# Can a momentum strategy be cast as a multilinear regression model?

Disclaimer: the question is similar to

Can momentum strategies be quantitative in nature?

and (to an extent)

What is the expected return I should use for the momentum strategy in MV optimization framework?

However (on the surface of it), I did not quite find a desirable answer.

Can a momentum strategy be expressed as something to the effect of $$r = \beta_0 + \beta_1 \frac{\mathrm{ten\_day\_moving\_average}}{\mathrm{hundred\_day\_moving\_average}} + \epsilon$$ or any other combination of predictors ($x_{2}$, $x_{3}$, ...); or maybe as some nonlinear model?

• A dissenting view: because a momentum strategy has a go/no go character, switching abruptly between long and not long, it is not particularly helpful to analyze the ratio $\frac{\mathrm{ten\_day\_moving\_average}}{\mathrm{hundred\_day\_moving\_average}}$ which varies continuously. To put it in stochastic control theory terms, the control function is discontinuous in this problem. – noob2 May 26 '17 at 15:10