TIME SERIES ANALYSIS ON STOCK MARKET FOR TEXT MINING CORRELATION OF ECONOMY NEWS

Sadi Evren SEKER; Cihan MERT; Khaled AL-NAAMİ; Nuri OZALP; Ugur AYAN

Article Details

TIME SERIES ANALYSIS ON STOCK MARKET FOR TEXT MINING CORRELATION OF ECONOMY NEWS

Authors:

Sadi Evren SEKER | Cihan MERT | Khaled AL-NAAMİ | Nuri OZALP | Ugur AYAN

Publisher:

Sosyal Bilimler Araştırmaları Derneği

Journal:

International Journal of Social Sciences and Humanity Studies 2014 Vol.6 Issue 1, pp.69-91

Document Type:

Article

Publication Date:

5/2014

Document Language:

Turkish

Document ID (Org No.):

2000820051

Frequency:

Bi-Annual

eISSN:

1309-8063

Abstract:

 

This paper proposes an information retrieval method for the economy news. The
 effect of economy news, are researched in the word level and stock market values
 are considered as the ground proof.
 The correlation between stock market prices and economy news is an already addressed
 problem for most of the countries. The most well-known approach is applying
 the text mining approaches to the news and some time series analysis techniques over stock market closing values in order to apply classification or cluster- ing algorithms over the features extracted. This study goes further and tries to ask  the question what are the available time series analysis techniques for the stock  market closing values and which one is the most suitable? In this study, the news  and their dates are collected into a database and text mining is applied over the  news, the text mining part has been kept simple with only term frequency – in- verse document frequency method. For the time series analysis part, we have  studied 10 different methods such as random walk, moving average, acceleration,  Bollinger band, price rate of change, periodic average, difference, momentum or  relative strength index and their variation. In this study we have also explained  these techniques in a comparative way and we have applied the methods over  Turkish Stock Market closing values for more than a 2 year period. On the other  hand, we have applied the term frequency – inverse document frequency method  on the economy news of one of the high-circulating newspapers in Turkey.

Article Details

TIME SERIES ANALYSIS ON STOCK MARKET FOR TEXT MINING CORRELATION OF ECONOMY NEWS

Authors: Sadi Evren SEKER | Cihan MERT | Khaled AL-NAAMİ | Nuri OZALP | Ugur AYAN

Publisher: Sosyal Bilimler Araştırmaları Derneği

Journal: International Journal of Social Sciences and Humanity Studies 2014 Vol.6 Issue 1, pp.69-91

Document Type: Article

Publication Date: 5/2014

Document Language: Turkish

Document ID (Org No.): 2000820051

Frequency: Bi-Annual

eISSN: 1309-8063

Issues

Authors:

Sadi Evren SEKER | Cihan MERT | Khaled AL-NAAMİ | Nuri OZALP | Ugur AYAN

Publisher:

Sosyal Bilimler Araştırmaları Derneği

Journal:

International Journal of Social Sciences and Humanity Studies 2014 Vol.6 Issue 1, pp.69-91

Document Type:

Article

Publication Date:

5/2014

Document Language:

Turkish

Document ID (Org No.):

2000820051

Frequency:

Bi-Annual

eISSN:

1309-8063