Opening Cross: If You’ve Got It, Flaunt It

They say it takes money to make money. Not strictly true, as many an entrepreneur will tell you, but it demonstrates the point that it is much easier to achieve something when you’re already part of the way there.
For example, with attention turning to pricing over-the-counter and illiquid instruments in a more real-time manner, who better to develop a streaming terminal for OTC data than pricing and risk management software vendor SuperDerivatives, which already prices many of the assets in question, and already receives input data at a higher frequency than it currently distributes derived prices. Hence, because SuperDerivatives has much of the required data already in place, it is easier and less expensive to take the next logical step in development—and indeed, to recognize that next step in the first place.
Similarly, Thomson Reuters last week unveiled a text analysis service developed by its StarMine division to create default probability scores that assess a company’s creditworthiness based on analysis of documents including news stories and financial statements. Were StarMine and the vendor at large not already involved in machine-readable text analysis—though officials say there was no overlap between this development and its machine-readable news and sentiment analytics for algorithmic traders—this opportunity to do something different with data that the vendor already had lying around in-house may never have been spotted.
Likewise, since acquiring machine-readable event data provider RapiData, Nasdaq has been flaunting the feed—renamed the Event-Driven Analytics feed—and making it available in new locations, most recently its primary datacenter in Carteret, NJ. In short, once it had the data, how Nasdaq hose to leverage the EDA feed was limited only by client demand and its own imagination—and in fact, the exchange is already imagining new ways to expand the existing content in EDA. Meanwhile, Standard & Poor’s Indian ratings and research subsidiary Crisil is exploring the potential to expand its proprietary content and analytics, leveraging its acquisition of UK-based analytics provider Coalition, to—like Nasdaq—create an offering with broader appeal.
But, speaking of limiting factors, what about when you don’t have something that is becoming increasingly important to your clients—such as the ability to trade via data terminals? As discussed elsewhere in this week’s issue, if prospective clients say they need something, you have to deliver, even if that means partnering with unlikely bedfellows.
“As traditional ISVs add charts, analytics and algorithms, traditional analytics vendors have to add trading to their front-ends,” says Mike Glista, director of trade routing at CQG and vice president of Continuum, the division that provides enterprise data connectivity and trading APIs to clients—including other vendors. “Something that isn’t integrated just doesn’t work.”
This particular issue is largely—though not exclusively—driven by the need to reduce costs by cutting back overlapping products. Why have a data terminal and a trading screen that also contains the data—which attract separate fees—when one will do. And chances are—assuming a reasonably competent level of content and analytics on the trading platform—you’d pick the one with the ability to trade. Another reason for picking this would be that some exchanges waive data fees when market data is included in a trading system rather than just a view-only display, to incentivize trading, because they know they’ll make money from incoming order flow—which also plays to a firm’s cost management needs.
And against the current economic backdrop, these kinds of circumstances are bound to hand an advantage to the company that can be the first to deliver what clients need. And the companies usually best positioned to achieve that are those with skin already in the game.
So the moral of this story is: if you’ve got it, flaunt it. And if you haven’t got it, get it!
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@waterstechnology.com or view our subscription options here: https://subscriptions.waterstechnology.com/subscribe
You are currently unable to print this content. Please contact info@waterstechnology.com to find out more.
You are currently unable to copy this content. Please contact info@waterstechnology.com to find out more.
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@waterstechnology.com
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@waterstechnology.com
More on Emerging Technologies
Waters Wavelength Ep. 331: Cresting Wave’s Bill Murphy
Bill Murphy, Blackstone’s former CTO, joins to discuss that much-discussed MIT study on AI projects failing and factors executives should consider as the technology continues to evolves.
FactSet adds MarketAxess CP+ data, LSEG files dismissal, BNY’s new AI lab, and more
The Waters Cooler: Synthetic data for LLM training, Dora confusion, GenAI’s ‘blind spots,’ and our 9/11 remembrance in this week’s news roundup.
Chief investment officers persist with GenAI tools despite ‘blind spots’
Trading heads from JP Morgan, UBS, and M&G Investments explained why their firms were bullish on GenAI, even as “replicability and reproducibility” challenges persist.
Wall Street hesitates on synthetic data as AI push gathers steam
Deutsche Bank and JP Morgan have differing opinions on the use of synthetic data to train LLMs.
A Q&A with H2O’s tech chief on reducing GenAI noise
Timothée Consigny says the key to GenAI experimentation rests in leveraging the expertise of portfolio managers “to curate smaller and more relevant datasets.”
Etrading wins UK bond tape, R3 debuts new lab, TNS buys Radianz, and more
The Waters Cooler: The Swiss release an LLM, overnight trading strays further from reach, and the private markets frenzy continues in this week’s news roundup.
AI fails for many reasons but succeeds for few
Firms hoping to achieve ROI on their AI efforts must focus on data, partnerships, and scale—but a fundamental roadblock remains.
Waters Wavelength Ep. 330: AI hot takes
It’s Shen and Reb this week talking about AI and the landscape for fintech partnerships.