I am trying to construct a portfolio whose return is $a + bm_{t+1}$ where $a$ and $b$ are some constants for a certain investor. $m_{t+1}$ is the stochastic discount factor at time $t+1$.
I am guessing that to have $a$ as return, you would have to buy $\frac{a}{1+r_f}$ units of the risk-free asset, whose existence we take for granted. Here $r_f$ is the risk-free interest rate.
Then for the portfolio that returns $m_{t+1}$, I proceed as follows. I have been given the hint that I should consider the regression $m_{t+1} = \sum_j^J \beta_jR_{j,t+1} +\varepsilon_{t+1}$ with $E[\varepsilon_{t+1}R_{i,t+1}] = 0$ for all $i=1,\ldots,J$. Here $R_{i,t+1}$ is the return on asset $i$ and $J$ is the total number of assets.
My guess was to find a $(\beta_j)_{j=1,\ldots,J}$ such that $m_{t+1} = \sum_j^J \beta_jR_{j,t+1}$ almost surely. Then if I show that $$E[\lvert m_{t+1}-\sum_j^J \beta_jR_{j,t+1}\rvert^2] = 0$$ I will have what I want.
This gives me something like $E[m_{t+1}^2] = \sum_j^J \beta_j$. I am not sure where I am going with this to be honest. I am fairly new to this stuff. I would appreciate it if someone could put me on the right path in solving this problem. Thanks.