Multi-Stage Optimization For Long-Term Investors
Multi-Stage Optimization For Long-Term Investors
复制标题
针对长期投资者的多阶段优化
DOI：
10.1142/9789812778451_0003
复制
发表时间：
2002
期刊：
影响因子：
--
通讯作者：
J. Mulvey
中科院分区：
文献类型：
--
作者：
J. Mulvey
多阶段模拟优化模型是解决长期财务规划问题的有效方法。突出的例子包括：养老金计划的资产负债管理、保险公司的综合风险管理以及个人的长期规划。几个应用程序将简要提及。一个多阶段的框架提供了优于单周期近视的方法。首先，投资者了解长期目标无法实现的风险，例如退休时拥有足够的财富。多阶段模型可能比单周期模型更真实。因此，股权等资产可以降低长期风险，同时增加短期波动性，可以在时间环境中进行评估。在多期背景下，长期收益和短期收益之间的权衡变得明显。第二个优势是，动态投资策略可以提高回报。例如，当资产波动性增加时，将资产重新平衡到固定战略基准的传统方法会产生更高的回报。这种“波动性抽水”受到交易和市场影响成本的抑制。只有通过求解多阶段优化模型，才能发现最优的再平衡规则。同样，将一个大的投资组合转移到一个新的战略基准可以得到优化。第三个例子是，个人通常持有内含大量收益的资产。出售这些资产会引发资本利得税。同样，这些决定可以通过多阶段模型进行评估。养老金规划的一个实际例子说明了这些概念。三种不同的方法可用于求解多阶段优化模型：（1）动态随机控制，（2）随机规划，和（3）优化随机模拟模型。我们简要回顾了这些方法的优缺点;似乎不太可能有一种方法会主导其他方法。最后，我们总结了一些未来研究的主题。
AbstractMulti-stage simulation and optimization models are effective for solving long-term financial planning problems. Prominent examples include: asset-liability management for pension plans, integrated risk management for insurance companies, and long-term planning for individuals. Several applications will be briefly mentioned.A multi-stage framework provides advantages over single-period myopic approaches. First, the investor gains an understanding of the risks that a long-term goal will be unfulfilled, such as retiring with adequate wealth. A multi-stage model can be more realistic than a single period model. Thus, assets such as equity, which reduce long-term risks while increasing short-term volatility, can be evaluated in a temporal setting. The tradeoff between long- and short-term gains becomes apparent in a multi-period context. As a second advantage, enhanced returns are possible with dynamic investment strategies. For instance, the traditional approach of rebalancing assets to a fixed strategic benchmark generates higher returns when assets possess increased volatility. This “volatility pumping” is dampened by transaction and market impact costs. Only by solving a multi-stage optimization model can we discover the optimal rebalancing rules. Likewise, moving a large portfolio to a new strategic benchmark can be optimized. As a third example, individuals often hold assets with large embedded gains. Selling these assets triggers a capital gains tax. Again, these decisions can be evaluated by means of a multi-stage model. A real-world example from pension planning illustrates the concepts.Three distinct approaches are available for solving the multi-stage optimization model: (1) dynamic stochastic control, (2) stochastic programming, and (3) optimizing a stochastic simulation model. We briefly review the pros and cons of these approaches; it seems unlikely that a single approach will dominate the others. We conclude with some topics for future research.