There are some powerful stock analysis libraries in R that make time series forecasting fairly straightforward with ARIMA. Included are tests used to check for stationarity, a measurement of a time series' mean, variance, etc. remain constant over time in addition to any necessary transformations with diff functions.
Stock data can be loaded directly into R using a few different libraries (tidyverse, et al) or from a CSV of adjusted returns from Yahoo finance.