Estimize Readies Factor Model, International Estimates, Indicators

Within the next two weeks, Estimize will make historical data available for quantitative analysts to test. Within two weeks after that, the vendor will make the data available for purchase via its API, and within a further two weeks, will make it available within its Earnings Edge stock screener tool.

The factor model compares three data points—Estimize’s mean and Select Consensus (i.e. weighted) crowd-sourced estimates, and the Wall Street consensus, sourced from Zacks—to create values for pre- and post-earnings drift, which respectively provide indicators of what investors believe a company’s earnings will be in the two weeks before an earnings announcement, and how a company’s price is expected to change in the three days after an announcement.

The vendor began using the model available over the summer to demonstrate to prospective clients how they could better test its data, and “had a lot of success” with this approach, says Christine Short, director of media and PR at Estimize, adding that the company became cash flow-positive in August. “We used to give clients a dump of data… but how many data scientists do these firms have to perform a lot of analysis themselves?” she says.

Making it easier for firms to find alpha in Estimize’s data also shortens sales cycles, as does the fact that the vendor now has almost five years’ worth of historical data, which is the minimum requirement for historical datasets at many firms, Short says.

Next year, the vendor plans to expand the coverage of its earnings estimates to Europe and Asia, creating its own crowd-sourced datasets for each region, and partnering with third-party providers of local estimates to provide the equivalent of a Wall Street consensus.

Meanwhile, in the fourth quarter of this year, Estimize will expand its range of crowd-sourced economic indicators by adding 16 new indicators covering the UK, France, Germany—as well as EU-wide indicators—Russia, Brazil, China and Japan. These range from unemployment figures, inflation rates and GDP, consumer price indexes, balance of trade, manufacturing PMIs (purchasing managers’ indexes) and retail sales to consumer and business confidence figures.

Short says this expansion is based on client demand, especially for data on China and Asia, from firms in China and others looking to trade the Chinese market, adding that the majority of indicators are very similar to the US indicators the vendor already provides, with a few regional differences.

Though there is no “Wall Street Consensus” for indicators, making these harder to benchmark, Short says Estimize is looking to further expand this dataset, and expects to offer around 80 indicators by year-end.