Portfolio Optimizer Tool (POT) Based on Trend Market Analysis and News Sentiment Analysis
| atmire.migration.oldid | 2742 | |
| dc.contributor.advisor | Alhajj, Reda | |
| dc.contributor.author | Al-jomai, Riad | |
| dc.date.accessioned | 2014-10-16T15:28:43Z | |
| dc.date.available | 2014-11-17T08:00:53Z | |
| dc.date.issued | 2014-10-16 | |
| dc.date.submitted | 2014 | en |
| dc.description.abstract | Stock market and portfolio analysis on financial data conducted by professional investors, who seek informative decision making, is found to be complicated and hard to understand by non-professional investors. In this thesis, we suggest to develop a portfolio optimizer framework which is intended to be beneficial to investors ranging from professionals to non- professionals. The proposed framework integrates data mining techniques such as frequent pattern mining, clustering, classification, and sentiment analysis. To achieve the target, we will apply sentimental analysis to investigate stock market trend in order to predict the actual stock price index movement. This has been realized as an important task for the last decades following the development in technology, though investments in the stock market are active for over a century. According to the accuracy of prediction results, the investors can be guided to investments that might help them make more money. On the other hand, loss of investment is the risk when the prediction reported to investors suffers from lower accuracy or when the prediction is missing some of the factors or objectives that directly or indirectly affect the trend of the market. The integrated framework will help to find the correlation between various stocks in the market to determine groups of stocks predicted to behave similarly, i.e., maintain same trend whether up or down. We will concentrate on the classification of stocks by sector and by industry. This will allow investors to diversify their investments and hence reduce the risk if they prefer. In conclusion, this thesis provides useful guidelines for investors to select appropriate market areas and formulate efficiently diversified investment portfolios. The reported test results demonstrate the applicability and effectiveness of the proposed framework. | en_US |
| dc.identifier.citation | Al-jomai, R. (2014). Portfolio Optimizer Tool (POT) Based on Trend Market Analysis and News Sentiment Analysis (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/27388 | en_US |
| dc.identifier.doi | http://dx.doi.org/10.11575/PRISM/27388 | |
| dc.identifier.uri | http://hdl.handle.net/11023/1931 | |
| dc.language.iso | eng | |
| dc.publisher.faculty | Graduate Studies | |
| dc.publisher.institution | University of Calgary | en |
| dc.publisher.place | Calgary | en |
| dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | |
| dc.subject | Information Science | |
| dc.subject.classification | Stock Market | en_US |
| dc.subject.classification | Data Mining | en_US |
| dc.title | Portfolio Optimizer Tool (POT) Based on Trend Market Analysis and News Sentiment Analysis | |
| dc.type | master thesis | |
| thesis.degree.discipline | Computer Science | |
| thesis.degree.grantor | University of Calgary | |
| thesis.degree.name | Master of Science (MSc) | |
| ucalgary.item.requestcopy | true |