Recent regulatory developments have important implications going forward relating to institutional research payment models. These developments will also likely impact publisher strategies for research content structure and delivery. Key findings include:

Our organization acknowledges and is grateful for the insights of Neil Scarf from Frost Consulting and Richard Brandt from Quark, which sponsored this study.

These important emerging business drivers are key to the underlying technology discussions within RIXML.org working groups, where, topics including content componentization, new delivery channels(mobile suite), social media delivery, implications for Big Data, others, are of increasing importance as this "sea change" unfolds. We encourage and welcome members' participation in these working groups.

Identifying research content packaging and delivery opportunities through the use of Social Media is gaining traction with our Technology working group. We are grateful to Sara Noble for leading this effort. Key areas of focus include:

We welcome members'(and domain experts') input on these topics.

Imagine that you make and sell a large number of products, each of which has hundreds of pieces. To package these products, you have three choices:

Which would you choose? Which one do you think your potential customers would prefer? In this example, the packaging makes a huge difference in the usability of the product itself. The product can exist without good packaging, but it becomes far more usable – and valuable – with it.

What is this product? Investment research. What are the pieces? All of the valuable information – company information, financial data, recommendation information, and analysis – that each report contains.

XML is sophisticated packaging for electronic information. Furthermore, RIXML is sophisticated packaging customized specifically for investment research.

To apply RIXML to a particular piece of research content (such as a research report or an audio file of a morning call), the relevant tags along with the information that is described by these tags are formed into a tagging file. This tagging file is called an instance document. This instance document does not replace the research report or audio file. Instead, it travels along with the research item, providing the necessary tagging to the desired data repositories. Within the instance document are the tags and content that describes the content in the research item (for example, ) as well as the tags and content being used to uniquely identify the research item (for example, Strategy_Daily_20120512.pdf).

By standardizing a common set of tags for the information that is generally included in research content, such as security identifiers, industries and sectors, ratings and recommendations, asset types, etc., the creators, aggregators, and consumers of investment research are able to vastly improve the process for getting the right research into the hands of the consumers who want and need it. In addition, this advanced level of tagging and access to individual contextual elements allows for a new generation of alerting mechanisms, navigational frameworks and enhanced user interfaces, and delivery to mobile devices. The remainder of this Implementation Guide contains details on implementing RIXML, core concepts behind RIXML, and details on the schema itself. These sections provide information that is critical to understand in order to begin to leverage the strengths of RIXML.

Interested in joining RIXML.org? Call our Program Office and 212-652-4470 or email us at to=This email address is being protected from spambots. You need JavaScript enabled to view it." target="_blank">This email address is being protected from spambots. You need JavaScript enabled to view it. for additional information.

As we build out our Events calendar, we welcome direct participation in members’ events, as part of panel discussion, topical roundtables and e-Seminars/Webinars. Related, we also encourage members’ direct contributions to our recently revamped web site(www.rixml.org), through the additions of whitepapers, RIXML.org experiences/forums, in the spirit of promoting/adopting the schema and best practices.

ALL of our members are part of the Marketing & Membership committee !

PLEASE NOTE: This viewpoint is entirely my own and neither the official viewpoint of RIXML.org northe viewpoint of any of its member organizations.

Remembering "The Really Big Shoe" and Anticipating "The Really Big Data"

I realize an attempt to tie together what could be a significant development in the Research space to a significant milestone for a past television/musical event is quite a stretch to say the least. But, what the heck – chalk it up to seeing signs(however slight and early) of breaking out from what has been an especially brutal winter in the northeast and as a result, perhaps, a rite of Spring: SPRING FEVER---we'll see where this goes....

For those of us that experienced the event firsthand, it is hard to believe that is has been 50 years since The Beatles made their U.S. debut on national television, first appearing on "The Ed Sullivan Show" on the night of February 9, 1964, in front of an unheard of 73 million people. This was certainly the jumping off point for the Fab Four as they swept through New York City, as a NYTimes.com article highlights, "on the way to a unique kind of fame that was both instant and enduring." This T.V. event, however brief, also proved to be a welcome diversion for our country, having gone through the tragic loss of President Kennedy just a few months before.

I still remember details about the event that night. At the ripe old age of 9, I got caught up in Beatlemania—loving their music, although that night, I could not hear a single note over the screams of my two older sisters---that just went with the territory.

An always animated Ed Sullivan only added to the fun---and often referred to any given T.V. broadcast, and slate of guest stars, as part of a "Really Big Shoe", in Ed Sullivan-speak. Most would agree that the Beatles debut broadcast had to be the biggest of the "really big shoes." As they say, from that momentous occasion, "the rest is history."

So, as an ongoing die-hard Beatles fan, how might I weave this theme into something that would have anything to do with the Research space? I will give it a shot---perhaps, through Beatles' song titles...

In past newsletters and as often discussed in RIXML.org members' meetings, we are witnessing a Revolution in the Research space---changing payment models, heightened regulatory scrutiny, leveraging emerging technology for innovative content packaging and delivery and examining more closely, topics relatively new to Research – one such topic that has Come Together lately is examining the potential for Big Data Analytics.

In a recent blog post from Gabriel Lowy of tech-tonicsadvisors.com Gabe mentions that "major sell-side and buy-side institutions are trialing new software that leverages cloud infrastructure and big data analytics to model markets and stocks. Massive data sets can include macro news from anywhere in the world such as economic variables, political events,"(very timely "Back in the U.S.S.R.?) "seasonal and cyclical factors. These can be blended with company-specific events, including earnings, financings or M & A activity. Newer data sources, including Social Media, GPS and spatial, can be layered into models. Users can input thousands of variables to build specific models for an entire market or for an individual security."

Seems to me, the potential arrival of Big Data Analytics in the Research space may be on to Something.... Because:

Gabe Lowy mentions that the advantages to both sell-side and buy-side are significant, namely, lower costs(time and expense) through leveraging cloud based infrastructure and analytics software, improved accuracy through machine learning and predictive analytics techniques and enhanced competitiveness using tools that compete with the largest technologically advanced hedge funds.

Spreadsheet geeks are so Yesterday. Lowy mentions that, with the emergence of these new tools, the analyst skillset must evolve. These new "Data Scientists" have a Ticket to Ride – Lowy adds that data discovery and visualization tools will replace spreadsheets for identifying dependencies, patterns and trends, valuation analysis and investment decision making. Rather than Let It Be, these Data Scientists will Act Naturally with these tools, to develop a deeper understanding of client strategies and trading styles(always a Help) in order to tailor their research to individual clients.

RIXML.org, through its technology working groups, and With a Little Help From My Friends, will continue to explore the potential place for Big Data Analytics in our space, at the least, to educate the members at large, in the process.

In the meantime... it’s been a long cold winter... Here Comes the Sun !

"In every walk with Nature one receives far more than he seeks."
   John Muir

Quarterly Updates

Upcoming

January 10, 2020 - 9AM EST:

Technology Working Group monthly meeting

 

January 23 - 10AM EST:

RIXML Quarterly Meeting

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February 7 - 9AM EST:

Technology Working Group monthly meeting