You are testing the empirical validity of asset pricing models. You have monthly return data on $100$ test portfolios over the previous $50$ years. You also have monthly data on the market portfolio return as well as the relative price change of crude oil. You can think of the relative price change of oil as a return for holding a reserve of oil. You carry out your research in four steps.

In the first step you estimate market betas for the test assets by estimating the regression

Ri$,$t$=\backslash$alpha i$+\backslash$beta iRM,t$+$ei$,$t$,$

where Ri$,$t is the excess return of test portfolio i in month t and RM$,$t

is the excess return of the market portfolio in month t$.$ You run this estimation for all each of the $100$ test portfolios and keep the market betas $(\backslash$beta i$).$ You now have $100$ market betas, one for each test portfolio.

In the second step, you estimate a two$-$factor model where the test portfolio excess returns depend on the market portfolio excess return and the excess return on oil

Ri$,$t$=\backslash$alpha i$+\backslash$beta iRM,t$+\backslash$gamma iRO,t$+$ei$,$t$,$

where RO$,$t is the excess return of oil in month t$.$ Again, you run this estimation for all each of the $100$ test portfolios and this time keep the oil price sensitivities $(\backslash$gamma i$).$ This gives you $100$ oil price sensitivities$,$ one for each test portfolio.

In the third step, you estimate the average excess returns for the test portfolios as

ARi$=1600$t$=1600$Ri$,$t$.$

This gives you $100$ average excess returns, one for each test portfolio. You also observe that the market portfolio has an average excess return of $0\mathrm{.}6\%.$

Now, in the fourth step, you get to the actual testing of the asset pricing models. You estimate a regression where you relate the average excess return of the test portfolios to their sensitivities to the market portfolio and the oil price:

ARi$=\backslash$lambda $0+\backslash$lambda $1\backslash$beta i$+\backslash$lambda $2\backslash$gamma i$+$ui$.$

This regression has $100$ observations, one for each test portfolio. The dependent variable is the average excess return ARi, and the explanatory variables are the sensitivity to the market portfolio $\backslash$beta i and the sensitivity to oil $\backslash$gamma i$.\backslash$lambda $0,\backslash$lambda $1,$ and $\backslash$lambda $2$

are the coefficients that you estimate.

Which of the following results would be consistent with the CAPM being the correct asset pricing model?

Select one:

a$)$

$\backslash$lambda $0=0,\backslash$lambda $1=0,$ and $\backslash$lambda $2=0\mathrm{.}006$

b$)$

$\backslash$lambda $0=0\mathrm{.}006,\backslash$lambda $1=0,$ and $\backslash$lambda $2=0$

c$)$

$\backslash$lambda $0=0$ and $\backslash$lambda $2!=0$

d$)$

$\backslash$lambda $1=\backslash$lambda $2$

e$)$

$\backslash$lambda $0=0$ and $\backslash$lambda $1>0$

f$)$

$\backslash$lambda $0=0,\backslash$lambda $1=0\mathrm{.}006,$ and $\backslash$lambda $2=0$