Please use this identifier to cite or link to this item:
http://localhost:80/xmlui/handle/123456789/2472Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Das, Dipankar | - |
| dc.date.accessioned | 2018-09-24T05:21:52Z | - |
| dc.date.available | 2018-09-24T05:21:52Z | - |
| dc.date.issued | 2016-05 | - |
| dc.identifier.issn | 2395 -0056 | - |
| dc.identifier.uri | http://172.16.0.4:8085/heritage/handle/123456789/2472 | - |
| dc.description.abstract | The foundation of today’s world is knowledge. Every single event generates some amount of data and by analyzing these vast amounts of data a lot of useful information can be obtained which may lead us to knowledge discovery. Data analysis is an essential step of knowledge discovery. The stock market generates a huge amount of data and by analyzing these data huge amount of useful information can be collected. This paper analyzed the S&P BSE SENSEX data from April, 2015 to March, 2016 to identify the pattern or tend of the S&P BSE SENSEX during this time period by using curve fitting technique. In this paper we have observed that the Compound, Growth and Exponential curves best fit the data i.e. S&P BSE SENSEX versus time during April, 2015 to March, 2016. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | IRJET | en_US |
| dc.relation.ispartofseries | Vol. 3;Issue 5 | - |
| dc.subject | Curve Fitting | en_US |
| dc.subject | S&P BSE SENSEX | en_US |
| dc.subject | Data Mining | en_US |
| dc.subject | Compound Model | en_US |
| dc.subject | Growth Model | en_US |
| dc.subject | Exponential Model | en_US |
| dc.title | Data mining of Indian stock market from April, 2015 to March, 2016 using curve fitting technique | en_US |
| dc.title.alternative | (In) International Research Journal of Engineering and Technology (IRJET) | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | BCA | |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.