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Asset Pricing John H. Cochrane June 12, 2000

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where<br />

CHAPTER 3 CONTINGENT CLAIMS MARKETS<br />

R f ≡ 1/ X pc(s) =1/E(m).<br />

The π ∗ (s) are positive, less than or equal to one and sum to one, so they are a legitimate set<br />

of probabilities. Then we can rewrite the asset pricing formula as<br />

p(x) = X<br />

s<br />

pc(s)x(s) = 1<br />

Rf X<br />

∗ E<br />

π (s)x(s) = ∗ (x)<br />

Rf .<br />

I use the notation E∗ to remind us that the expectation uses the risk neutral probabilities π∗ instead of the real probabilities π.<br />

Thus, we can think of asset pricing as if agents are all risk neutral, but with probabilities<br />

π∗ in the place of the true probabilities π. The probabilities π∗ gives greater weight to states<br />

with higher than average marginal utility m.<br />

There is something very deep in this idea: risk aversion is equivalent to paying more<br />

attention to unpleasant states, relative to their actual probability of occurrence. People who<br />

report high subjective probabilities of unpleasant events like plane crashes may not have<br />

irrational expectations, they may simply be reporting the risk neutral probabilities or the<br />

product m × π. This product is after all the most important piece of information for many<br />

decisions: pay a lot of attention to contingencies that are either highly probable or that are<br />

improbable but have disastrous consequences.<br />

The transformation from actual to risk-neutral probabilities is given by<br />

π ∗ (s) = m(s)<br />

E(m) π(s).<br />

We can also think of the discount factor m as the derivative or change of measure from the<br />

real probabilities π to the subjective probabilities π∗ . The risk-neutral probability representation<br />

of asset pricing is quite common, especially in derivative pricing where the results are<br />

independent of risk adjustments.<br />

The risk-neutral representation is particularly popular in continuous time diffusion processes,<br />

because we can adjust only the means, leaving the covariances alone. In discrete time,<br />

changing the probabilities typically changes first and second moments. Suppose we start with<br />

a process for prices and discount factor<br />

dp<br />

p = µp dt + σ p dz<br />

dΛ<br />

Λ = µΛ dt + σ Λ dz.<br />

56

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