tl;dr By "give away" they mean allow their sophisticated clients access the tools to do business with Goldman. It's not open sourced or available publically in any manner.
If a customer uses a bank's database to do their pricing, they tend be much more likely to do their trading with that firm. This is why firms like to have their models become the market standard. (Example: "Lehman Live" was used to price Mortgage Backed Securities. Unfortunately that didn't end well)
It's used for pricing & risk management. Considered the best in class for large banks and has been attributed (at least partially) for GS scathing away from the financial crisis relatively unharmed because of being able to quickly price things, determine risk throughtout the firm, and make quick decisions.
Many other banks expose some of their pricing code as a web application to varying extents. For example https://live.barcap.com/ which was inherited from LehmanLive, considered state of the art for fixed income back in the day.
Also as the article states, anything that still has an actual competitive advantage won't be released.
I'm pretty sure they're referring to SecDB. There isn't much known about SecDB outside of Goldman, but I think the essence is that it:
1. Is a distributed data store for market positions, etc.
2. There's a dataflow/spreadsheet-like valuation engine on top of the data store
3. It's had long-term and senior level support among management, and most/all of GS's positions and businesses are available within SecDB.
4. There's a large pool of internal talent that's well acquainted with SecDB and how to use it.
So... it gives GS an easy way to see where they are, and then run models to figure out where they might be under different hypothetical scenarios.
What's noteworthy about this to me is that while they may be 'giving away' points 1 and 2 from my list, points 3 and 4 are the bigger competitive differentiators for Goldman. Even if another bank immediately adopts SecDB, while they may get the technology, it'll take them quite a while to integrate it as fully into their culture and business. SecDB implemented for a small bit of a big bank and run by a bunch of relative newcomers is a very different thing than SecDB as it might be implemented at Goldman.
I'm pretty sure that's not the same SecDB. It's interesting that it's written by Serge Aleynikov, but it doesn't really match the extant descriptions of the Goldman tool and it's a fork of https://github.com/maxlapshin/stockdb
It's been available outside Goldman for a long time. Cantab Capital had based their systems on it as long ago as 2006. The founders were ex Goldman and wangled some kind of deal where they could use the GS systems.
IIRC from a conversation with an employee, the two were initially very close: I think the deal included something like CC co-locating servers in a GS datacenter as well as licensing its software, but both ended several years ago in anticipation of a change in regulation.
You can click "web" which will provide you a link to the article without the paywall.
But just for you: "Called Securities DataBase, or SecDB, the system remains Goldman’s prime tool for measuring risk and analyzing the prices of securities, and it calculates 23 billion prices across 2.8 million positions daily. It has played a crucial role in many of the seminal moments of the firm’s recent history, including its controversial trading just ahead of the financial crisis."
I would assume because this space is becoming more of a commodity and their tool is no longer unique -- on it's face. So by making it available to customers they can garner goodwill and entrench themselves.
The tool is also extremely messy internally, written in a proprietary language that resembled a very early version of Python and has accrued nearly unthinkable technical debt. Delivering usage via webservice lets them better hide the dysfunction on the other end of a service call.
This whole topic is not all that newsworthy. The team within Goldman that had architected and developed this years ago had spun out into a consulting group that essentially reimplemented the same thing in Bank of America (Quartz), JPMorgan (Athena) and many others, now including Morgan Stanley, and even trickling down to smaller banks like PNC.
I consider it one of the biggest ripoffs in modern finance that those organizations have paid untold fortunes to adopt the Goldman-like approach, sometimes even with new or additional proprietary languages brought in on the project. It also adds systemic risk for society because it further correlates these internal banking systems between the largest banks. If something goes systematically wrong with it in one place, there's a comparatively high risk the same sort of thing can or will go wrong in another too.
