Would it be feasible to incorporate these weekly/monthly variables into the model? Given their lower frequency their values would have to repeat, given that the dependent variable is captured on a daily frequency. How should I interpret the coefficients of these lower frequency variables then? My reasoning is that I don't want to leave these variables out of the model because they do act as a shock to soybean prices when the reports are published (depending on whether the data surprised), and my sense is that there's probably "long-lasting" effect on prices until the next report is released.

I've read that MIDAS models could be a good approach here but just wondering how do those models differ from a linear regression model where the lower frequency independent variables are simply repeated along the factor columns?

Much appreciated!