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Python toolkit for quantitative finance

github.com

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Re: Python toolkit for quantitative finance

#51

Post by sexy_year »

You can also check OpenBB, one of the most known projects in this category: https://github.com/OpenBB-finance/OpenBBTerminal

Most data vendors will require a free API key because that's their GTM. They want you to create an account with them to get a free API key and then expect to be able to upsell you over time.

Or you can access "free data" (e.g. yfinance) that relies on projects who actively scrape financial data from a website - these tend to need a lot of updates from main maintainer since there are no aligned incentives between maintainer of the scrapped API and company that has the data.

PS: I'm the main creator behind the OpenBB project on GitHub.

Re: Python toolkit for quantitative finance

#52

Post by openrisk »

jgalt212 wrote: post #45
openrisk wrote: post #44

The financial industry never considered a serious open source strategy to be aligned with their interests and that has painted the sector in increasingly narrower corners. Think eg. the comparison with the acumen of the adtech sector, which supports (among countless other things) the most used open source mobile OS, the most used open source web browser, the most sophisticated open source suites for machine learning…

The problem is that the models (closed sourced or open source) only get you part of the way. For example, (to name just a few items) a stock option pricing model is useless without - holiday calendars - ex dividend dates - interest rate curves - real-time stock prices - corporate actions database Are there open source and free sources of the above? For the first two, sort of, for the remainder, no. And I'm sure I'm f…

Any data requirement in the above list that is public knowledge can be solved (in principle), but it takes coordination between parties that are not used to collaborative/coopetitive behavior.

There is also the bit of data cleaning work that is costly - somebody must be paid to design and operate it, but again with modern tech solutions its likely that this could become immaterial.

Yet there is broader challenge beyond concrete applications: the financial industry is 100% an information processing industry but is largely inconsequential and absent in the development of modern digital technology.

Re: Python toolkit for quantitative finance

#55

Post by dash2 »

sexy_year wrote: post #51

You can also check OpenBB, one of the most known projects in this category: https://github.com/OpenBB-finance/OpenBBTerminal Most data vendors will require a free API key because that's their GTM. They want you to create an account with them to get a free API key and then expect to be able to upsell you over time. Or you can access "free data" (e.g. yfinance) that relies on projects who actively scrape financial data…

Is there a way out of this dilemma?

Are there any decent APIs for UK data, by the way?

Re: Python toolkit for quantitative finance

#56

Post by curiousgal »

kingkongjaffa wrote: post #11

The only utility here is to study the design. Access to anything useful is behind GS specific data APIs via https://developer.gs.com/docs/gsquant/authentication/gs-sess...

How could one study said design? By generating class diagrams or what?

Re: Python toolkit for quantitative finance

#57

Post by bostik »

refset wrote: post #43
snovymgodym wrote: post #36

Earlier quoted context omitted.

Nah this looks pretty orthogonal to that. This just looks like a collection of pure python libraries for doing common quant work. The thing Cal Peterson is describing (which is pretty transparently JP Morgan's Athena) would be SecDB at Goldman and would be running on their proprietary scripting language called "Slang". None of that is open source. Goldman was the first place to do a system like that, and when it was…

Beacon is more PaaS than SaaS from what I've seen, but it's all very neatly integrated and they even wrote their own compute scheduling engine. The data model is interesting: https://www.beacon.io/wp-content/uploads/2021/05/5.-WhitePap...

> Beacon is more PaaS than SaaS from what I've seen

You are correct. (Full disclosure: I work at Beacon.)

Financial institutions are extremely sensitive about where their data is held, processed, stored and/or sent to. Some of it is just basic corporate governance ("we do not like the additional risk"). Some you could lump in with secrecy and competitive edge ("this is our secret sauce, no way are we going to let anyone else get it"). Some is driven by regulations ("we hold/process highly sensitive financial and personal data on individuals, sending it to a third party is a huge no-no"). And some is just garden variety contract obligations.

[Note that I intentionally chose to omit any consideration for "plain" security. In this industry that can get political.]

Where data governance/sovereignity is concerned, the term "SaaS" is commonly understood as: "send data to a third party, get results back". You can imagine how well that plays with any data an institution considers precious.

Re: Python toolkit for quantitative finance

#59

Post by solatic »

jgalt212 wrote: post #45
openrisk wrote: post #44

The financial industry never considered a serious open source strategy to be aligned with their interests and that has painted the sector in increasingly narrower corners. Think eg. the comparison with the acumen of the adtech sector, which supports (among countless other things) the most used open source mobile OS, the most used open source web browser, the most sophisticated open source suites for machine learning…

The problem is that the models (closed sourced or open source) only get you part of the way. For example, (to name just a few items) a stock option pricing model is useless without - holiday calendars - ex dividend dates - interest rate curves - real-time stock prices - corporate actions database Are there open source and free sources of the above? For the first two, sort of, for the remainder, no. And I'm sure I'm f…

I can't see the financial industry getting behind FOSS, but there's very much a missed opportunity for Data API companies. Let trading firms pay standard rates to get access to high-resolution, realtime data; the secret sauce in each firm then becomes what kind of trading algorithm you write to make the most profit off that data. Ensuring that everyone has potential access to the same underlying data helps dissuade claims that profits are made from insider trading. There should be all kinds of data for all kinds of domains available when you fork over a little money for an API key.

Re: Python toolkit for quantitative finance

#60

Post by [deleted] »

openrisk wrote: post #44

The financial industry never considered a serious open source strategy to be aligned with their interests and that has painted the sector in increasingly narrower corners. Think eg. the comparison with the acumen of the adtech sector, which supports (among countless other things) the most used open source mobile OS, the most used open source web browser, the most sophisticated open source suites for machine learning…

[deleted]
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