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Asset Pricing John H. Cochrane June 12, 2000

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SECTION 2.3 CONSUMPTION-BASED MODEL IN PRACTICE<br />

production technology. Having a taste of the extra assumptions required for a general equilibrium<br />

model, you can now appreciate why people stop short of full solutions when they can<br />

address an application using only the first order conditions, using knowledge of E(mx) to<br />

make a prediction about p.<br />

It is enormously tempting to slide into an interpretation that E(mx) determines p. Weroutinely<br />

think of betas and factor risk prices – components of E(mx) –asdetermining expected<br />

returns. For example, we routinely say things like “the expected return of a stock increased<br />

because the firm took on riskier projects, thereby increasing its β.” But the whole consumption<br />

process, discount factor, and factor risk premia change when the production technology<br />

changes. Similarly, we are on thin ice if we say anything about the effects of policy interventions,<br />

new markets and so on. The equilibrium consumption or asset return process one has<br />

modeled statistically may change in response to such changes in structure. For such questions<br />

one really needs to start thinking in general equilibrium terms. It may help to remember<br />

that there is an army of permanent-income macroeconomists who make precisely the opposite<br />

assumption, taking our asset return processes as exogenous and studying (endogenous)<br />

consumption and savings decisions.<br />

2.3 Consumption-based model in practice<br />

The consumption-based model is, in principle, a complete answer to all asset pricing<br />

questions, but works poorly in practice. This observation motivates other asset pricing models.<br />

The model I have sketched so far can, in principle, give a compete answer to all the<br />

questions of the theory of valuation. It can be applied to any security—bonds, stocks, options,<br />

futures, etc.—or to any uncertain cash flow. All we need is a functional form for utility,<br />

numerical values for the parameters, and a statistical model for the conditional distribution of<br />

consumption and payoffs.<br />

To be specific, consider the standard power utility function<br />

Then, excess returns should obey<br />

"<br />

0=Et β<br />

u 0 (c) =c −γ . (41)<br />

µ −γ<br />

ct+1<br />

R<br />

ct<br />

e t+1<br />

Taking unconditional expectations and applying the covariance decomposition, expected ex-<br />

47<br />

#<br />

(42)

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