Stock Market Prediction Using Hidden Markov Model

被引:0
|
作者
Somani, Poonam [1 ]
Talele, Shreyas [1 ]
Sawant, Suraj [1 ]
机构
[1] Coll Engn Pune, Dept Comp Engn & Informat Technol, Pune, Maharashtra, India
关键词
Neural networks; Hidden Markov Model; Support Vector Machine; Stock market prediction; Mean Squared Error; Mean Absolute Percentage Error;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Stock market is the most popular investment scheme promising high returns albeit some risks. An intelligent stock prediction model would thus be desirable. So, this paper aims at surveying recent literature in the area of Neural Network, Hidden Markov Model and Support Vector Machine used to predict the stock market fluctuation. Neural networks and SVM are identified to be the leading machine learning techniques in stock market prediction area. Also, a model for predicting stock market using HMM is presented. Traditional techniques lack in covering stock price fluctuations and so new approaches have been developed for analysis of stock price variations. Markov Model is one such recent approach promising better results. In this paper a predicting method using Hidden Markov Model is proposed to provide better accuracy and a comparison of the existing techniques is also done.
引用
收藏
页码:89 / 92
页数:4
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