I am new to time series forecasting and looking to compare the performance of ARIMA/Prophet with an XGBoost model in predicting future stock market values based on historical stock market data *and* social media sentiment scores.

I am more familiar with machine learning, so would usually use an evaluation metric like $R^2$ to assess model performance for this sort of problem.

Are there any common evaluation metrics which forecasting methods like ARIMA/Prophet use to assess their accuracy, so I can do a like-for-like comparison with the XGBoost's prediction accuracy?