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> Didn't get the job.

You dodged a bullet. I worked for CIQ from 2003-2007, it was not such a great time. (I recently reminisced a bit here: http://mcfunley.com/manual-delivery)

At one point I was offered a job with Bloomberg that I didn't wind up taking. In my last interview with a director, he described an experience he had rewriting quite a bit of the Bloomberg terminal as a modern (for the time anyway) Windows app as some kind of skunkworks project. He said he was nearly fired for this. His superiors explained to him very slowly that although the terminal looks like obvious insanity to a tech person, it's embedded in the culture in finance. People like it in part because it's insane. It's hard to attack this with modern methods.

One other giant stinking reason it's really hard to innovate here is data. All of these companies are vertically integrated. CIQ, for example, is (or was back then, anyway) a tiny shim of a crappy tech company in New York and thousands and thousands of people doing data collection in India. The data is the product. Initially CIQ was just the website, and they bought their data from competitors. As they became successful their competitors shut them down and they had to scramble to replicate datasets by themselves.

I tried to implement a back button for Bloomberg while I was there. I came up with a few hacky prototypes before giving up, and never showed it to anyone. The software just wasn't designed for this.

Could you give me a range of how much a dev can expect to earn at bloomberg? I'm curious because currently I'm a client (front office finance) but by next year I hope to get a tech degree and job. I'm just bracing myself for what kind of pay cut i'll need to take.

Yes, and in fact if you look at the job boards you can get a picture. I am going to speak from what I saw two years ago.

If you teach devs in their classes you can get a starting salary of around $150k. That's a tough team to get into, since it's one particular team. If you are a developer in general you get around $80-120K starting. I got $95K straight out of a master's program.

Like any other company, a lot of it has to do with their commission to the recruiter that they pay. If you can somehow apply without a recruiter and have them really like you, you can probably get a larger salary.

If you stay for years then over time you'll be making more, probably around $200-300K. Unless you're really instrumental to the company, then you'll be making $500k probably. Still not as much as a trader or quant getting multi million dollar bonuses to stick around. But definitely good. Their company is a meritocracy, and if you want to keep one thing in mind, it is this: the more good work you do and the more indispensable your work is, the more you will be able to ask for in a couple years. Making yourself really indispensable is the trick there, and it's very possible.

Actually my advice to you is this: if this is a whole year away, look around and see what companies you like and form connections with hiring managers WITHIN that company, rather than external recruiters. How? I don't know, get to know employees and then have them put in a good word. They get a commission actually for introducing you, but it's nowhere near what a recruiter would get.

Thanks, man. This helps.

Bloomberg now has a back and forward button, as well as a drop down to go between recent commands/pages

Great thoughts here, and funny story on Cap IQ. Speaking of which, Cap IQ is exactly an example of positioning away from the Bloomberg terminal (with a core initial focus on investment banking as opposed to trading). Unclear whether there's a big juicy opportunity out there like this, like there was when Neal Goldman and his co-founders started Cap IQ in 1999. And great points on #4 and #5, although there's a whole subsegment (underbelly?) of financial services companies which are more cost conscious and where $20k per year for one user is a real investment. Bloomberg is not going after those as aggressively as far as I know.

good points, and great article! Maybe you know better than I do, were Neal Goldman and co-founders originally Bloomberg guys?

They were all investment bankers. Originally they were competing with Factset and Thomson, not so much Bloomberg.

Not all Bloomberg users are traders though, and that's where I would try to challenge them. I worked on software for many years that was used side by side with Bloomberg. Many of our customers were Bloomberg customers as well -- although our software was a bit more niche and we didn't hit the heights that Bloomberg did. But when I doubted if we were in the right business, I would look over to Bloomberg and convince myself that the money was there for the right products.

While Bloomberg has almost any conceivable piece of data in real time, what they were missing was presentation. For instance, if you wanted to make a presentation to your board which demonstrated your value as a money manager, you'd have to leave Bloomberg to do it. That's how we were able to share space with them. But I've heard rumors they are moving in this direction now.

I also agree with the author that the data is really the lynch pin. Some commonly used data can be very expensive to acquire if you are able to get it at all. For instance try finding out what stocks and weights make up the Russell 2000 index (and then legally redistribute that data). We were fortunate in that we got in the business when data vendors were willing to negotiate with small software vendors. And much of the value we offered was in those accumulated contracts.

Once those contracts are in place it is very difficult for either side to cancel them without pissing off their customers. For instance a couple years ago FactSet and Morningstar got into a spat and FactSet's contract to provide Morningstar data wasn't renewed. All hell broke loose on both sides. They made a deal. Data is pretty big chasm for a startup to cross. And users are particular about what data vendors they use, even for nearly equivalent products.

