How to calculate a financial beta and theta (time decay) in R linear regression?

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I have the following code trying to calculate a beta (if priceA goes up 1, then priceY goes up X) and theta (each month that passes priceY goes down Z).

lmS9 = lm(priceY ~ months_past + priceA, data = S9)
summary(lmS9)

It prints the following:

              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  1.172e+03  3.126e+02   3.750 0.000854 ***
months_past -5.620e+01  2.019e+01  -2.783 0.009703 ** 
priceA       1.959e-01  9.945e-03  19.701  < 2e-16 ***

Both are significant input variables, but I'm not sure if I'm interpreting it correctly.

In the example above months_past would be theta and priceA would be a form of beta. Is that correct? How can I create a coefficient that says if priceA goes up 1%, the priceY goes up Z?

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