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STOCHASTIC DIFFERENTIAL UTILITY
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DOI：10.2307/2951600.png)
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Abstract
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This paper presents a stochastic differential formulation of recursive utility. Sufficient conditions are given for existence, uniqueness, time consistency, monotonicity, continuity, risk aversion, concavity, and other properties. In the setting of Brownian information, recursive and intertemporal expected utility functions are observationally distinguishable. However, one cannot distinguish between a number of non-expected-utility theories of one-shot choice under uncertainty after they are suitably integrated into an intertemporal framework. In a smooth Markov setting, the stochastic differential utility model produces a generalization of the Hamilton-Jacobi-Bellman characterization of optimality. A companion paper explores the implications for asset prices.
Keywords:
CHOICE UNDER UNCERTAINTY
STOCHASTIC CONTROL
RECURSIVE UTILITY
BELLMAN EQUATION
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