Stock Market Data Analysis

Using stock price and volume data from an API (see API tab) and DASH by Plotly (open to others), create a stock criteria filter and show the past results of all stock symbols and dates in which the selected stock filter criteria are met. Attached files may help to understand the project details. Please begin by viewing "[login to view URL]" That is the general description. Other files provide accompanying descriptions of some items within the StockMarketDataProject file. The stock data considered are the following: For approximately 5,000 stock ticker symbols, analyze 6 months of 1-minute-intraday data. Each 1-minute line of data contains an 'open', 'high', 'low', 'close', and 'volume'. The time frame considered each day is 04:01:00 to 20:00:00. Not every minute of every day for every symbol contains data. Time frames within the full day time frame will be explained in other tabs of this Excel spreadsheet. For dates beyond 6 months in the past, a separate API call will be made. Details of the different API calls are shown in the 'API' tab. In all, we are considering about 710 million rows of data. 5 data points per each row * 710 million = approximately 3.5 billion data points. The program created will need to be able to handle this amount of information without slowing down the output. We need under 5 seconds of lag from the time inputs are selected to the time that output is completed and visible. I am currently considering the options offered by Vaex + HDF5 file combination to decrease lag. I will be open to other solutions that can produce the results requested. Please see project details in the attached excel file. Further additions are planned. So, this needs to be scalable and still able to handle calculations within 5 seconds. Please note that the 1-minute intraday data will need to be updated once a day. The Company overview data will need to be updated once a week. This should be an automatic function of the program created. Further details are included in the attached file Python, C, Vaex + HDF5, DASH (by Plotly) may be helpful, but not necessary if better options are available that can fulfill the project requirements. If HDF5 files will be necessary and a reliable online file transfer method is not available, then I would prefer that the programmer is based in the U.S. to be able to increase reliability and convenience of sending files by post. Experience with stock market data is not necessary, but if you don't have stock market related project experience, I would prefer working with somebody that has strong English communication skills so that the details are not lost due to communication issues. The files added to the project files may help you to understand the project a bit more. If, after viewing the files, you have any questions, please let me know.