Investors lose their edge if they have to wait for corporate quarterly reports or monthly government statistics, and they are constantly looking for legal ways to obtain information that other investors won’t discover at the same time.
According to the Wall Street Journal, such information might be found in big data—gathered from sources as varied as satellite photos and Twitter feeds. Consequently, entrepreneurs are gearing up to collect and analyze such data and sell it to sophisticated investors.
One such entrepreneur, writes Bradley Hope in the Journal, is former Google engineer James Crawford, whose company Orbital Insights analyzes the shifting shadows cast by buildings under construction in 30 Chinese cities. The goal, Hope writes, is to give traders independent data about China’s construction boom so they don’t have to rely on government statistics.
Continues Hope, “Orbital is also selling analysis of satellite imagery of cornfields to predict how crops will shape up and studies of parking lots that could provide an early indicator of retail sales and quarterly earnings of companies such as Wal-Mart Stores Inc. and Home Depot Inc.”
Hope adds, “For the parking-lot analysis alone, Orbital bought one million images from satellite companies and built computer systems to produce possible trading indicators out of the data.”
However, he quotes Paul Rowady, a senior analyst at market-research firm Tabb Group, as calling big-data analysis-based information experimental, cautioning that turning it into a trading indicator presents a huge challenge.
Nevertheless, Hope reports, Orbital, based on parking lot images, accurately predicted last week that Ross Stores would report better than expected results for the third quarter.
Of course, you don’t need satellites to find out how many cars are in a retailer’s parking lot; you could hire an earthling to go out and count them, and he could even sneak into the store to monitor the prices at which merchandise is sold. This is somewhat the approach taken by Premise Inc., which, Hope reports, “…makes small payments—often in the form of credit for cellphones—to people around the world who monitor prices of goods, giving the company an early idea of changes in inflation rates and other economic indicators.”
And rather than pay people even small amounts for information you could just collect freely available gossip—from sources like Twitter. Dataminr analyzes tweets in real-time, “…weeding out spam and comparing information against news feeds, market prices, weather patterns and other data to determine its significance.”
Based on Twitter analysis, the company notified its subscribers that Home Depot may have been a credit-card breach victim “…a full 15 minutes ahead of financial news wires and before a 2% decline in Home Depot’s share price,” Hope reports.
If you have a WSJ subscription, you can read the complete article and view some interactive graphics here.
