| dc.contributor.author | Arinaitwe, Herbert | |
| dc.date.accessioned | 2021-08-20T09:19:18Z | |
| dc.date.available | 2021-08-20T09:19:18Z | |
| dc.date.issued | 2021-05-17 | |
| dc.identifier.citation | Arinaitwe, Herbert (2021)E-Broker application. Undergraduate dissertation. Makerere University | en_US |
| dc.identifier.uri | http://hdl.handle.net/20.500.12281/10883 | |
| dc.description | A project report submitted to the School of Computing and informatics Technology for the study leading to a project report in partial fulfillment of the requirements for the award of the Degree of Bachelor of Science in Computer Science of Makerere University | en_US |
| dc.description.abstract | Stock market prediction has always caught the attention of many analysts and researchers. Popular theories suggest that stock markets are essentially a random walk and it is a fool's game to try and predict them. Predicting stock prices is a challenging problem in itself because of the number of variables which are involved. Application of forecasting techniques and other algorithms for stock price analysis and prediction is an area that we have explored in our research in order to resolve most of the challenges faced in stock trading in Uganda. We first provide a concise review of stock markets and taxonomy of stock market prediction methods. We then focused on some of the methods used in data collection, stock analysis. We
discussed technical, fundamental, short and long- term approaches used for stock analysis.
Finally, we present our findings aimed at addressing the challenges faced by stock traders | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Makerere University | en_US |
| dc.subject | E broker application | en_US |
| dc.subject | stock markets in Uganda | en_US |
| dc.title | E-Broker application | en_US |
| dc.type | Thesis | en_US |
