In our aim to provide you with the best quality, institutional level data we're now working with Estimize.com to bring you crowd-sourced earnings estimate data.

Each financial quarter companies publish their earnings per share (EPS) and revenue figures to investors. When a company performs worse than expected, often the share price can fall dramatically, and vice versa.

Each time there is an earning announcement the Estimize.com community of 13,000 users makes predictions on what the Earnings Per Share (EPS) will be, along with the Revenue for the quarter. On average they are more accurate than Wall Street analysts 69% of the time!

For the first time you can freely use historical sentiment data to design trading algorithms! With QuantConnect you can now access estimates from the crowd into your algorithms to design powerful sentiment strategies. Imagine testing how a bad earnings announcement affects the stock price!

In your Initialize() Method: 

AddSentimentData(SentimentDataType.Estimize, "IBM");

And then handle the events using the OnEstimize() handler: 

public override void OnEstimize(Dictionary estimates) {

//Incoming IBM Estimate

Debug("IBM EPS:" + estimates["IBM"][0].Eps+" Rev:"+estimates["IBM"][0].Revenue);

}

See the full documentation at QuantConnect.com/docs