Event-driven strategies, which analyse the potential impact of events on stock price movements in order to explore returns, are an important type of investment trading strategy commonly used in the capital markets. Datayes provides investors with the data characterized with both the breadth and depth to help generate alpha in the stock market.

The Event-driven Stock Data launched by Datayes takes into account the validity and attention on the part of the events related, as well as their availability. Currently, Datayes Event-driven Stock Data includes market sentiment, corporate behavior, financial reports, institutional behavior and other major categories of events, which are divided into dozens of subdivided types. The Data supports dynamic updating and will keep adding new event types.

Backtesting data shows its outstanding overperformance. Take the example of the Bottom Divergence Event, whose logic is that the stock price reaches a record low in the wake of a drop of more than 30%, but there is a divergence pattern, and the stock price is expected to reverse in the future. Accordingly, a historical data backtest was performed for the period from January 2010 to June 2023. Using the CSI All Ordinaries Index as a benchmark, the return from T+1 to T+60 was 8.11%, with a winning rate of 64.71% and a profit/loss ratio of 1.7031.

The Datayes Event-driven Stock Data takes full advantage of the massiveness of Datayes’ data, focusing on the development of events with a strong correlation to stock alpha, and is committed to generating event data with high alpha. The underlying data includes traditional data such as company, fund and financial announcements, as well as quotes, research reports, funds data and much more, which are combined with Datayes’ exclusive AI Revenue Forecast Data and other data. It retains event detail data to support further screening based on demand. The data used strictly guarantees PIT to avoid the use of future data.