Stock Market Prediction Using Data Mining Techniques

2019 ◽  
Author(s):  
Archana Gupta ◽  
Pranay Bhatia ◽  
Kashyap Dave ◽  
Pritesh Jain
Keyword(s):  
Data Mining ◽  
Stock Market ◽  
Stock Market Prediction ◽  
Data Mining Techniques ◽  
Using Data

A Review on Applied Data Mining Techniques to Stock Market Prediction

2013 ◽  
pp. 108-126
Author(s):  
Neslihan Fidan ◽  
Beyza Ahlatcioglu Ozkok
Keyword(s):  
Data Mining ◽  
Stock Market ◽  
New Technologies ◽  
Point Of View ◽  
Stock Market Index ◽  
Data Mining Techniques ◽  
Market Index ◽  
Predictive Data Mining ◽  
Using Data ◽  
Analysis Point

A portfolio manager considers forecasting the asset prices and measurement of the market risk of an underlying asset. Financial institutions produce datasets to handle their problems by using data mining tools. Recently new technologies have been developed for tracking, collecting, and processing financial data. From a data analysis point of view, this chapter reviews the published articles based upon predictive data mining applications to stock market index. It is observed that hybrid models that combine data mining techniques or integrate an algorithm to a method work efficiently. Finally, the chapter provides likely directions of future researches.

scholarly journals Analysis of investors’ preferences in the Montenegro stock market using data mining techniques

2014 ◽  
Vol 27 (1) ◽  
pp. 463-482 ◽  
Author(s):  
Ljiljana Kašćelan ◽  
Vladimir Kašćelan ◽  
Miomir Jovanović
Keyword(s):  
Data Mining ◽  
Stock Market ◽  
Data Mining Techniques ◽  
Using Data

Analysis of Crop Yield Prediction of Kharif & Rabi Jowar Crops Using Data Mining Techniques

2017 ◽  
Vol 7 (11) ◽  
pp. 79
Author(s):  
Sujata Mulik
Keyword(s):  
Data Mining ◽  
Crop Yield ◽  
Crop Production ◽  
Climatic Factors ◽  
Crop Productivity ◽  
Yield Prediction ◽  
Data Mining Techniques ◽  
Agriculture Sector ◽  
Using Data ◽  
Rabi Crops

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction.  The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops. 

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