Journal of Empirical Finance, Volume 48, September 2018

在弹性动态依赖模型下的投资组合优化

作者：Mauro Bernardi (University of Padova)

Leopoldo Catania (Aarhus University and CREATES)

摘要：来自多元高阶条件矩的信号以及外生协变量中包含的信息可被理性投资者利用，以将其财富在不同的风险投资机会之间进行分配。本文提出了一种新的弹性动态copula模型，能够解释和预测多维度资产收益分布的时变形态。本文通过允许copula相关性参数的动态更新方程依赖于潜在马尔可夫转换过程以及外生协变量，来引入时变依赖性。作为模型规范的另一个关键要素，我们让单变量边际由基于条件分布的量表分数的更新机制驱动。这个框架允许我们在条件矩达到四阶时引入时变性。然后使用时变矩来建立投资组合分配策略，以最大化代表性理性投资者的效用函数。我们以经验评估所提出的模型在竞争性替代投资策略方面大大改善了最优投资组合分配。

Portfolio optimisation under flexible dynamic dependence modelling

Mauro Bernardi (University of Padova), Leopoldo Catania (Aarhus University and CREATES)

ABSTRACT

Signals coming from multivariate higher-order conditional moments as well as the information contained in exogenous covariates can be exploited by rational investors to allocate their wealth among different risky investment opportunities. This paper proposes a new flexible dynamic copula model being able to explain and forecast the time-varying shape of large dimensional asset returns distributions. The time-varying dependence is introduced by allowing the dynamic updating equation of the copula correlation parameters to depend on a latent Markov-switching process as well as on exogenous covariates. As a further key ingredient of the model specification, we let the univariate marginals to be driven by an updating mechanism based on the scaled score of the conditional distribution. This framework allows us to introduce time-variation in the conditional moments up to the fourth order. Time-varying moments are then used to build a portfolio allocation strategy that maximises the utility function of a representative rational investor. We empirically assess that the proposed model substantially improves the optimal portfolio allocation with respect to competing alternative investment strategies.

原文链接：https://www.sciencedirect.com/science/article/pii/S092753981830032X

翻译：陈然