Show HN: Factor.fyi – use SQL to visualize financial, crypto and econ datasets

Show HN: Factor.fyi – use SQL to visualize financial, crypto and econ datasets(factor.fyi)

7 points by sdcoffey 4 years ago | 2 comments

Hey HN,

I'm Steve, co-founder of Factor.fyi, a new data platform for querying and visualizing financial datasets using SQL. During the pandemic, I took much more of an active role in managing my portfolio. I wanted to be able to make informed decisions about the investments I was making, and explore financial data in new ways. Market and Econ data are some of the most talked-about and widely-available datasets out there, but I was frustrated by the lack of options to answer questions I had, like, "What would have happened if I had started dollar-cost averaging VTI back in 2013?"[1] Or, "How many days did BTC and ETH move in the same direction as the S&P500?"[2]. We built Factor to answer these questions. You can use Factor to query disparate datasets in ways that are impossible on any other platform. We currently have 20 datasets [3] that you can use to answer questions you have about the markets and create beautiful visualizations around them. Factor is community-powered and free forever; you can browse our community-built charts here [4].

We'd love to get feedback from the HN community, hear your thoughts on what datasets we can add, and get advice on how we can make the querying experience even easier for those new to SQL.

[1]: https://factor.fyi/questions/dollar-cost-averaging-the-marke... [2]: https://factor.fyi/questions/s-p-btc-dia-correlation-factor-... [3]: https://factor.fyi/docs/dataset-reference [4]: https://factor.fyi/browse

mritchie712 4 years ago |

Very cool.

Do you have to pay for any of the data? I'd think that'd get expensive quickly.

sdcoffey 4 years ago | |

Thanks! We don't pay for any of our current datasets. Certain types of data we will eventually have to pay for (e.g., deep options data, short interest). We'll eventually onboard some of these as we see interest, but for now we're optimizing for publicly available but disparate datasets.