Max Bowie: But Can We Still Call It All Data?

Data consumers now must consider an array of new data types and delivery mechanisms if they are to give their traders an edge.

max-bowie
Max Bowie, editor, Inside Market Data

The nature ─ and breadth ─ of what we know as market data is changing, requiring data consumers to consider an array of new data types and delivery mechanisms if they are to give their traders an edge, according to Max.

If you didn't make it to last month's North American Financial Information Summit and subsequent awards evening hosted by Waters stablemates Inside Market Data and Inside Reference Data, then (a) you missed a treat on all fronts-a packed agenda of expert speakers and engaging panel discussions-and (b) you missed finding out which data-related products and services grabbed the attention of the publications' readers.

Worth special mention were the best new data product, the best real-time market data initiative (vendor), and most innovative market data project (vendor) awards, won by BATS Global Markets' BATS One Feed, Thomson Reuters' Commodities Fundamentals content on its Eikon desktop, and Interactive Data for its Continuous Evaluated Pricing (CEP) service, which jointly won with Airex's Airex Market, a new online content marketplace.

While BATS' One Feed is a more traditional example of a new data product, Interactive Data's CEP service is a distinctly new approach to pricing fixed-income securities, while Airex is one of a growing number of players carving out a niche as independent content aggregators.

Changing Nature

These awards demonstrate the ever-changing nature of what we classify as market data. No longer is market data necessarily data from a market, like an exchange or a broker price. Now it includes synthetic prices created to serve the function of a reference price, such as Interactive Data's CEP service as well as all kinds of technical signals, such as those provided by technical analysis software vendor Updata, which has begun offering data from Toronto-based economic data aggregator Quandl as a source for its analytics.

And in today's era of social media analysis and crowdsourcing of data, market data also encompasses signals derived from social media, such as those created by Market Prophit, which ─ with S&P Dow Jones Indices as its calculation agent and Bloomberg distributing the data ─ recently created an index based on analysis of social media chatter.

Like many new datasets, this is a case of revamping an existing data source like an index by introducing a novel methodology, just as how Estimize has revamped old-school estimates with a crowdsourced approach.

And far from the least traditional datasets that we recognize as market data, just as latency figures became an important input to trade routing decisions, network security information such as that provided by Redscan ─ which recently partnered with data consultancy Cordatum to help increase its sales penetration of financial markets ─ is likely to become an equally important "data" signal about the health of a company's network, or perhaps a counterparty's or supplier's infrastructure.

Ready For Launch

Meanwhile, TickerTags, a start-up provider of tags covering mentions of companies or keywords on social media that just closed a round of seed funding, is preparing to launch its online platform for monitoring social media chatter for recognized keyword "tags" that could be indicative of a market-moving change relating to a company or its products.

Having moved from structured price data to unstructured text and sentiment, there's still another level of data that's even harder to derive, but potentially just as useful-visual data that needs to be interpreted by the human eye, then requires computers to be trained to recognize trends or changes on photographs. For example, companies like Genscape rely on a combination of physical monitoring with visual analysis of power stations or oil fields, while newcomer Orbital Insight uses satellite images to estimate data about store sales and crop yields.

A picture may be worth a thousand words, but reverse-engineering that level of value out of a picture is complex. And if these new data types deliver true value, then consumers may not mind them being ─ to quote an old commercial for Stella Artois beer ─ "reassuringly expensive."

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