Optimal long-term investment model with memory
Optimal long-term investment model with memory
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DOI：
10.1007/s00245-006-0867-0
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发表时间：
2007-01-01
影响因子：
1.8
通讯作者：
Nakano, Yumiharu
中科院分区：
文献类型：
--
作者：
Inoue, Akihiko;Nakano, Yumiharu
考虑了一个由不同于布朗运动的平稳增量的Rn值高斯过程驱动的金融市场模型。这个驱动噪声过程由n个独立的分量组成，每个分量具有由两个参数描述的记忆。对于这个市场模型，我们明确地解决最优投资问题。其中包括：（i）默顿的投资组合优化问题;（ii）财富在无限范围内的预期效用增长率的最大化;（iii）财富以高于给定基准的速度增长的大偏差概率的最大化。还考虑了参数的估计。
We consider a financial market model driven by an R-n-valued Gaussian process with stationary increments which is different from Brownian motion. This driving-noise process consists of n independent components, and each component has memory described by two parameters. For this market model, we explicitly solve optimal investment problems. These include: (i) Merton's portfolio optimization problem; (ii) the maximization of growth rate of expected utility of wealth over the infinite horizon; (iii) the maximization of the large deviation probability that the wealth grows at a higher rate than a given benchmark. The estimation of parameters is also considered.