A Rational Multi-Asset Portfolio Rebalancing Decision-Making Framework
提出了一个量化决策框架，通过模拟资产回报不确定性和动态交易成本，优化多资产组合的再平衡策略，并量化其收益来源。
The authors propose a comprehensive, rigorous, and quantitative decision-making framework that considers the important elements for selecting an optimal multi-asset portfolio rebalancing strategy. These aspects are typically ignored in traditional rebalancing research, which either leverages one historical sample path for asset returns in the analysis or ignores transaction costs (or assumes static transaction costs) or does not propose an optimal rebalancing strategy. In particular, the proposed framework incorporates a simulation engine to model the inherent return uncertainty of assets as well as a dynamic transaction cost simulations model that links the bid–ask spread with the market condition, and a utility-based optimization engine that determines the optimal rebalancing strategy while simultaneously quantifying its benefit. Additionally, the framework allows for attributing the source of benefit of one rebalancing approach relative to another and in which market environments those benefits typically play out.