Whatever word you use to describe them—analytics, indicators, signals, or something else—datasets that provide some kind of directional indication, rather than just a static data point, are among the most valuable to any trader, analyst or investment professional.
The form these take can vary, but what they all have in common is the ability to deliver more immediate benefit than their static sidekicks, allowing users to get more value out of the data, while having to put less effort into creating a signal of their own (though they can equally overlay different signals themselves to create a proprietary indicator, if they don’t mind the extra work)—then all they have to do is execute swiftly enough to make good on the data’s inherent promise.
For example, the Chicago Board Options Exchange’s Volatility Index—known as the VIX index, and sometimes as the “fear index”—is a significant and widely quoted barometer of market sentiment. However, CBOE realizes that users could gain even more value from the VIX—as well as the exchange’s other options and volatility data—with access to more granular analytical tools. One such set of tools are those offered by Chicago-based volatility analytics provider Livevol, which the exchange acquired last week to gain full control over its direction and the combined offerings it could offer to clients.
For those facing a different challenge, there’s value to be found in comparing one dataset to another, such as firms trading on Liquidnet being able to use Interactive Data’s Continuous Evaluated Pricing as a reference price to support their own price formation process—not to mention for best execution—when submitting orders to the marketplace, rather than relying on dealer runs or potentially stale prices. Instead, firms can compare Interactive Data’s price to their own or to dealer prices to arrive at an accurate and advantageous trade price.
Similarly, Deutsche Borse-owned index provider Stoxx has developed a series of what it calls “True Exposure” indexes that aim to more accurately reflect the geographic dispersion of a company’s revenues, rather than assuming that where a company is domiciled is also where its revenues come from. The aim of the indexes is to allow investors to see which regions and countries they are really exposed to. For example, if you invest in a US company that sells most of its products to Africa or China, in reality you are far more exposed to the African and Chinese economies than to the US market.
The vendor says it will license the indexes to third parties, such as exchange-traded funds sponsors, to create investible products that fill the gap between the True Exposure values and corresponding values for countries or markets from other indexes—though if a firm finds the indexes significantly more accurate than incumbent benchmarks, it could conceivably arbitrage the difference between them.
Of course, in some instances, there’s more value to be gained from exploiting similar characteristics between datasets, rather than looking at their differences. For example, by allowing clients to input their own custom data fields into its Mint database, company fundamental data provider Bureau van Dijk is enabling users to leverage data types used in other applications—such as CRM systems—as factors when mining Mint for information.
Of course, key to any analysis are the tools that allow users to view and compare data. In CBOE’s case, Livevol will play a key role in allowing users to do more with the exchange’s datasets. But for many, spreadsheets remain the most-used analysis tool. Hence, for startup economic data provider Quadrant, while distributing its data via eSignal is an important development, an Excel add-in is perhaps even more critical to attracting the types of institutional end users that the vendor sees as its main audience.
So when it comes to data, pour on that sweet stuff, add a dash of analytics, and dig in.
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