Bloomberg Stock Analysis System

Abstract – Stock market prediction and analysis is the act of trying to determine the future value of company stock or other financial instrument traded on an exchange. The Stock market is an important part of the economy of the country & plays a vital role in the growth of the industry and commerce of the company that eventually affects the economy of the country. Both investors & industry are involved in the stock market and want to know whether some stock will rise or fall over a certain period.


Bloomberg is the most reputed stock analysis company in the world, which provides the data of stock exchanges of various listed companies. They want to show live data of stock market analysis of various listed china-based market companies, in that we have to predict the future market of stock analysis for the next 2 hours using the previous 100 times data. This is predictive analysis.


1. Stock exchange returns lots of data in a single request as per user preferences we have to fetch all interested company stock values and have to keep UI updated. A major challenge in the system was to keep UI updated and active while the system is loading each stock data in the background for every 16 ms and do the analysis work after response.

2. While we have to predict any stock value for the next two hours we also have to make sure the prediction accuracy percentile should be 70-90%.To achieve this much accuracy we need more historical data to analyze. Also, we have to think about how much historical data we can use to make sure it’s not making any performance concern in an application.


We provide the Windows-based application for analysis of listed company stock analysis for the next 2 hours, for that we use the WPF technology along with C-harp & graphical representation of stock analysis.

To overcome 1st challenge, we used solution like ,Parallel Background processing and Multithreading option. And for 2nd challenge we used following technique, In that we used Bloomberg’s livestock API’s, using that we refresh the data after every 16 ms for that We used the maximum 100 history records which get converted into 100% values with a difference of positive and negative percentile.

The above fig shows the live data analysis between various companies , in that green digits shows the positive changes in stock market whereas the red digits shows the negative changes in the stock market of various companies.


  • Using Stock Analysis system we can predict the market for stock for next 2 hours, based on previous history of 100 times only.
  • Stock analysts attempt to determine the future activity of an instrument, sector, or market.


  • We can convert this application with a web application or android application.
  • We can improve our prediction accuracy using Data Analytics & AI.
  • We can develop the same system for other markets.
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