Stock trend prediction (STP) aims to predict the price fluctuation, which is critical in financial
trading. The existing STP approaches only use market data with the same granularity (such
as daily market data). However, in the actual financial investment, there are a large number
of more detailed investment signals contained in finer-grained data (eg, high-frequency
data). This motivates us to research how to leverage multi-granularity market data to capture
more useful information and improve the accuracy in the task of STP. However, the effective …

Stock trend prediction (STP) aims to predict price fluctuation, which is critical in financial
trading. The existing STP approaches only use market data with the same granularity (eg, as
daily market data). However, in the actual financial investment, there are a large number of
more detailed investment signals contained in finer-grained data (eg, high-frequency data).
This motivates us to research how to leverage multi-granularity market data to capture more
useful information and improve the accuracy in the task of STP. However, the effective …