About the Project The availability and accessibility of financial news in the World Wide Web has surged over the decade as the internet platform became more accessible versus ten years ago. While news had evolved to become more machine-readable, few financial analytical applications had managed to fully take advantage of these news and provide insights. The aim of Project NAVI is to take advantage of news with machine-readable characteristics and create meaning.

Project NAVI presents relationship between news data and financial market place by quantifying financial news. The project employs self-defined text parsing algorithm that quantifies financial news into sentiment ratings. The combination of such quantification algorithm with the project’s map charting and stock charting features enables the representation of news in a quantified and macroeconomic manner, and the display of news and market price relationships to be possible.

Key Benefits

• Appreciate impact of financial news to financial markets: Stock chart’s 30 days news overlay feature plots financial news and sentiment ratings with market prices to enable improved understanding of news impact.
• Improved macroeconomic analysis: Map chart enables macroeconomic visualization of news with insights aggregated for each country. Macro stock picking will be more effective.
• Interactive charts: Charting tools are based In Javascript which are manipulated on the client-sided. Interactive responses from these charting tools are possible.

Key Technologies Used:

• Amazon Elastic Compute Cloud Server
• Crontab scheduler
• Alternative PHP Cache solution
• Apache
• MYSQL Database
• Computer Languages
• Cascading Style Sheet
• JQuery
• Asynchronous Javascript and XML
• PHP Hypertext Preprocessor
• Regular Expression

Potential Opportunities

• Implementing a strong Natural Language Processing algorithm will dramatically improve accuracy of news quantification techniques
• Supporting discourse of finance-related topic through forum while enabling analysis of the community’s opinions through computer algorithms to gain further insights
• Enabling NAVI the flexibility to analyze any form of unstructured English text passage not just limited to the finance domain and output a machine-generated opinion/ rating

Project Team Members

• Yan Dawei
• Ong Qi Yong
• Soh Jun Jie
• Leung Kai Yiu

Supervisor Esther Chia (Ms)