We solve the optimal saving/portfolio-choice problem in an intertemporal recursive utility framework. To date, progress on this problem has been constrained by both the lack of analytical solutions and the computational burdens inherent in large-scale stochastic dynamic programs of this type. Our solution to this problem is sufficiently general to allow (i) risk aversion to vary independently of intertemporal substitution, (ii) many risky assets with stochastic properties that can exhibit very general dynamics, (iii) stochastic labor income that may be correlated with asset returns and/or follow life-cycle patterns, (iv) portfolio adjustment costs, and (v) time-nonseparabilities in preferences (e.g., habit formation and consumption durability). We use the Linear Exponential Quadratic Gaussian (LEQG) model as a starting point. We use perturbation methods around this analytical solution to derive decision rules for portfolios. Unlike previous models that have been solved by these methods, our baseline case is explicitly stochastic, which greatly enhances the accuracy of our approximations without imposing additional computational costs. Preliminary and incomplete. Previous versions of this work circulated under the titl
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