HJB

By using stochastic optimal control theory, the Hamilton _ Jacobi _ Bellman ( HJB ) equation for target function was gotten.

根据随机最优控制理论, 导出了目标函数满足的Hamilton_Jacobi_Bellman ( HJB ) 方程.

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HJB Equations Subject to Stochastic Control Theory and Securities Investment Models

随机控制的HJB方程与证券投资模型

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Based on the definition of the value function and the coefficient of risk aversion, the nonlinear transformation of value function was proved to be in agreement with HJB partial differential equation with the coefficient of risk aversion.

根据值函数和风险规避系数的定义，说明经非线性变换后的值函数满足带有风险规避系数的HJB偏微分方程。

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Abstract: This paper gives a proof of a comparison theorem on the viscosity solution of HJB Equation.

文摘：证明了与随机控制问题有关的动态规划方程粘性解的比较定理。

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This paper gives a proof of a comparison theorem on the viscosity solution of HJB Equation.

证明了与随机控制问题有关的动态规划方程粘性解的比较定理.

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From the HJB equation satisfied by the value function V ( x), we find the optimal stopping time τ.

通过建立值函数V（x）满足的HJB方程，我们找到了最优停止时刻τ。

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First the associated Hamilton-Jacobi-Bellman ( HJB ) equation is given, then its continuously differentiable solution is constructed.

首先给出了最优控制问题对应的Hamilton_Jacobi_ Bellman 方程, 接着构造出了它的连续可微解.

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Through the dynamic programming principle, we got the HJB equation which the optimal policy should satisfy.

通过动态规划原理，我们得到了最优策略应该满足的HIB方程。

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The continuity of the value function and the HJB equation value function satisfies are discussed.

讨论约束条件的描述,最优投资问题值函数的连续性,以及值函数所满足的HJB方程.

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