Windjam

Think about 2 time-series data (i.e - stock returns) for each of the following:

daily movements and monthly movements.

The daily movements of 2 stocks will be noisy and volatile (i.e - 1 day it gives +0.4% return, the next -0.6%, etc). When you measure the correlation of the 2 stock returns using daily data, it will likely be very low.

Monthly movements: this will be less noisy for the 2 stocks and more correlated to each other.

In general, the longer out your data, the more "smoothed" it is. That is why high-frequency data is very noisy (which they call asynchronous). Also, because of this noise, correlation will be very low.

Hope that makes sense.