dc.contributor.author |
Siddeek, Ishfaaq |
|
dc.date.accessioned |
2024-03-20T04:04:50Z |
|
dc.date.available |
2024-03-20T04:04:50Z |
|
dc.date.issued |
2023 |
|
dc.identifier.citation |
Siddeek , Ishfaaq (2023) Cryptocurrency Trading Recommendations and Analysis System. BSc. Dissertation, Informatics Institute of Technology |
en_US |
dc.identifier.issn |
2018243 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/1912 |
|
dc.description.abstract |
"Cryptocurrency trading is a highly volatile firm, with the prices of each cryptocurrency shifting
fast. It is difficult for traders to maintain the pace of continuously shifting market trends and
make informed decisions based on the facts provided. The author attempted to solve this
challenge in this study by building and implementing a Cryptocurrency Trading
Recommendations and Analysis System that may give significant insights into market trends
and assist traders in making profitable investment decisions.
The author used machine learning techniques and statistical models to extract relevant insights
from the massive quantity of data accessible in the Bitcoin market to tackle the challenge of
analyzing it. To predict Bitcoin price patterns, the author used couple of technical indicators.
In addition, the author analyzed market sentiments by pulling data from Twitter media. The
author created a trading recommendation and analysis system that delivers reliable Bitcoin
price predictions by integrating the findings of both technical and fundamental analysis" |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
IIT |
en_US |
dc.subject |
Crypto |
en_US |
dc.subject |
Block chain |
en_US |
dc.subject |
Trading |
en_US |
dc.subject |
Forecast |
en_US |
dc.title |
Cryptocurrency Trading Recommendations and Analysis System |
en_US |
dc.type |
Thesis |
en_US |