Real time decision making forecasting using Data mining and Decision tree

被引：0

作者：

Asaduzzaman, Md ^{[1
]}

Shahjahan, Md ^{[2
]}

Murase, Kazuyuki ^{[1
]}

机构：

[1] Univ Fukui, Grad Sch Engn, Fukui, Japan

[2] Khulna Univ Engn & Technol, Dept Elect & Elect Engn, Khulna 9203, Bangladesh

来源：

2014 JOINT 7TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 15TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS) | 2014年

关键词：

Autoregressive; Data mining; Stock markets; Neural network;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The stock market is gaining relevance with each day. Much research has been done in the area of finding a means to forecasting the fluctuations. Yet decision-making remains a challenging task in the current age of forecasting. Our proposed algorithm uses autoregressive methods to assist with the decision to buy as well as the selling point for any stock price. The proposed algorithm is more useful for the shareholder than the trader. This decision making tool can be essential to the formation of the business plan and its viability is proved by the significant amount of profit that has already been yielded.

引用

页码：1029 / 1033

页数：5

共 13 条

[1]

Abrabian Alireza, 2012, J SEL TOPICS SIGNAL, V6, P399

[2]

[Anonymous], 2011, SAGE DICT QUANTITATI, DOI DOI 10.4135/9781446251119.N67

[3] Permutation entropy: A natural complexity measure for time series [J].