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Python toolkit for quantitative finance

github.com

41–50 of 72 posts

Re: Python toolkit for quantitative finance

#41

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...

I was really surprised there aren't any real examples here. You have a couple of videos linked, but am I really going to pause the video and hand copy each line of code?

Re: Python toolkit for quantitative finance

#43

Cool to see some "bank Python" that Cal Paterson had described previously is now open source https://calpaterson.com/bank-python.html

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...

Re: Python toolkit for quantitative finance

#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 etc. etc.

In fact a good reason why "adtech" is (absurdly) considered part of "big tech" is that no other business sector has managed to articulate a long-term sustainable digitization story.

Re: Python toolkit for quantitative finance

#45

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 forgetting a number of other inputs.

Re: Python toolkit for quantitative finance

#47

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…

You can limp into a fair bit of the corpact data via open source/free channels, but reliable sources are definitely expensive.

Not to mention the real-time data which is, quite simply, catastrophically expensive. And that’s assuming the least sophisticated (retail) implementation of this stuff.

Re: Python toolkit for quantitative finance

#48

This seems pretty basic, really just classes of common data structures used in finance. Closer to what you would expect for a final project for a undergrad in OOP course.

That's what you find in a lot of domain specific libraries written by scientists, mathematicians, etc. Professional engineer-quality code written by people who aren't professional engineers is rare. Or it's some enormously popular library that has had a lot of attention from engineers over the years.
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