There have been some reasonable exits in the financial software business that don't get much play in the Valley. For instance BlackDiamond sold their reporting package (again presentation) to Advent in San Francisco for about $70million and eVestment has been taking on investment and growing like crazy. But neither of those companies competed head to head with Bloomberg's core business. But they are big enough markets that I could see Bloomberg wanting to grow into them.

In general, if you want a slice of the market that Bloomberg is in, I don't think it would easy to do it head on over data. You have to outflank them where they are weak, and hope to chip away at their mindshare that way.

I never found presentations that hard. For most presentations I kept an Excel template with the BBG Excel plugin, which would then be linked by Powerpoint.

But I do agree with the point that not everyone is a trader. The quality of a lot of macro data often wasn't there. For this I also had a Datastream terminal, which excelled in longer term macro data.

Certainly Excel works for many people, but there was a significant number of users who wanted a vertically integrated presentation/reporting platform. I think there is still room for innovation in this area.

I agree that there may be space for vertically integrated presentation/reporting platform, but do you think this space is as lucrative as the actual data streaming? My guess would be that financial services customers would be very price insensitive to mission critical/directly revenue generating data/analysis (hence, Bloomberg's subscription costs) while a reporting platform would be just a nice plus but a much harder sell. Thoughts?

Presentation is pretty important in much of the business because that's how the products are sold and fees justified.

Let's say your firm trades bonds. Your product is your expertise in trading those bonds, and you have to sell that expertise. How are you going to do that? Much of it is still reputation, but the days of closing a pension fund with a few martinis and your good looks are coming to an end. You have to have the numbers to back up your claims.

> For instance try finding out what stocks and weights make up the Russell 2000 index

This actually sounds like a fun little linear algebra problem.

You might be able to do something with the correlations of the index returns and stock returns, but I doubt their would be enough information there to depend on results.

"Reputation. Even if you create a perfect replica of Bloomberg, would I stake my clients money on your track record?"

It's not just your clients' money, but your own safety. If you lose money for your client while using an unproven technology, the client might try to sue you for negligence. Using the system that's "industry standard" would be a defense against that.

Great points. I think #2 (reliability) and #3 (reputation)are really key here.

I would argue that there is a caveat to #1. Agreed that a MVP for a Bloomberg replacement wouldn't work unless you had everything Bloomberg had and more (in which case, it's hardly an MVP and good luck). That said, I think an MVP for a niche fin-tech data product that Bloomberg does not have would work if the sales pitch is that I use your product in addition to Bloomberg. If you offer me an edge by providing data (or analysis) others don't have, an MVP would be fine. Heck, some traders/funds would pay for just a csv file if it contained unique (but directly useful) financial data/analysis (an obvious example that may have had potential 5 years ago was sentiment, although now everyone and their dog is offering that and it's not entirely clear there's direct value to it). I think the very fact Bloomberg can look like its "from the 1980s" just reflects the needs of the market it serves. Wall Street doesn't put great value on pretty interfaces, ease of use, or anything other than direct value add to their revenue generation process (ie. investing, pricing, selling financial products, etc.). Tell me how your product makes me more money today. I think any fin-tech startup needs to be driven by that philosophy if they want to succeed, I don't see how you'd convince a trader that the fact your app offers a nice interface or interesting but questionably actionable analysis is any real advantage if the other guy offers analysis or data that is directly applicable.

Another thought: while disrupting pricing data would be very difficult (given the speed + accuracy required + relationship with exchanges), what about other financial data like fundamentals/accounting/relationships data? That data is free - it's all on the SEC's EDGAR (and it's far more than just financial documents, there's plenty of data on individuals too). Would Fact Set or Capital IQ, for instance, have more competition if the SEC had API/machine readable data? There has been some effort through XBRL to do this - although the percentage of filing actually available in that format and the lack of consistency in the format (in some cases, there's at least several hundred 'tags' for the same or similar financial line item) makes any large scale data processing from EDGAR a massive undertaking.

"the lack of consistency in the format (in some cases, there's at least several hundred 'tags' for the same or similar financial line item) makes any large scale data processing from EDGAR a massive undertaking."

Izyda, you are absolutely correct on the issues with XBRL. I'm the co-founder of a company called TagniFi that is working on a solution. We have a standardized dataset that makes comparing this data across companies, industries and sectors possible. We are in beta so you are welcome to check out for API for free: http://www.tagnifi.com

This looks very cool - I will certainly sign up for the beta. I think there is real potential in this space.

