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arXiv 1102.1186q-fin.PMmath.PRq-fin.CPq-fin.PR
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随机系数市场的最优消费与投资

Optimal consumption and investment for markets with random coefficients

Berdjane Belkacem, Serguei Pergamenchtchikov

摘要:

本文考虑了一个由扩散过程驱动的具有随机系数的Black-Scholes金融市场的最优投资和消费问题。我们假设一个智能体基于CRRA效用函数做出消费和投资决策。利用动态规划方法研究了Hamilton Jacobi Bellman(HJB)方程,该方程是一个高度非线性的二阶偏微分方程。利用Feynman-Kac表示证明了解的唯一性和光滑性.此外,我们研究了价值函数和最优投资组合的迭代数值格式的最优收敛速度。我们表明,在这种情况下,最佳的收敛速度是超几何的,即比任何几何的更快。我们将我们的结果应用到一个随机波动率的金融市场。

英文摘要:

We consider an optimal investment and consumption problem for a Black-Scholes financial market with stochastic coefficients driven by a diffusion process. We assume that an agent makes consumption and investment decisions based on CRRA utility functions. The dynamical programming approach leads to an investigation of the Hamilton Jacobi Bellman (HJB) equation which is a highly non linear partial differential equation (PDE) of the second oder. By using the Feynman - Kac representation we prove uniqueness and smoothness of the solution. Moreover, we study the optimal convergence rate of the iterative numerical schemes for both the value function and the optimal portfolio. We show, that in this case, the optimal convergence rate is super geometrical, i.e. is more rapid than any geometrical one. We apply our results to a stochastic volatility financial market.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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