Just a general question that I couldn't find too much on.
What would be some good approaches to one step ahead forecasting of financial time series with mixed frequencies?
Often a lot of the available data influencing the price of say a stock or commodity is published at different frequencies, some daily, some weekly, some monthly etc. which in my head makes it tricky to use normal models for anything but the longest time interval.
Edit: found this paper which goes some way to cover the topic