The only concern - and maybe you have a solution - I have is that to my knowledge, XBRL has only been required on 10K's and 10Q's since around 2009 (I may be incorrect, 2010?). As someone involved in research with financial data, there's really no avoiding using pre 2009 data. Parsing that from raw text files is even harder than XBRL - is TagniFi able to do that as well? (I've perused your website but haven't found the answer). Unfortunately, without that capability, I'm forced to rely on services like Fact Set at least partially.

Thanks for the feedback. You are correct that the lack of history is an issue for us but we have to start somewhere and the cost to collect non-XBRL data is really high. The timing of the available history in XBRL depends on the size of the company. XBRL was phased in starting in 2009 with the largest 500 companies filing their 2010 10-Ks in XBRL. These 10-Ks generally had income statement data back to 2007 so that is where most of our data starts on the larger companies. The next largest 1,500 companies started filing in 2010 so their data generally starts in 2008. The remaining 9,000 companies started filing XBRL in 2011 so their data generally starts in 2009. This means we have 7 years of data for the largest 500 companies, 6 years of data on the next largest 1,500 companies and 5 years of data on the remaining 9,000 companies. Since the cost to go back and collect this data manually is really high we are going to focus on building the deepest datasets (footnotes and industry-specific) to offset the lack of history.

"(an obvious example that may have had potential 5 years ago was sentiment, although now everyone and their dog is offering that and it's not entirely clear there's direct value to it)"

Presumably the sentiment you are referring to is real time financial sentiment derived from online chatter. A source other than online chatter wouldn't yield enough data in terms of time granularity or symbols, i.e we've had sentiment data for decades in the form of the AAII and NAAIM, they just weren't useful as data sources for active trading.

5 years ago a statistically significant sample set of investors and traders wasn't chatting online to yield actionable data. Today there is, the data has alpha, and smart money is trading on it.

No, actually, I am referring to real time sentiment analysis of any kind - services such as http://www.dataminr.com/ or http://www.infotrie.com/ do this today mostly using online chatter, which you correctly point out probably would not be possible 5 years ago. However, real time news sentiment analysis would have been possible and relatively novel 5 years ago. For instance, Columbia's Paul Tetlock published a very interesting paper in the Journal of Finance in 2007 ago on the subject here: http://www0.gsb.columbia.edu/faculty/ptetlock/papers/Tetlock... (he used words from a Wall Street Journal column). If you read the paper, you'll find he used daily data over the 16 year period 1984-1999. While this is not of the same granularity you could get from services like InfoTrie or Dataminr, it certainly is of high enough granularity to trade on (and could have been done 10 years ago apparently!) and appears more useful than AAII or NAAIM.

I am interested in your claim that the data has alpha and smart money is trading on it. I have been looking for any peer reviewed, academic articles actually documenting that alpha (ie. by anyone except the people trying to sell you the data). One such paper I found was Bollen et al's http://arxiv.org/abs/1010.3003. From my understanding, there are several problems with the methodology (I could find a rebuttal paper I read if you're interested) and the methodology was used in Derwent Capital - although the fund only traded it for 1 month: http://venturebeat.com/2012/05/28/twitter-fueled-hedge-fund-...

Care to point me to anything else like that?

DataMinr is an event detection service not a 'real time sentiment'

infotrie does sentiment analysis on news stories they also mix this news sentiment with social media sentiment. This is a muddled approach and not pure real time sentiment.

Let's back up a moment. You wouldn't expect Gallup to have accurate surveys of the presidential election by processing news articles and blogs. They poll individuals in brief snapshots of time. Polling for sentiment is the same thing. News articles and blog posts are amplified opinions of a small set of people, they are a poor substitute for direct measurement of many many people.

The Bollen paper is widely discredited in our space. Derwent licensed the technology and subsequently ran into trouble because the tech and data was not sound.. though Bollen's initial theory was correct.

Not peer reviewed but you can see a few papers Deltix published documenting alpha:

http://www.deltixlab.com/research/an-automated-trading-strat...

Interesting points...

News articles and blog posts are amplified opinions of a small set of people, they are a poor substitute for direct measurement of many many people.

You might be correct (sounds very reasonable) but I guess the question is why do I necessarily care about directly measuring many many people? What if loud, amplified opinions are actually better indicator of market momentum?. Tetlock's article suggests that those amplified opinions actually do contain useful information. Again, I have yet to find any conclusive evidence that measuring people's chatter actually ... matters.

Derwent licensed the technology and subsequently ran into trouble because the tech and data was not sound.. though Bollen's initial theory was correct.

