Application of Support Vector Regression in Indonesian Stock Price Prediction with Feature Selection Using Particle Swarm Optimisation
作者: Zuherman RustamPuteri Kintandani
刊名: Modelling and Simulation in Engineering, 2019, Vol.2019
来源数据库: Directory of Open Access Journals
DOI: 10.1155/2019/8962717
原始语种摘要: Stock investing is one of the most popular types of investments since it provides the highest return among all investment types; however, it is also associated with considerable risk. Fluctuating stock prices provide an opportunity for investors to make a high profit. We can see the movement of groups of stock prices from the stock index, which is called Jakarta Composite Index (JKSE) in Indonesia. Several studies have focused on the prediction of stock prices using machine learning, while one uses support vector regression (SVR). Therefore, this study examines the application of SVR and particle swarm optimisation (PSO) in predicting stock prices using stock historical data and several technical indicators, which are selected using PSO. Subsequently, a support vector machine (SVM) was...
全文获取路径: DOAJ  (合作)

  • prices 行情
  • stock 岩株
  • investing 熔模铸造
  • indicator 指示剂
  • technical 技术的
  • opportunity 机会
  • Application 应用
  • Selection 分选
  • selected 被选
  • Vector 矢量