Estimating parameters using Lasso Regression in Python

I'm a begginer and my goal is to estimate these parameters (a0, a1, a2, a3) from the following model:

SPXret(h) = a0 + a1*SPX(t) + a2*VIX(t) + a3*IVTS(t)


where:

• SPXret(h) = log(SPX(t+h)) - log(SPX(t)) -- h is the forecast horizon in days
• SPX(t) = the current SPX value
• VIX(t) = the current VIX value
• IVTS(t) = VIX(t) / VIX3M(t)

I have been trying to use the python library sklean.linear_model (https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lasso.html) without success because I don't know how to use it, I would really appreciate it if anyone could guide me here, my background isn't maths.

• What have you done so far and where are you stuck exactly? The sklearn documentation gives examples for Lasso. Sep 14 at 10:52