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英文标题：
《Long Term Optimal Investment in Matrix Valued Factor Models》
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作者：
Scott Robertson, Hao Xing
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最新提交年份：
2014
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英文摘要：
Long term optimal investment problems are studied in a factor model with matrix valued state variables. Explicit parameter restrictions are obtained under which, for an isoelastic investor, the finite horizon value function and optimal strategy converge to their long-run counterparts as the investment horizon approaches infinity. This convergence also yields portfolio turnpikes for general utilities. By using results on large time behaviour of semi-linear partial differential equations, our analysis extends affine models, where the Wishart process drives investment opportunities, to a non-affine setting. Furthermore, in the affine setting, an example is constructed where the value function is not exponentially affine, in contrast to models with vector-valued state variables.
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中文摘要：
研究了具有矩阵值状态变量的因子模型中的长期最优投资问题。对于等弹性投资者，当投资期接近无穷大时，有限期价值函数和最优策略收敛到其长期对应的参数约束。这种融合还产生了一般公用事业的投资组合收费公路。通过使用关于半线性偏微分方程大时间行为的结果，我们的分析将Wishart过程驱动投资机会的仿射模型扩展到非仿射环境。此外，在仿射设置中，构造了一个值函数不是指数仿射的示例，与具有向量值状态变量的模型相比。
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分类信息：
一级分类：Quantitative Finance 数量金融学
二级分类：Mathematical Finance 数学金融学
分类描述：Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法，包括随机、概率和泛函分析、代数、几何和其他方法
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