Is there any time series model which handles data at variable frequencies.? Goal: Predict the yellow points.(yellow events appear at varying frequencies)

But I'm struggling to find a good model to fit this use case. 
Most of the time series algorithms are handling data which are at same frequencies(like per day/every 10 secs). I tried a lot of stuff but may be completely on the wrong approach.


Thanks a lot for any hint!!!
It looks like stock price data. You can use fbprophet(python),BATS(R),TBATS(R) to predict the data. 
You said your model contains different frequencies which mean it contains more than one seasonality.
To find seasonality(frequencies) you can use Fourier transform. You should have significant data to get a good prediction