Right - I think there are more than a couple complaints about his paper. Why do you say his initial theory was correct though? If I recall correctly, his initial theory was that social chatter contained market information that could be extracted using neural networks and used to predict short term market returns (like a few days forward). I haven't really seen anything along the same lines (especially using his approach of neural networks) anywhere - although the articles you link to might be considered similar.

I am just reading through the articles you posted from Deltix now, sound interesting. One problem is that because of the relatively novelty of services like PsychSignal, the data does not go back as far as traditional indicators (this was a problem with Bollen's paper as well). When you say you have impressive alpha, sharpe, or whatever for 6 months.. that does not really prove much, especially in the eyes of academics. I'd love to replicate or work with this data presented in Deltix - but given the data is proprietary, that's difficult to do.

side note: This was just mentioned in the Wall Street Journal yesterday, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1807265 claims to find signal in blog posts. That's not to say measuring many people's chatter wouldn't work as well or better though. Also just heard of paper today, so no guarantees about quality but maybe someone finds it interesting.

Re: "shipping a csv" -- this market is exactly what the Bloomberg App Store caters to. Bloomberg takes care of all the distribution, billing, discoverability headaches for your niche play and you just focus on the product. The nice thing about the store is that all apps are monthly recurring fees. There are no 0.99 downloads and some are quite expensive.

totally agree - and probably why if all you have is a niche play, even if it has potential to be extremely profitable, attempting to replace the Bloomberg App Store is like trying to replace the Apple app store for one mobile game.

You really nailed it with #5.

Not only that, but Reuters data services are questionable as well.

I can confirm this wholeheartedly

I work for an asset management firm designing the back-end architecture including interfacing data feeds and Reuters gives us issues at least once a week.

They recently updated their Eikon app and the addin was auto-disabled by excel because Excel deemed it as unstable.

I contacted support and they said they were aware of the issue.

Blows my mind that they could release a software update that breaks a critical part of their offering - and not even send an email to clients telling them how to fix an issue that they caused (forced update) and knew about!

Bloomberg support is excellent but I disagree it is as significant in decision making as some commentators appear to imply. Many shops will have internal support able to handle the majority of first line questions, then Bloomberg support is relied on more for edge cases or tier 2 support. Especially at the senior (decision makers) level they may have someone contact Bloomberg on their behalf; so the degree to which support is better is not punishing competition.

Tangential to 5) there are numerous financial services firms of various scales, and even the mid-sized and small shops (for whom $20k/yr + exchange fees is not a write-off amount) disproportionately use Bloomberg. I think squigs25 identifies some of these reasons, I would highlight and add the following:

1) Network effect - Even if you build a better mousetrap capital markets are highly connected. On the sell side we may adapt our technology choices to our most significant clients on the buy-side to provide as seamless a service as possible to clients. Bloomberg messenger has been mentioned by many people and that is a huge factor in our decision making, but simpler things contribute too:

1.a) Consistency - If my client calls we're discussing a trade or security it is a significant advantage in seeing the same thing they see. Be it VWAP on the day to 6dp, the order we're looking at published research, recent trades, if we're looking at the same thing the service I can provide is improved. My service and execution is how I differentiate myself. This relies on us using the same system

1.b) Connectivity - I can have a Bloomberg EMSX client able to send trades to me in ~5 minutes with no exaggeration. Similarly if they want to receive our IOIs or TA (basically advertising from the sell-side to the buy-side) and have an acronym - the connection between the systems already exists and I can find and target your specific acronym in under 5 minutes.

B) Incentives - Smaller shops are, in my experience, less likely to mandate technology to sales/trading/research. It is also unlikely that my personal technology expenses are tied to my comp. Even if cost is significant to the firm it may not be to the individual who have influence

C) Inertia - Capital Markets are not Technology firms. Technology exists to facilitate a job and if it does that well enough there is scant appetite for change. No one wants to re-learn tools that have been familiar for years. They want to even less when that is fundamentally not seen as part of the job, it's a facilitator and should be easy and convenient as a result.

Reliability cannot be emphasized enough. The uptime % we expect (and Bloomberg delivers) is exceptionally high during and around market hours.

(source: work on sell-side trading desks)

What do you think about Factset's chances?

Factset's main defensive position it that they have direct feeds from most of the money managers and can do attribution analysis on their trade data overnight. That might not be as hard as getting the market data Bloomberg has, but still a pretty big step.

Also the performance attribution that FactSet provides requires constituent data from the major indexes. Money managers are particular as hell about their indexes, so you can't just provide generic indexes, unless you first convince them that the generic indexes have value. That could take years.

hahaha i lol'd :)