Solving Consumption and Portfolio Choice Problems: The State Variable Decomposition Method
提出一种状态变量分解法，通过将状态变量分解为投资者可观测部分和随机偏差，并利用泰勒展开近似值函数的条件期望，高效求解离散时间动态投资组合选择问题，适用于多资产、多状态变量、组合约束等复杂情形。
We develop a new solution method for a broad class of discrete-time dynamic portfolio choice problems. The method efficiently approximates conditional expectations of the value function by using (i) a decomposition of the state variables into a component observable by the investor and a stochastic deviation; and (ii) a Taylor expansion of the value function. We illustrate the accuracy of the method in handling several realistic features of portfolio choice problems such as intermediate consumption, multiple assets, multiple state variables, portfolio constraints, non-time-separable preferences, and nonredundant endogenous state variables. We finally use the method to solve a realistic large-scale life-cycle portfolio choice and consumption problem with predictable expected returns and recursive preferences. The Author 2010. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.