Financial Algorithm Development: Mass Data Search Capability and Interpretation Function.

Hello and thank you for taking the time to read this. I am currently employed by an investment company which requires myself to pinpoint relevant market data that essentially dictates which financial investments provide the opportunities to generate revenue. The better the information, the better the financial forecast and naturally the improved end result. The internet is the source of 98% of this data but a human can only read so much and process so much. Furthermore forecasts can change based on new information systematically and he who is aware of new information tends to have the competitive edge. This algorithm's mission is to provide increased up to date data pools to develop higher quality accuracy enhanced forecasts which hypothetically should lead to improved revenue results. I would like someone to help design an algorithm that has the capability to search the world wide web on particular financial categories and topics e.g Commodity (Silver). The algorithm will need to source and process the maximum data it can locate and present this in a statistical format e.g a percentage formula. The objective of this project is to process higher levels of data a human simply can not. The algorithm will interpret the information to formulate a market sentiment. Algorithm Execution Example- >Topic of search- SILVER >The search begins to any data in relation to the topic (Based off most recent information) > The algorithm collects the required data >The data is processed, interpreted and presented in a percentage formula. The data based sentiment: 55%- Likely hood of Silver prices increasing 45%- Likely hood of Silver prices decreasing. This data is then used in a forecast projection. The algorithm will be an indicator for future price movement. A further in-depth explanation and presentation will be provided to qualified people with the skill set to bring this into reality. Once again thank you for your time.