TD Ameritrade clients can now create a more fully formed view of individual securities through new earnings analysis capabilities on the thinkorswim ® trading platform from TD Ameritrade, Inc. 1 The new capabilities streamline research by combining historic data investors use to analyze a company poised to release earnings into a single visual, including consensus expectations from Estimize. 2 Through a new relationship with Estimize, thinkorswim users can view a security's projected range of earnings and revenues from third-party Wall Street analysts along with crowdsourced estimates for past and upcoming earnings periods. Estimize is an open financial estimates platform that aggregates fundamental estimates on more than 2,100 U.S.-listed securities from a diverse set of more than 3,000 independent, buy-side and sell-side analysts, private investors and students. The Estimize model has been validated by researchers from the University of San Diego, Rice University, Michigan State University, and University of Kentucky 3. In fact, the Estimize consensus has proven to be more accurate than comparable sell-side data sets over 74 percent of the time. The company was named one of the world's top 10 most innovative companies in finance in 2014 by Fast Company. "We're kicking earnings analysis into overdrive for our clients as part of our mission to level the playing field," said Nicole Sherrod, managing director of trading, TD Ameritrade. "The impact of Estimize has been well-documented by academics. Combining Estimize data with our expertise on options trading platforms and post-earnings price movement can revolutionize how retail investors trade earnings." Additionally, TD Ameritrade has made it even easier for clients to conduct in-depth historical analysis on individual securities. Investors can go back as far as two years and make quarter-by-quarter comparisons to get a more complete picture of a security's activity. Earnings events from each of the previous eight quarters can be viewed side-by-side, along with five days of pricing and volatility data before and after the event.