMA and support vector machines model in stock price forecasting

PF Pai et al.

OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE (2005)

Article Computer Science, Interdisciplinary Applications

Forecasting stock market movement direction with support vector machine

W Huang et al.

COMPUTERS & OPERATIONS RESEARCH (2005)

Article Computer Science, Artificial Intelligence

Financial time series forecasting using support vector machines

KJ Kim

NEUROCOMPUTING (2003)