Show HN: Investorsexchange.jl – parse trade-level stock market data in Julia
2 by lukemerrick | 1 comments on Hacker News.
Backstory: I wanted to play with intraday stock data but couldn't find a free dataset anywhere. IEXCloud [1] offers API access to 1-minute granularity intraday historical price data, but I was worried that it could get expensive or unwieldy to build up a substantial dataset via API calls. Plus, IEX gives out their raw data for free. I probably should have just used the IEXTools python library [2] to parse IEX's raw data dumps, but I was working on a Julia project, so it felt more thematically appropriate to build a new tool from scratch. I haven't been actively using InvestorsExchange.jl a lot lately, but it's made me the proud owner of a 50GB SQLite DB dump covering several years of trade data, and I think it would be awesome if I could help folks in the HN community more quickly build up this kind of dataset for their own curiosity or research. Feedback is also greatly appreciated! [1] https://ift.tt/Z1LDicV [2] https://ift.tt/Hqv8klT
2 by lukemerrick | 1 comments on Hacker News.
Backstory: I wanted to play with intraday stock data but couldn't find a free dataset anywhere. IEXCloud [1] offers API access to 1-minute granularity intraday historical price data, but I was worried that it could get expensive or unwieldy to build up a substantial dataset via API calls. Plus, IEX gives out their raw data for free. I probably should have just used the IEXTools python library [2] to parse IEX's raw data dumps, but I was working on a Julia project, so it felt more thematically appropriate to build a new tool from scratch. I haven't been actively using InvestorsExchange.jl a lot lately, but it's made me the proud owner of a 50GB SQLite DB dump covering several years of trade data, and I think it would be awesome if I could help folks in the HN community more quickly build up this kind of dataset for their own curiosity or research. Feedback is also greatly appreciated! [1] https://ift.tt/Z1LDicV [2] https://ift.tt/Hqv8klT