I have non-stationary time-series data (stationarity tested using ADF Test) for variables such as stock market returns, money supply, interest rates, exchange rate, inflation,etc. and I want to study the impact of these macroeconomic variables on stock returns.
I performed a linear regression which gave me spurious results (r-squared >0.9)
Now after testing these time series for unit roots using Augmented Dickey- Fuller test all of them were found to be non-stationary and hence the spurious regression. However their first differences were found to be stationary (for money supply - second difference was found to be stationary).
My question is how should I proceed now, can I apply linear regression to the first/second differences of these variables, would those results be non-spurious? If not, what is the way forward?
P.S. - I am an undergraduate student with very little knowledge about econometrics.