My goal is to deploy an ML model which can perform price prediction on an exchange traded fund (ETF) - which is essentially an aggregation of stocks. A very popular ETF is the S&P 500 (which is not actually the ETF I want to predict on. The one I want to predict on only has about 30 stocks).

Can an ML model trained/tested on individual stocks which are *not* in the ETF a valid way of building a model which can accomplish price prediction on an ETF?