I have basic knowledge in time series prediction and supervised/unsupervised machine learning algorithms (clustering, classification, decision tree, etc.) I am now given a task to predict a bunch of stock prices. Each stock has its previous trading price (a period of 18 months) as well as some other features: coupon, asset rating, industry, etc. I only know how to use time series analysis or supervised machine learning separately, I have no idea of how to combine these two together. Is there any particular algorithm that I can use as a predictive model? What are steps to combine both dynamic and static information? Any help will be appreciated!