If we were bearing that risk for a good reason it might be OK. But really we're only bearing it because of the superficial branding of Goldman, and the pressure on banks to hand wave and appear to be doing something in the aftermath of the 2008 crisis. And so they go for what looks politically defensible (e.g. "well, this is what Goldman did and they survived the crash" -- despite it being widely researched and reported that Goldman's position in the crash truly had nothing at all to do with superior risk management systems and was a mixture of political favors and luck) instead of anything sensible from a system design point of view.
Last I heard Quartz and Athena are both failed projects. Quartz's lead left years ago, Netezza DB was having massive issues, and Python was way too slow. They had to reboot the project and it is nowhere close to what they wanted it. Athena has similar issues with developers constantly changing, no direction, and still isn't anywhere close to real-time risk. I know Credit Suisse had something working, but I haven't heard where that project was going since they moved it from C# to Java.
Would you have any insights on why other places are perceived to not to be able replicate Goldman's success (since you mentioned failed projects) ?
Is it really the tech, and not because of GS's business practices instead ?
I can't speak for the other commenters, but my view is that not even Goldman has really any success to show for it. The whole Slang/SecDB thing is a colossal failure even inside of Goldman. That they nonetheless ratchet pay upwards to entice overqualified engineers to babysit a clearly defunct and ineffectual system is no surprise though, because keeping the lid on its badness is paramount to their marketing efforts, which in turn drives GSAM's ability to get high AUM, and more recently has driven the ability to sell this nonsense to others.
The software is junk software. There's no other secret thing going on -- no misdirection or duplicitous motives. A certain class of high-paying customers responds more to the Goldman brand name -- or at least believes it buys them cache with regulators or investors. For that class of customers, vetting the reliability and quality of the tech stack is at best an afterthought. Since that pile of money exists as a thing for Goldman to target, they do target it.
I advocate that more people should prioritize vetting the technology. If so, they would see it is not of sufficient quality to justify its use, let alone paying to perpetuate it elsewhere. But I'm not naive -- the political approach will always matter more to a wide range of people than will a more objective assessment.
Besides introducing systematic risk, the sale of this software by Goldman smells fishy. Despite the Blankfein quote about maybe selling for $5 billion back in the day, if the software is what they purport it to be, wouldn't selling it be akin to Amazon licensing their product distribution to Walmart?
I've wondered what these million dollar per month programmers do on Wall Street. This really puts it in perspective.
On that note, it's completely depressing to see many of the best minds of our time working on shit software that adds nothing to society. Another swath of them are working on getting people to click on ads for Facebook and Google.
> Another swath of them are working on getting people to click on ads for Facebook and Google.
Which finances Google's driverless car efforts and an untold other amount of businesses (like gmail). Plus the salaries of thousands of developers and the myriad of other people who work for Google, and the subindustries it supports (bus drivers, chefs, real estate, etc). Just because their specific job isn't world-changing doesn't mean it has no positive effect on the world.
Silicon Valley has benefited greatly from the ad industry which is why the popularity of this type of complaint bothers me.
Same with Goldman. They do contribute to the world by facilitating commerce. Although they likely contribute far less to the world than SV developers since they siphon so much off the top for ultimately marginal longterm ROI. They also ultimately wouldn't make so much money unless they did provide some value to the economy beyond exploitation of byzantine financial systems.
I grant that Google is more of a social good than Facebook.
Your claim that Goldman has contributed is a debated topic. Paul Krugman favorably mentioned a study that purports to demonstrate that Wall Street's endeavors are largely unproductive. I can't find it now unfortunately.
Please see my last comment, this is a debated topic.
However, I've read Mike Milken and, despite his warts, I believe he did radically improve capital allocation. So it certainly has happened over the years.
-- edit: I meant about Mike Milken
Somewhere along the line CTO's or their juniors with budgeting authority were convinced that Goldman's success was due in some measure to SecDB and Slang, which is pure nonsense.
haha, but of course you mean ctrl+F9 -- you probably edited multiple files...
