Finding alpha, while never easy, has become an ever-greater challenge in today's information-rich electronic markets.
Some observers posit that the proliferation of real-time data and tools that allow data to be analyzed quickly leaves little alpha -- the additional return above a certain benchmark that everyone is seeking -- for fund managers. Others say alpha has more to do with luck than any specific strategy or unique market insight. After all, it's better to be lucky than good.
Some fund managers have more luck than others, which is why they all continually seek ways to improve performance and returns. With everyone having access to real-time news and data, market participants are looking for new ways to gain an edge. After all, although "past performance is not an indication of future results," almost every investor makes fund decisions based on past performance. Thus, funds do everything to improve performance by increasing alpha.
In order to find the ever-elusive alpha, asset managers are looking at more data than ever, including real-time news feeds, sentiment data and even social media data from sources such as Twitter. These newer data sources, unlike typical market data feeds, aren't structured, and they require new technology and analytical skills to capture, crunch and turn the data into valuable information.
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While some of the largest asset managers have the resources to invest in building new data stores, analytical tools and complex algorithms that can make sense of this data, many smaller fund managers need help from off-the-shelf data analysis tools and database technologies.
Over the past few years, the quality of these tools has improved and the variety increased, making them viable options. Oracle, SAP, SAS, StatsPro and newcomers to the market, such as EidoSearch, all offer products in this area. And big data tools, such as Hadoop and Hive, also are helping funds looking to improve their data capabilities with a combination of building their own infrastructure and buying analytical packages.
However, while the technology required to analyze data has changed, the basic principles of data analysis for finding alpha remain the same, points out Matt Samelson, principal at capital markets research and advisory firm Woodbine Associates. Today's data analysis challenges require new skill sets and tools to handle the massive amounts of data. These tools let analysts spend more time actually digging into the data, rather than collecting and scrubbing it as they did in the past, Samelson notes.
So, will newer technologies help asset managers find alpha? Unless you're consistently more lucky than good, using newer data analytics tools seems like your best bet.
On another note, Samelson is also an Advanced Trading Thought Leader who will help drive the online discussion at the Advanced Trading Community. You'll hear from him and his colleagues at Woodbine in the Street Cred column in our digital issues and also online at the advancedtrading.com community.