dc.contributor.author |
Aamir, Ammar |
|
dc.contributor.author |
Batool, Syyeda Farheen |
|
dc.contributor.author |
Abdullah, Rai Wasiq |
|
dc.date.accessioned |
2024-10-26T09:12:12Z |
|
dc.date.available |
2024-10-26T09:12:12Z |
|
dc.date.issued |
2024-10-28 |
|
dc.identifier.uri |
http://repository.cuilahore.edu.pk/xmlui/handle/123456789/4337 |
|
dc.description.abstract |
Wealth creation and the stability of the financial system heavily rely on the stock market, which is
an essential part of the global economy where brokers and stakeholders usually trade stock
manually. Alternatively, intelligent systems are also used that make predictions based on past data
to trade automatically. This project proposes “Trading Bot" that facilitates the traders to make
trading simpler on NASDAQ stocks by making educated decisions using deep learning models.
Utilizing historical data, a deep learning model forecasts stock closing price. The user-friendly
interface enables users to visualize predictions and execute manual or automated trades based on
these insights. Additionally, “Trading Bot" can also be useful for amateur users that are interested
in investing in stocks. |
en_US |
dc.language.iso |
en |
en_US |
dc.relation.ispartofseries |
;9250 |
|
dc.relation.ispartofseries |
;FA20- BCS- 076 |
|
dc.relation.ispartofseries |
;FA20- BCS- 001 |
|
dc.relation.ispartofseries |
;FA20- BCS- 004 |
|
dc.subject |
NASDAQ stock |
en_US |
dc.title |
Trading Bot |
en_US |
dc.type |
Thesis |
en_US |