I completely agree with the parent and grandparent posts! I worked with one of the SecDB clones for three years at a Too Big To Fail bank, and it was criminally bad (imho). It's snake oil.
I agree with jnordwick that "Quartz and Athena are both failed projects." For example, Mike Dubno, Kirat Singh, and three other managing directors on the Quartz project are all gone [1].
I agree with the grandparent post that "Goldman's position in the crash truly had nothing at all to do with superior risk management systems and was a mixture of political favors and luck"
The snake oil in this case is what p4wnc6 (who's spot on) highlighted: "The team within Goldman that had architected and developed this years ago had spun out into a consulting group that essentially reimplemented the same thing" [at other banks].
The product that they sold (a SecDB clone) is pure snake oil, and the projects (which were massively expensive) delivered very little value.
Consider: If SecDB really lives up to the hype, then why would Goldman let all these other banks steal Goldman developers and straight-up copy it?
And they can gauge where client's interests lie at. Something like google could (what I would do if I were google) gauge interest in various stocks and commodities people search for and make some kind of model based on that. Ye olde adage, if you're not paying for the product, you are the product.
Any bank will provide it's buy side customers research and in many cases software or at least web applications to evaluate and price securities which are over the counter and/or illiquid. It's not just courtesy; it's necessary if you want to buy and sell the stuff.
However, a customer who blindly puts their trading book onto some Goldman application isn't smart enough to do business with Goldman.
As someone who worked at a large bank providing month-end marks for customers (as a 'courtesy'), we knew that we were basically just seeing the stuff we had sold them, and at most half of any other positions they asked for were actually bonds they owned.
Using non public information obtained from a client in dealings with another client, or at all on the public side of the firm, would breach Chinese walls. Never mind internal controls, most jurisdictions have relevant legislation to prevent exactly this behaviour.
There is no non-public info in this case. It's same as if you were in a public hall with a lot of people, who talk only about stocks, and writing down how many, how often and when particular stocks are mentioned and in which context (buy, sell, various). Morally ambiguous thing is that hall belongs to Google and they're the only one up in the balcony, which is the only place you can hear all the people from.
So, is it data, a database, or a risk-management tool?
Sounds like something that could have been hard with constraints of 1990s hardware, but these days any old person could rent a cloud to do this.
Also, I suspect people who aren't involved directly in the technology talk it up a lot more than would someone who was involved in building it. The execs have bet on it with budget money, and they get to open or close the gate, making it seem more important than it really is.
At the end of the day, every financial form has a bunch of code that lets them slice and dice their data. GS didn't survive the crisis because they had this system, they survived because they had a system and made some wise choices.
It's also a very slick integrated development environment for financial use cases.
The securities/price data are exposed as first-class entities in an ORM layer and you can manipulate them easily with scoping rules.
For example, if you want to get the current USD/JPY rate, it's just:
Rate(Security("USD/JPY"))
If you want to know what the price of an FX contract is under different rate regimes, you can actually set that price and then reevaluate the contract, e.g.
SetDiddlescope() {
Foreach(X, [90, 100, 110]) {
Rate(Security("JPY/USD")) = X // Only takes effect within this scope
Print(X + ": " + Price(MyFXSwap))
}
}
How this actually works is that most object's fields are dynamically recalculated using an early form of functional reactive programming (note that SecDB was mostly built in the 90s). Fields specify their dependencies, and when their dependencies change, the field's value gets invalidated. This is very similar to how ReactJS or Angular work.
Unlike React or Angular though, you can force intermediate calculations to take on certain values as well; for example, in the scope above, you can also force Price(MyFXSwap) to take on a particular value. This is useful, for example, you had a book of securities, MyFXSwap was one of them, and you wanted to see how the price of your book would change.
Even though all the securities are actually in a database somewhere, anything happening locally gets cached to an in-memory database so the performance is pretty decent. The security database itself, btw, was much closer to a pure distributed object store; there wasn't much in the way of querying ability.
