I'm currently using historical financial data culled from Yahoo Finance then analyzing it using Google Sheets. While this has served me quite well for a while, I hate the idea of being 100% reliant on a single source of data. If Yahoo went down, I would effectively "go dark". Historical Google finance data is utter garbage, and I'm amazed Google permits the data to be disseminated without giant red flags warning of how imperfect it is. I'm willing to pay for historical data, but all I really need is OHLC and the ability to adjust for splits and dividends which is why YFIN data has been great.
Theoretically this shouldn't be tremendously difficult, but apparently it is difficult to find reliable historical data.
My somewhat *ambitious* plan:
1. Finally make the switch from Google Sheets to R.
2. Use Quandl (api w/in R) and their EOD wiki for data (my backup plan for Yahoo)
a. find a "plan C" for data. NDAQ site appears scrapeable
3. 20% chance: set up dedicated homeserver (using an old desktop, and using Python (or R!):
record EOD data, update daily (save data 1st, adjust after calling it)
most likely will store optionable stocks. must be able to add/delete tickers as needed w/minimal disruption to data
record short interest data, record biweekly
record earnings dates, update every weekend
This is more than enough for me to chew on for the time being. I'll probably need Tyler Durden to make sure I follow through with my plan. I'll update and reference this as I go. Don't be surprised if 3 months from now I haven't done a single thing with it.
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