Max Bowie: Hidden Indicators within the Data Itself

The Holy Grail of trading is spotting an opportunity that can be exploited before the rest of the market also spots it and piles in, reducing the first-mover advantage and potential profit for early adopters. And with entire subsets of the market data and analytics industry devoted to spotting opportunities early, competition is intense to identify pointers of opportunity hidden in the market data.

Traditionally, market participants have looked to the content to provide these indicators, rather than the supply and demand of the data itself as a commodity, since demand for—and expenditure on—specific market data typically lags the initial trading idea, and billing lags actual usage. However, just as vendors like Genscape and ClipperData realized that understanding supply data about commodities could yield valuable price information, examining the dynamics of price and consumption of market data itself can prove a leading indicator that can point the way to market movements.

For example, German vendor VWD recently expanded the currency forwards volatility data it sources from Tullett Prebon Information, in response to demand from corporate treasury clients in Europe for trading with customers in overseas countries. Arguably, this demand indicates that they believe business will increase—and specifically, that it will increase outside the Eurozone. Perhaps companies envisage a new target audience opening up overseas, or that an economy with cheaper labor will steal China's manufacturing crown and become their primary supplier. Or perhaps traders believe a certain business activity will require a specific hedging strategy—all of which could be valuable information for the dealers who would potentially be on the other side of those hedges.

Beat the Rush
In the stock market, predicting demand could allow you to get into a stock before a rush of interest drives up the price. Hence, demand for data itself could be an indicator of demand. The challenge is how to meaningfully gauge demand for data in real time. While it's possible to track how many times a page is viewed online, and track which elements within a page are actually clicked on, it's harder to gauge what people might be looking at on that page—say within a montage of prices for different stocks. And as search tools become more critical to interrogating big data repositories, search terms could yield useful information on what traders and investors are looking for. Think about it: When someone hears about something happening in their chosen stock, their first instinct is to Google the stock plus any other relevant search terms. If only someone was collecting information on Google searches—not just results—and correlating them against the markets!

Actually, someone already is—or, at least, was. Until recently, Merced, Calif.-based Stock Searches App was tweeting examples of how searches for certain companies can be predictive of broader market movements. However, @StockSearches' most recent tweet was soliciting venture funding.

In the stock market, predicting demand could allow you to get into a stock before a rush of interest drives up the price. Hence, demand for data itself could be an indicator of demand.

Information Leakage
Some might call this information leakage, while others use the term to refer to practices such as responding to a request for quote then canceling the trade—effectively "pinging" the market to reveal counterparties' positions—something that start-up fixed-income ATS OpenBondX aims to end by requiring participants to post firm quotes. And as initiatives like this make it (hopefully) harder to sneak a peek at your opponent's hand, firms may seek new ways to figure out where rivals are placing their bets—perhaps by looking at search queries, or by looking at other factors such as demand for underlying data. Like the early analyst-polling practice that landed BlackRock in hot water, might we see firms start polling data vendors about what datasets their competitors are demanding, or see data vendors creating consumption sentiment indexes or heat maps of their most-used content in real time? Because if the majority of your competitors are demanding the same data, perhaps you've missed something that you could have seen coming?