Unique Data: The Edge Capital Markets Firms Need
We’ve been hearing about the importance of Big Data for what seems like decades. But often, investment banks approach data projects the wrong way. The focus is more on getting ultra-fast market data, rather than new data like transactional, referential and social data for a more complete view of investment opportunities. Budgets can also be a stumbling block, with discretionary funds directed to the overwhelming demands of complying with regulations such as Dodd-Frank and Volcker Rule.
Prioritizing data projects correctly is a strategic imperative. Here are three reasons why:
1. Data volumes continue to grow exponentially
After sifting through near-unmanageable volumes of data, investment banks and asset managers must invest in ways to use all this data and, more importantly, find meaningful patterns that deliver insights others don’t have.
2. Competitive insight can yield giant returns
In the trading business—one of the most competitive of all industries—it’s all about a firm’s ability to differentiate itself. We all know that the trading business has evolved (some say devolved, but I’ll refrain from that debate for now) into one where technology trumps human intelligence, and quantitative process overrules fundamentals. In some ways, technology levels the playing field among the large firms, each investing hundreds of millions in trading technology every year simply to keep pace.
So if trading firms have similar technology and use the same data, the tide will rise and all firms will rise with it at the same rate. In trading, a zero sum game doesn’t satisfy. It’s relative growth that matters, leading one firm to win more frequently than its competitors. The winners are those who have the best inputs into their technology. Finding relevant and unique data—either raw or derived—is a winning formula.
3. Access to unique data enables well-informed investing
Reference data that offers insightful information about companies that form the core of investments—equities or fixed income securities—is moving to the front of the line for investment models.
This data can often identify a leading indicator for an investment position. For instance, having insight into the payment history for a private issuer of bonds can enable a trader to assess its price more precisely than other bidders. It’s about getting an early alert about glitches in a manufacturer’s supply chain that can dampen future earnings projections and trigger a ‘sell’ signal on its stock—before the rest of the market figures it out.
We know the data used by most trading firms is indeed quite similar. However, all traders remain on the lookout for data they can uniquely deploy to separate from the pack. Right now, the differentiating factor for many of these firms is in the models used to derive new data. That is the secret they count on to achieve alpha returns.