We need a series of Python scripts for historical stock data to a sqlite database ([login to view URL]). The first script ([login to view URL]) will download All of the possible data for the stock in to the current date. This script will run everyday or so to download the most recent data to the sqlite database. If there is no prior information then the script will download all available data and create the appropriate tables. The script [login to view URL] will read a sqlite table for the ticker symbols it will need to get. This script will not have any arguments. I would prefer each ticker to have its own table. Also to get the information from yahoo financial you can use [login to view URL]
The second script which is [login to view URL] will add addition information to the stock in an additional column. We need to know what day of the week the stock date is. This value can be numeric. Sunday = 0. This script will be a place holder for any future general data but for right now will only be day of week. This script should get its data from the sqlite database and then put the correct information back in the correct column.
The third script will calculate the Relative strength index ([login to view URL]). This will calculate the RSI for each data point and put the RSI value into a column in the sqlite database. It will need to see the table of available ticker symbols and calculate only the missing values. A good brief explaination on the RSI can be seen here <[login to view URL]:technical_indicators:relative_strength_in> If you have any questions let me know.
The last script is the MACD.py. This will calculate another "indicator" like the RSI and will operate the same as RSI in terms of calculation. Here is a good resource on it. <[login to view URL]:technical_indicators:moving_average_conve> . The values MACD line, Signal line and the MACD histogram will need to be saved into appropriate columns.
If you have any question please do not hesitate to ask. If this works out we will have other indicators programmed as well.