To get the benefit, you need the securities models…and the data to feed the models…real-time prices…covariance matrices…volatility surfaces…at which point you're living in a very Goldman world. Not that that's a bad thing but it creates a lot of lock-in.
Also I'm not sure what the upside is to letting people run on-premises, vs. providing cloud APIs based on it (they make it sound like the former).
Just the software, without the models, data, strategists, is kind of like providing a proprietary environment of Microsoft SQL + R.
As I understand it, the closest thing would be something like writing your application for MSSQL. You have a cluster that is storing your data, and with a complex set of triggers, views, queries, etc, you're re-calculating things live.
Unfortunately you program SecDB mostly in proprietary internal languages (not SQL), which while I understand they are moderately capable, they lag behind the 'state of the art' in programming by quite a long way - I wouldn't image it's even on a par with Python, I think somewhere like Lua is probably more accurate.
Caveat - this is based on chatting to people from GS, I don't have experience working with any of this first-hand.
SecDB has been in a class of its own for years now. I've seen and heard of many other banks try to replicate it and failed. It's customizability and performance are very well respected in fintech circles.
Having some friends who were poached for one of those replication efforts, it sounds like an issue of scale, culture, and transplant rejection.
A lot of the advantages of a unified cross-desk risk calculation system aren't realized until it's widely adopted, and it's difficult getting the desks to buy in to changing their thinking to an FRP mindset and adapting all of their existing code.
At Goldman, SecDb was developed by the Strats, who were part of the individual desks in a hybrid tech/quant role, not part of the Tech division. To some extent, SecDb was a bottom-up system driven by the desks who needed it, but in the other firms, it has been the technology divisions trying to push the new system on the desks. It's partly a political problem.
In order to jumpstart their systems, the other firms poached experienced talent from Goldman. Goldman's culture is generally receptive to suggestions and constructive criticism, at least comparatively. These new upstarts showing up and making suggestions to the old guard has not always gone over well at other firms. I'm told one ex-Strat who wrote discount curve calculation code at Goldman showing up at the new firm's technology division, noticing a discontinuity in his new firm's curve, poking around the code in the quant svn repository, and gently pointing out to the author that the same mistake had been made at Goldman several years prior. The response was not so much the expected "oh, hey thanks", but instead the very next day the entire technology division's read access to the quants' svn repository got revoked.
The people who wrote SecDB are now in charge of the technology org at Goldman, and they have presented the stack as a core firm asset in need of constant development and investment to the business, which has -- surprisingly -- accepted this position.
SecDB is not just another IT project with an end date for the business. Ultimately, that is what distinguishes it from all the other copycats on the Street.
That wasn't Dubno but Kirat Singh who worked for Mike at GS. I thin kit was the first of the SecDB offspring with other attempts at BAML and Morgan Stanley. I believe Deutsche bank are also doing something similar.
tl;dr The software is called SecDB. Giving it away is like giving a sports almanac to people that can't travel back in time. Somehow GS ended up using it at the right time, and even had fun speculating on how much to sell it for.
So now Goldman can create artificial risk with its software and further manipulate the market to its will? I think this "gift" fits under the definition of a Trojan horse. Conspiracy maybe, but think about how easy it would be for GS to make a trade based on the numbers its software spits out, before those numbers are public. The SEC has let far bigger things "slip" in the past.
You have no idea what you are talking about. How exactly does GS manipulate the markets to its will? You'd think their balance sheet would look better if that was case..
Goldman Sachs did not manipulate LIBOR because it's not even one of the banks that is asked for LIBOR submissions (they were an investment bank, not a commercial bank).
I'm all for bashing banks when it's appropriate, but it's our obligation to get the facts straight first.
At minimum, GS has done this in the past via political back-patting. Any other means would not surprise me, although to be honest I could care less if I am right/wrong about this particular case. :)
